Maintenance Manager Mel wakes up and turns on his EU (entertainment unit), a combination of a television, music system, computer, and Internet access rolled into one. As he drinks his first cup of coffee, a streaming download from work appears in the corner of the screen. As he watches the news, he also sees that the third shift has completed preventive maintenance on the HVAC unit in building one.

He also notes that 15 new work orders have come in during the night, most of them generated automatically by the building's systems. The moisture sensors on the fifth floor picked up a small roof leak, accessed the warranty information, and have already forwarded the work order to the roofing contractor. He has already posted that he will be out by noon to start the work. Two airflow sensors picked up a drop in performance in some of the HVAC equipment and have created work orders based on the data and posted job plans based on the probable causes.

Mel marks these for review by the shift supervisor to pick the best course of action. Before Mel leaves the comfort of his home, he assigns the work orders to the shift supervisors using a Neural Input Device (NID) that he wears on his fingertip. It provides him the capability to use the computer without typing, using his own brain to control the data.

On the way into work he opens a communications link and does a check of his day's calendar and of the current backlog of work. The system has assigned a number of work orders already to his staff. In the car, he makes some last-minute adjustments. The car is tied to an auto-guide program that sets its speed and literally chauffeurs the vehicle to the office with no human intervention. While he finishes that second cup of coffee, Mel pulls down a copy of the Washington Times to check the sports scores from the night before. He is a little old-fashioned, still going to the news sites rather than the direct data feeds from the teams themselves.

At the office, the maintenance team is already on the job. Each is wearing a tiny device that holds out a small transparent piece of plastic in front of the eye. The device is fitted with a camera and is lighter than a pair of eyeglasses. On the small square of transparent material, an image is projected showing the details of the work order.

What makes the work order so different from old fashioned ones is that it can play video and audio as part of the instructions, all done by voice command from the wearer. It also is linked directly to the manufacturer of both the parts and the equipment itself, pulling down whatever specifications are necessary as well as the exact manufacturing standards. This information is constantly updated and current because it is stored right at the manufacturer, and includes all parts recalls, known problems from other customers, and their resolutions.

As a worker opens the equipment, he notices some burn marks near the circuit housing. Using the camera in the tiny headset, he zooms in on the image and opens a communications link to the manufacturer. A check of known data does not show any probable causes, so the maintenance worker is directly linked to one of the engineers who designed the unit. He can see the image being broadcast and asks the maintenance worker to remove the panel. Inside he sees a burned out board. Asking the worker to zoom in on the part number, he pulls up a feed to the part's manufacturer. It turns out that a recall was in place on this part. Any damage caused by it is covered by the manufacturer.

An RMA is cut online, while the worker pulls the board and checks inventory to see if there are any others in stock. There is, in a crib across town. He reserves the part and, using the messaging system built into his headset-data feed, asks a runner to go over and pick it up. Using his own finger-worn NID, he updates the work order and includes a video image of the burn marks so if the problem occurs again, no one will have to waste the 15 minutes it took him to track down the problem.

Yes, this sounds like fantasy, but in reality, all this technology exists or is being developed today. NIDs are still in their infancy, but by 2012, they could be reality. The integration of this technology is happening all around us and is in the process of being tested and deployed. The impact on the maintenance operations, as well as the business world as a whole, is not too far away. This passes the era of the smart buildings, and enters the realm of smart departments/companies.

Robert C. Baldwin, CMRP, Editor

We also gather reader opinions in other areas. This year we investigated the relative importance of various reliability and maintenance issues such as installing CMMS, training, predictive maintenance, spare parts management, contract service management, maintenance work planning, safety and environment, and dealing with upper management.

The questionnaire asked the reader to "indicate the relative emphasis or effort being expended by you and your department in the following areas".

Survey participants were asked to provide answers for their personal effort and for department emphasis using the following scale: 4 = emergency priority, 3 = major effort, 2 = considerable effort, 1 = routine, under control, and 0 = none.

The reliability and maintenance issues on the questionnaire, arranged here in decreasing importance by the simple average of respondent scores, were:

• Responding to challenging health, environmental, or safety issues. Average score was 1.79, with 29 percent of respondents stressed by major effort (3 or 4) and 49 percent of respondents OK, having this area under control (0 or 1).
• Improving work planning and job scheduling systems and processes (1.64 score, 20 percent stressed, 49 percent OK).
• Finding and training reliability and maintenance employees (1.53 score, 19 percent stressed, 47 percent OK).
• Installing or improving condition monitoring or predictive maintenance systems and processes (1.50 score, 20 percent stressed, 52 percent OK).
• Developing improved strategies and processes and negotiating with upper management (1.44 score, 16 percent stressed, 54 percent OK).
• Improving parts procurement and inventory management systems and processes (1.35 score, 13 percent stressed, 59 percent OK).
• Installing or improving CMMS, EAM, or other information systems (1.25 score, 16 percent stressed, 61 percent OK).
• Managing and directing contract service providers (1.23 score, 11 percent stressed, 66 percent OK).

By all measures, the spotlight is on safety, health, and the environment. Are you comfortable with your focus? MT

Audits in general are associated with investigation and reform, particularly in present industrial environments where change is interpreted as a survival strategy rather than a controlled improvement process. Many organizations have experienced audits in safety, quality, or environmental and financial management; however, few companies have considered maintenance audits.

Maintenance costs have been quoted to represent between 5 and 40 percent of the total cost to make a product. Furthermore, the effectiveness of maintenance directly affects equipment performance. As competitive pressures grow, management must look for ways to reduce costs. Quite often decisions involve a reduction of employees, contractors, spares, and training when other options may exist. Unfortunately, these decisions are often made without a real understanding of the consequencesand, most importantly, without understanding the real cost drivers.

Business owners are good at making strategic product decisions because that is their core competence. However, very few business owners can make good business decisions regarding maintenance because maintenance is not their core competence.

Case studies
Here are three typical scenarios showcasing reasons companies may want to conduct maintenance audits.

Scenario 1. A paper company was in the process of purchasing three paper mills in different locations. These mills were not meeting performance standards, and there appeared to be a need for quick improvements to the process, the organizational structure, and the overall maintenance performance.

The new owners reviewed the papermaking operations and knew what was required to achieve business budget requirements. They requested a maintenance audit in order to understand their total investment needs.

The audit revealed the need for a greater investment in maintenance tools, systems, organizational structure, training, and maintenance strategy effectiveness. With this information available, the owners recognized the potential for a quick return on their investment by concentrating on their core businesspapermakingand outsourcing maintenance to a company whose core competence was the business of maintenance.

The resulting business partnership was successful because it was based on expected performance indicators and continuous improvement.

Scenario 2. A large cement company was building a new plant next to an existing plant that had not been performing to budget expectations. A maintenance audit was carried out to identify maintenance effectiveness and specific requirements needed to improve performance at the existing plant and, most importantly, to provide management with a clear understanding of the maintenance requirements of the new plant.

The audit identified an improvement strategy for the existing plant. By operating the existing plant more efficiently, the company achieved potential cost benefits to actually fund the existing plants improvement program and the maintenance tools and strategy development for the new plant.

Scenario 3. The corporate body of a company with seven plants at different locations wanted to improve overall plant performance and increase profitability. The company used the maintenance audit process to identify opportunities for improvements at each site and to create common benchmarks, standardization, transfer of best practices, methods, tools, and resources.

The audit was customized to represent the business and was sold to the company. A working team of plant managers was formed so they could be trained in the maintenance audit and best practice maintenance business. An audit engineer was assigned to the working team to lead the project and to assist in developing individual plant improvement programs and corporate benchmarking requirements.

Why conduct audits
The main reason for conducting maintenance audits is to improve plant performance and to increase profits. Put simply, companies produce a marketable product for profit and businesses invest in equipment and processes to produce this product with confidence.

However, the availability and productivity of the equipment and processes are determined by maintenance effectiveness.

Most companies do not have a core competency in maintenance management and, in particular, do not understand the true consequences of maintenance inefficiencies.

The maintenance audit identifies the effectiveness and maturity of key elements in the maintenance business and provides accurate data for decision making with the best interests of the company, business, and the organization in mind.

The audit process
The audit process is conducted on site and reviews key elements systematically. This is done by:

• Interviewing key people in the organization (including preferred suppliers and preferred contractors)
• Conducting site inspections of equipment and facilities
• Reviewing process flows and mapping maintenance functions and controls
• Reviewing stores management, documentation management, and control
• Demonstrating systems application
• Attending key meetings
• Becoming involved in all maintenance functions
• Validating plant, equipment, and maintenance performance

Maintenance audit results
It is imperative that the audit results are represented in a format understood by management and the people audited. Carrying out a presentation before and after the audit ensures maximum understanding and cooperation.

Audit results are provided in the following format:

1. Management summary and essential recommendations
2. Audit evaluation table for each element
3. Audit summary sheets for each principal function
4. Audit comments and recommendations for each element

Based on the audit results and recommendations, a continuous improvement plan should be developed and implemented to achieve optimal results.

Auditing tools
Siemens Westinghouse Technical Services has developed a number of tools to use when it conducts a maintenance audit.

Organizational structure determination. Most organizations are divided into three segments: Management, Systems and Procedures, and Personnel and Resources (the workforce). Each of these areas is made up of key elements and vital links to determine the effectiveness and success of the organization.

Management responsibility is aligned with the value chain of the business and represents the who, what, why, and how in order to successfully maintain or capture market share of the product. Most importantly, management determines the business reasons for maintenance.

Systems and Procedures are the tools, either imported or developed within the organization, to effectively administer management's visions and requirements and to provide best practice assistance to the workforce.

Personnel and Resources carry out the work within the performance expectations of management.

The links between these three key areas are the drivers of organizational culture and directly represent management's commitment and leadership.

A thorough maintenance systems audit has to question all of these areas and links in order to present a total understanding of the business. Management then will have a benchmark with appropriate recommendations to minimize waste of resources and employ best practice principles to areas or service in line with the business plan.

Audit evaluation table. The audit evaluation table is formatted to provide an objective assessment of each element. The purpose of this is to provide the auditor with an understanding of the status of the maintenance function development within the company.

The Assessment Levels pyramid is based on the principles of continuous improvement. The top of the pyramid represents the most specific, advanced level of assessment. Similar evaluation tables are commonly used to represent progress in maintenance organizations.

Audit summary sheets. These summary sheets are commonly used to prepare short- and long-term improvement programs focused on recommendations and requirements.

For example, if management agrees that financial control is an element that has to be improved to better manage maintenance expenditure and asset performance, these decisions have to be made:

• The level of control which should be achieved in the next one to two years
• Whether support systems are in place
• Who will be responsible and what the performance requirements are
• Required training
• Benefits that can be achieved and measured
• Cost of this exercise

As each element result is compared to the business plan, management can use a report summary to represent the continuous improvement plan required in order to achieve future business direction.

If this is carried out correctly, management will invest wisely to improve the principal elements in order to achieve their goals. Furthermore, they also will provide a plan for the future that can be reviewed to ensure that the improvement plan is on target.

A maintenance audit should be the building block for proactive decision making because cost-effective improvement can be accomplished only when management understands the effectiveness of the maintenance organization. An audit provides the framework and benchmarks for targeted continuous improvement with a clear understanding of the gaps and needs among the three primary areas of the organization. MT

Joe Zancolich is a senior maintenance consultant for Siemens Westinghouse Technical Services, a business of Siemens Energy & Automation, Inc., 100 Technology Dr., Alpharetta, GA 30005; (770) 740-3639.

While there are a number of issues to be resolved, the wireless world seems inevitable, at least according to the reviews by industry experts. The convergence of the Internet and this wireless world holds the promise of many opportunities for maintenance personnel to increase their efficiency and ultimately reduce operating costs.

With computerized maintenance management systems (CMMS) now available for use over the Internet from application service providers (ASP) for a rental fee, one part of the puzzle is in place. The promise of wireless technology is that maintenance personnel can access, from any work location, their CMMS application to review work orders, check manuals and equipment drawings, enter labor and parts used, or browse the Internet for pertinent information.

For more than a year now, on-line software rental has allowed organizations to use sophisticated software applications on their personal computers for a low monthly service fee. Internet delivery of maintenance management software reduces the overall cost of the CMMS application, while it eliminates the need of organizations to maintain and upgrade these software modules. This is all part of the service included in the monthly rental fee, as is implementation assistance, training, and on-going support. (See accompanying section "ASP Delivery Model.")

The wireless connection
With this CMMS software delivery model in place, we have to determine the part to be played by wireless technologies. These technologies need to be reviewed to evaluate what benefits flexible communications can bring to the maintenance department. Ask the following questions:

• Is the fundamental design and concept reasonable? Is it feasible to have a general-purpose handheld device that allows access to all of the features of a CMMS, and what are the benefits of increased information, such as drawings and manuals, on a handheld device?
• Is immediate notification about the receipt of an inventory part required, or can the stockroom simply notify the tradesman via the paging system?
• Is time saved by entering work time on a handheld device? More importantly, do we want the tradesman burdened with another tool when he can have a full-sized PC screen to enter his time?
• Are the technologies available to deliver these features? We have not seen a single PDA that effectively delivers voice, data, and Windows, and standards are still evolving for the communication between these devices.

The cost of supporting wired infrastructures and their inherent static design provides a significant opportunity for wireless technology. We are in the early stages of delivering the technology to a maintenance department because much of what is reviewed is material such as pictures, drawings, text, and manuals.

Three tools or one?
Based on my review of the state of wireless technologies, a maintenance staffer would need a pager, cell phone, and handheld computer in his toolbox to deliver all of the hype promised. He also would need communications protocols from one of the five or six major suppliers.

Unfortunately, these protocols are neither standard nor compatible between different devices. Europe has adopted a standard called Global System for Mobile Communications, while North America has several competing standards. Pagers will work in most environments, cell phones will work only in certain areas, and handheld devices are supported only in large cities for on-line Internet access.

In certain specialized areas where mobility is the main criteria, such as for service management personnel, contractors, or managers of multiple facilities, there is definitely a benefit to using wireless technology to provide information at the service site. For plant maintenance personnel, wireless has a fairly limited application at this time because of the size of the devices and the need to have more than one device.

But, there is hope. The next generation of devices is predicted to combine the necessary features that would be beneficial for a maintenance department. The incorporation of an Internet browser in a cell phone allows the sourcing of parts and specifications via the Internet. It also allows limited database access to the CMMS. The necessary communications protocol will be available in most areas of North America in the near future.

When these events take place, maintenance personnel will be able to remotely sign on to their Internet-delivered CMMS application, review parts availability, select the preferred supplier, call the supplier, place a requisition on the system, receive notification when the part arrives, and surf the Internet for the latest manual on the appropriate piece of equipment.

The convergence of these technologies is happening today, but until that time, I suggest we continue to use the proven approach of a phone, pager, bar coding, and desktop PC to provide the information needed for maintenance operations. MT

Information supplied by R.W. (Bob) Mutch, president of MegaMation Systems Inc., Oakville, ON; (905) 844-9947.

In the baseline article for this series, "Be Brilliant With the Basics" (MT 3/00, p 41), six basic elements of maintenance were proposed. The third of these basic elements was to make work planning an integral part of the maintenance process.

That article posed the following questions for this element of maintenance where the answers gauged a facility's adherence to the basics:

• Are there permanently assigned maintenance planners?
• Are there identified and trained back-up maintenance planners?
• Is the planner's "product" a well-developed job package, which clearly details the scope of the work to be done?
• Do the maintenance planners plan for the future and not engage in day-to-day activities such as expediting parts for emergency work?
• Do maintenance planners have access to a complete and accurate bill of materials for the facility assets?
• Do maintenance planners have an accurate and active backlog of work?
• Are maintenance planners' contributions to the maintenance organization equal to or greater than their costs?
• Is the effectiveness of maintenance planners measured?

The job planning process is that portion of the overall planning function that focuses on the efficiencies of individual work orders. In reality, job planning only provides the opportunity to achieve efficiencies and to avoid delays. Taking advantage of opportunities created by job planning requires coordination and cooperation of production supervisors, maintenance supervisors, and maintenance craftspersons to use job planning in ways that actually reduce the time it takes to complete each job.

Although it is recognized that not all work orders need to go through the entire formal job planning process, all jobs actually get planned to one extent or another, either before or after the work starts. Depending on the nature of the job and its affect on safety or production, it is most often an advantage to plan work before the job actually begins.

Planning adds value
Why have maintenance planners, a planning organization, and a planning structure that drives proactive maintenance? Well-established and trained planning organizations bring value to businesses in excess of their costs. More maintenance work is accomplished in less time using the same resources than would be the case if the planning function did not exist. If the bottom line is not improved by having a planning function, it is usually the result of poorly defined roles and responsibilities, an absence of understanding of the planning role and its value, a lack of support from management, insufficient planner training, or having the wrong people in the planning role.

The way work is planned in industry varies widely. In some plants it is a process driven by the culture of the facility. At others, it is a blend of culture and a formal system. In some facilities, it is strictly a process-driven function. Some plants do not feel the need to have a planning organization. Others have tried to implement planning, but have not been successful for a variety of reasons and have dissolved the planning organization.

Some organizations have maintenance planners in place and functioning within a planning model that is structured and controlled. In this environment, planners plan. Their focus is the future, one to two weeks out. Their days are consumed with the fundamentals of producing planned job packages, and then working with maintenance and production to schedule the most appropriate date and time to implement the work package. The planners in these organizations own the backlog. They keep the backlog clean through periodic scrubbing to eliminate duplicate work, work that has been accomplished and not reported complete, or work that is no longer desired to be done.

Others have organizational charts that show planners who, in reality, are mostly parts expediters for current work activities. These individuals do not produce work packages that improve the efficiency of the craftspersons because they do not have time. The planner in this type of organization is reacting to current events instead of planning for future events, which is a fundamental violation of the basics of maintenance. It is well recognized that someone needs to perform the expediter role but it is always recommended that it not be the planner. Some organizations do not have trained back-up planners so a gap caused by vacation or illness is filled by the maintenance supervisor or one of the craftspersons.

Some organizations have the area maintenance supervisor perform the role of planner. In this situation, the supervisor is rarely the one who does the planning activity. It is pushed down to the craftsperson. The results are that several individuals (the craftspeople) are performing tasks they were not trained to perform and wasting productive time trying to figure how to resource each job. Each is identifying the work to be performed, the parts needed, and craft or contractor support requirements. Eliminating the craftspersons time in planning efforts and concentrating that time on completing planned work is where the intrinsic value of the planner is realized. A basic of maintenance management is that planners plan and supervisors supervise.

There are appropriate circumstances for the maintenance supervisor and the craftsperson to be engaged in planning issues. The maintenance supervisor and craftsperson should be planning reactive emergency work. This work cannot wait to be processed through the normal planning cycle to be addressed. The planner should not be tasked to address this type of work because it is not in the future, it is now.

How to plan work
The actual job of planning begins with selecting a job from the planning backlog and validating the requested work:

• Is the work request clear on what is to be done or is more information needed?
• Is the priority coding for the work request correct?
• Is the equipment properly identified?

If any of these are in error, the planner should make the correction before proceeding. The planner also should examine the equipment maintenance archives for same or similar jobs and print out the previously used job plan if one exists.

The next step is job scoping and estimating. Work cannot be entirely planned from behind a desk. The planner must visit the job site and further validate the requested work. The planner evaluates each request independently. Using a facility-developed scoping and estimating check sheet, the planner determines if:

• The requested work is what really needs to be accomplished.
• Pre-work can be accomplished to expedite the repairs and minimize the equipment downtime.
• The work impacts other equipment. The planner looks for opportunities to accomplish conjunctive maintenance to other equipment.
• There is interference to be removed to make the repairs.
• Repair parts are needed to accomplish the work. An accurate and complete bill of materials for all critical equipment is necessary for the planner to efficiently plan.
• Craftspersons, contractors, or vendors need to be involved in the work, and how long the job should take for each craft, contractor, or vendor involved.
• Permits will be required to accomplish the work.

To continue the job scoping and estimating the planner should:

• Take pictures (digital cameras are a wonderful planning tool) and draw sketches.
• Consult with maintenance craftspersons, maintenance engineers, operators, and anyone else who can contribute to the job plan.
• Map the major steps of the job: shutdown, isolate, remove, repair, replace, test, and restore to service.
• Evaluate previously used job plans for applicability in the current situation. If it fits, reuse the job plan. If it does not fit in its entirety, look for opportunities to leverage reusable information.

Set up the job plan
Next comes the detail job plan development. The purpose of the job plan is to provide all of the information that the craftsperson needs to accomplish the job safely and efficiently. Every job package should consist of enough information and identified materials to enable maintenance craftspersons to complete the job without having to spend additional time searching for information or material.

A packet should be provided for each job with the following information, included as needed, to carry out the assigned tasks:

• Copy of all purchase orders for material
• Bill of materials list for equipment
• Copy of the work order
• Drawings required
• Job scope/estimating sheet
• List of stores stock parts
• Feedback and history information
• Special tools required
• Permits required
• Equipment location directions or sketch
• Safety procedures
• Special instructions on equipment
• Lock-out tag-out procedures
• Equipment inspection sheets
• Job procedures (detail tasks)
• Alignment cards if required

The amount of detail that goes into a job plan is largely dependent upon the qualifications of the maintenance team. If the team is composed of highly skilled, equipment knowledgeable individuals, then little detail is necessary. However, if the team contains a mix of skills and equipment knowledge or the facility plans to hire maintenance novices, then more detailed job plans are desirable. Well-written maintenance plans are an excellent training tool. Consider this the new standard job plan for this work activity.

Now that the job plan has been developed, the work order moves from the planning backlog to the ready-to-schedule backlog. Coordination between the maintenance planner, the production supervisor, and the maintenance supervisor is required to select the most appropriate opportunity to execute the job plan. The planner plays an essential role in bringing together the mutually agreeable equipment availability and maintenance resource availability. At this point, the job plan is turned over to the maintenance supervisor for implementation, which is the subject of the next article in this series.

It is recommended that each facility undertake a critical examination of its planning organization. Identify shortfalls and take the steps necessary to realize the intrinsic value of maintenance planning. A facility's bottom line will be improved by this effort and maintenance craftspersons will thank you.

Previous articles in this series include "Be Brilliant with the Basics" (MT 3/00, p 41), "Know What It Is You Have To Maintain" (MT 5/00, p 33), and "Identifying and Approving Work" (MT 7/00, p 27). Future articles will cover work hand-off, quality and safety, and information capture. MT

John Rasberry is an associate with Performance Consulting Associates, Inc., 3700 Crestwood Parkway, Suite 100, Duluth, GA 30096; (770) 717-2737.

Robert C. Baldwin, CMRP, Editor

That conversation will focus on the goals of the enterprise and how they are to be met. Reliability and maintenance leaders will have an opportunity to respond and possibly sell some best practice concepts that previously fell on deaf ears.

What I have picked up from various conversations with speakers, exhibitors, and attendees at recent conferences (Society for Maintenance & Reliability Professionals and Noria's Practicing Oil Analysis) and a recent press briefing by Rockwell Automation, is that top management may be ready to listen.

The C-level (CEO, CFO, CIO, etc.) has invested heavily in enterprise level information systems to avoid the effects of Y2K and assure the enterprise has a solid infrastructure on which to base operations in the so-called new economy. Much of this activity has resulted in a flat or negative return on investment (ROI) because not much has happened at the bottom line.

Meanwhile, Wall Street is putting earnings performance under the microscope. Projections must be met or exceeded. Companies are responding by changing their behavior. They are more focused on the bottom line. They are embracing the elimination of waste through lean manufacturing, searching for best practices to assure operational excellence, and freeing up capital by eliminating excess inventory. The term "predictable capacity" is heard.

Return on net assets (RONA) fed by overall equipment effectiveness (OEE) is the primary metric of this new business era. Reliability and maintenance leadership that has done its homework and developed an implementation plan for processes and technology to improve RONA may find an eager ear at the C-level. (If you need a refresher on how reliability and maintenance performance connects to RONA and the bottom line, check out the article links in the box on the first page of our website at www.mt-online.com.)

The C-level will be looking for some quick wins. And reliability and maintenance is in a position to provide them. The installation of best practices can reduce substantially the indirect cost of manufacturing, and that's what C-level people want to hear.

You better be ready because it many not be hot air that's blowing through that open window of opportunity. MT

For as long as I can recall, there have been varying degrees of confusion about what people mean when they use terminology that involves the word "failure."

Failure is an unpleasant word, and we often use substitute words such as anomaly, defect, discrepancy, irregularity, etc., because they tend to sound less threatening or less severe.

The spectrum of interpretations for failure runs from negligible glitch to catastrophy. Might I suggest that the meaning is really quite simple:

Failure is the inability of a piece of equipment, a system, or a plant to meet its expected performance.

This expectation is always spelled out in a specification in our engineering world, and, when properly written, leaves no doubt as to exactly where the limits of satisfactory performance reside. So, failure is the inability to meet specifications. Simple enough, I believe, to avoid much of the initial confusion.

Additionally, there are several important and frequently used phrases that include the word failure: failure symptom, failure mode, failure cause, and failure effect.

Failure symptom: This is a telltale indicator that alerts us (usually the operator) to the fact that a failure is about to exist. Our senses or instruments are the primary source of such indication. Failure symptoms may or may not tell us exactly where the pending failure is located or how close to the full failure condition we might be. In many cases, there is no failure symptom (or warning) at all. Once the failure has occurred, any indication of its presence is no longer a symptom—we now observe its effect.

Failure mode: This is a brief description of what is wrong. It is extremely important for us to understand this simple definition because, in the maintenance world, it is the failure mode that we try to prevent, or, failing that, what we have to physically fix.

There are hundreds of simple words that we use to develop appropriate failure mode descriptions: jammed, worn, frayed, cracked, bent, nicked, leaks, clogged, sheared, scored, ruptured, eroded, shorted, split, open, torn, and so forth. The main confusion here is clearly distinguishing between failure mode and failure cause—and understanding that failure mode is what we need to prevent or fix.

Failure cause: This is a brief word description of why it went wrong. Failure cause is often very difficult to fully diagnose or hypothesize. If we wish to attempt a permanent prevention of the failure mode, we usually need to understand its cause (thus the term, root cause failure analysis). Even though we may know the cause, we may not be able to totally prevent the failure mode—or it may cost too much to pursue such a path.

As a simple illustration, a gate valve jams "closed" (failure mode), but why did this happen? Let's say that this valve sits in a very humid outside environment—so "humidity-induced corrosion" is the failure cause. We could opt to replace the valve with a high-grade stainless steel model that would resist (perhaps stop) the corrosion (a design fix), or, from a maintenance point of view, we could periodically lubricate and operate the valve to mitigate the corrosive effect, but there is nothing we can do to eliminate the natural humid environment. Thus, PM tasks cannot fix the cause—they can address only the mode. This is an important distinction to make, and many people do not clearly understand this distinction.

Failure effect: Finally, we briefly describe the consequence of the failure mode should it occur. To be complete, this is usually done at three levels of assembly—local, system, and plant. In describing the effect in this fashion, we clearly see the buildup of the consequences. With our jammed gate valve, the local effect at the valve is "stops all flow." At the system level, "no fluid passes on to the next step in the process," and finally, at the plant level, "product production ceases (downtime) until the valve can be restored to operation."

Thus, without a clear understanding of failure terminology, reliability analyses not only become confusing, but also can lead to decisions that are incorrect. MT

Anthony M. "Mac" Smith, San Jose, CA, is a pioneer in the application of Reliability-Centered Maintenance (RCM) to complex plants and facilities. Mac has 47 years of engineering experience, the past 18 of which focused on RCM program installation. He is recognized internationally for his book Reliability-Centered Maintenance.

Wall Street values a company's stock based upon the company's ability to predict production and earnings. Consistently low estimates are just as bad as overestimates. Persistent production reliability problems can have a direct impact on a company's market share and revenues. Good, reliable production demonstrates control. The question that investors ask is: "Does management have control of the business?".

Investors will put their faith (and their money) into companies that demonstrate the best control. Meeting production targets is a very important part of demonstrating this control. Highly reliable plants consistently meet production goals, which gives the perception that the plant is well run. Reliability problems can erode this perception. The need for reliable operations can be summed up in one word: Predictability. Predictability is one of the most sought after, yet rarely achieved, aspects of modern business. While better predictability is the goal, it is not clear how to achieve it.

New decision-making schemes must accompany advances in information technology. Risk, reliability, projections, and experience must be brought together to understand current business needs and future functions. Investment in technology must be used to satisfy those needs. These new processes often require a paradigm shift in order to be successful. This paradigm shift necessitates that we implement new processes and modify or eliminate old processes.

How do we get people to accept, comprehend, and use statistical techniques applied to computerized maintenance management systems (CMMS) data? Some will tell you, "Ah, that data is just garbage!" Others will say, "I just don't have the time to get to it." Still others contend that "even if I had the time, I dont know what data to use in order to understand reliability."

Resistance to change is quite often the largest barrier to successful implementation of new technologies and procedures. People resist change and tend to trust familiar practices more than new ones.

Reliability analysis
Reliability analysis is a business practice that will make your business more competitive. The goal of analyzing installed assets is to uncover the reasons, symptoms, causes, and effects of equipment unreliability to get a handle on unexpected equipment failures.

An effective reliability program rests on one fundamental principle: future probability of failure can be accurately predicted using previous failure data. If the decision-makers in the company do not accept this concept, there is virtually no probability of success for the program. Success can range from solving a few problems to the tracking of reliability of all major assets and allowing reliability results to influence the "repair-overhaul-replace" decisions that are made on a daily basis. This is not to imply that this should be the only criterion used to make these decisions, but that reliability analysis can be used to modify this approach to improve reliability.

Some companies track failure data separately, simply to report on reliability. In some industries, regulatory agencies require failure tracking and some even require adherence to limits on failure rates of assets installed in their facilities. This kind of regulatory requirement ensures that reliability problems get addressed as a regular part of doing business.

CMMS were not necessarily designed to capture and report reliability data. These systems were optimized to manage, organize, and plan complex maintenance schedules. Because these systems were not originally intended for reliability tracking purposes, some people argue that reliability analysis on this data is invalid. While this is true in some cases, many plants have excellent record keeping in their CMMS, and analysis conducted on this data can be very helpful.

Data integrity is a key issue in using CMMS data for reliability analysis. The analysts need to know the data collection practices used to gather the CMMS data. Is the data submitted in a consistent fashion or is each work order subject to a high level of variability? Variability in data capturing is the enemy of good reliability analysis.

What data is needed?
Some of the basic assumptions of reliability theory are that equipment "times to failure" can be modeled with statistical analysis techniques. The first step in this modeling is to create a set of data based upon failure records for the equipment under study. Some CMMS capture the failure data needed to conduct the reliability analysis. Work orders often contain a vast amount of information, including:

Asset or equipment ID

Asset type

Manufacturer

Model number

Event type (PM, repair, etc.)

Description of work

Out of service date or failure date

Maintainable item or failed part

These data fields are used to extract failures against individual assets, manufacturers, or asset types. This is important when trying to model failures from the same cause (Weibull) or different causes (growth). Once we have created the set of data that describes the failures, statistical tools are applied to reveal additional information about the nature and cause of failure, the expected current reliability of equipment, the future reliability of the equipment if we solve the current problem, prediction of future failure time if no action is taken, and the evolution of a failure.

CMMS offer many ways to collect data about maintenance activities. In many systems, there are often areas for cost data, spare parts, and other fields to capture comments and descriptions. There are often many date fields that describe when work is scheduled to start, actually started, scheduled to be completed, and actually completed. When using CMMS data to perform failure analysis, care must be taken to use the proper data. In order to understand what data is available, definitions of each field need to be understood by the analyst.

When a piece of equipment fails in service, a sequence of events occurs. The same sequence happens, in most cases, independent of the CMMS used; listed chronologically, it goes like this:

The item fails

Someone notices that the item has failed

Someone contacts maintenance or enters a work request into the CMMS

The item is scheduled to be repaired

The repairs are conducted

The item is tested and made available for service

The item is returned to service.

While there are variations on this process, this list describes, in a generic sense, how the failed item is recognized and repaired. The CMMS entry noted is the first interaction by a worker with the CMMS. This may or may not coincide with the actual date/time of the failure. Reliability analysts need to keep this in mind when extracting data for use by the CMMS. Analysts often assume that the delay between when the item has failed and when it is reported to the system is short compared with the life of the equipment. For most analyses, this is a good assumption, especially for critical equipment. Sometimes more accurate failure estimates can be extracted from process data or operations logs.

Reliability analysis of the data
What constitutes a reliability analysis? There are many different ways to conduct a reliability analysis. Each method provides a slightly different answer that needs to be interpreted differently. For analyzing reliability data, we suggest the following five steps:

Step 1. Determine the goal of the reliability analysis.

Step 2. Extract the necessary data from the history brief view using a query.

Step 3. If a growth model is desired, build a query of the data that identifies the population of equipment that you want to model.

Step 4. Build the necessary reliability documents to satisfy the goal of the reliability analysis.

Step 5. Interpret the results and implement a corrective action if possible.

The goal of the reliability analysis
Each reliability analysis should have a goal. The goal helps to decide which tools to use. Unfortunately, sometimes analysts will use the wrong tool for the goal they wish to achieve. Two types of reliability modeling techniques are popular in industry today: Distribution analysis (Weibull, normal lognormal, and exponential distributions) and growth modeling.

In some cases, both a Weibull analysis and a growth model need to be constructed to get a complete picture of what is going on.

Weibull analysis
Weibull is by far the most popular approach for failure data analysis since the probability density function adapts itself to the population. A Weibull analysis provides information that can help an analyst to understand if the assets are experiencing end-of-life failures, infant mortality failures, or simply random failures with no discernable pattern. Weibull analysis results also can be used to estimate the time until a certain level of unreliability has been reached.

Growth modeling
In trying to understand the overall reliability of a set of equipment failure data, a popular technique called reliability growth (also called AMSSA Growth, Duane-AMSSAA or AMSSA-Crow) is often used. Growth is valid for all failure causes and can be set up to include assets that have not experienced failures. It is the ideal tool for understanding the overall reliability of equipment.

The growth model produces two parameters: beta and lambda. A beta value greater than 1 shows improving mean time between failure (MTBF). When beta is less than 1, MTBF is decreasing and reliability is deteriorating. These values of beta and lambda also can be applied to a formula which can be used to calculate time to next failure. These estimates have proven to be very accurate when the data is complete and failure data is accurate.

Accuracy of reliability data
Reliability programs use historical data to predict the future. When doing this, plant personnel are immediately faced with questions about the accuracy of the data being used to make the predictions. This accuracy is always of concern whenever future business decisions need to be based on historical datais the data accurate? Two features of reliability analysis help here.

The first is that the analysis itself can be used to sort out inaccurate data. Poor Weibull curve fit results point to inaccurate or "dirty" data. Mixed mode data can be sorted out through the visual inspection of the curve fit. Finally, significantly changing MTBF, detected through growth analysis, gives additional clues to a lack of data integrity.

The second feature of reliability analysis that helps overcome data inaccuracies is that the most important piece of information used for the reliability analysis is the failure date and time. This data for the most part is often quite accurate because it requires no interpretation by the user and, in many systems, is captured automatically.

Case history
During a routine inspection of maintenance costs data, a reliability specialist had come across a rather disturbing result. A Pareto chart of pump costs by location ID showed a particularly alarming result.

The graph, built with Meridium software, showed that maintenance costs for the pump at location Pump-1000 were over $300,000 in 1998. This result triggered an investigation by the reliability personnel. The first step in the investigation was to understand the cause for such high costs for this asset in this location. Another data query was constructed to extract the total maintenance costs for the entire period for which data exists, since 1990. The total maintenance costs over the 9-year period was $445,891.

Upon examining the results of the work order history query, the company found that $329,800 was associated with one event, a single work order conducted on January 19, 1998. The client investigated this work order further to understand the cause. This work order query revealed that 68 work orders had been written against this location over the 9-year period from January 1, 1990 to December 31, 1998. Out of the 68 work orders, 57 were described as "routine repairs" indicating that the asset had been experiencing a high failure rate in addition to the high costs. The work order history query was refined to extract only the routine repairs. A Weibull analysis then was conducted on the data set.

The reliability analysis that was conducted showed a rather low MTBF of 60 days. Typical values of MTBF for this type of asset (centrifugal pump) normally exceed 700 days in practice and 1458 days, according to reliability database. This analysis resulted in a Weibull parameter beta of 0.84, which indicates an infant mortality failure mode.

Since infant mortality is not an expected failure mode for this type of machinery, we can attribute these failures to a procedural deficiency rather than to a design deficiency. Further investigation revealed that the cause of failure was an inadequate lubrication program for this machine. This analysis was critical in bringing attention to this occurrence so that mitigating tasks can be put into place to prevent recurrence of this type of failure.

The reliability analysis bears out the results of the investigation as a procedural problem for this pump. The Weibull results, while not used in this case to solve the problem, provide additional information that further defines and illustrates the severity of the problem. This case shows that procedural problems can be very costly and disruptive to an organization. Identifying and eliminating these types of problems through regular analysis can lead to marked improvements in efficiency and cost performance.

The data contained within the CMMS can be used to describe reliability problems with machinery. Using statistical reliability analysis techniques, managers can identify the general area that causes the problem. The results of the reliability analysis can be compared with the results of analyses done on other equipment from the same site, analyses on like equipment from other sites, and industry data.

In order to manage the reliability of the equipment, you need to measure the reliability of the equipment. A good source of data for this analysis can be the CMMS, if the data can be manipulated to provide useful results. By conducting these types of analysis on problem areas, the organization can take appropriate corrective measures before the next failure can occur, costly in-service failure and unexpected downtime. This means better predictability for the plant, better performance for the company, and higher stock prices for investors. MT

Bob Matusheski is senior consultant at Meridium, Inc., supplier of enterprise reliability management software, Roanoke, VA; (540) 344-9205

Most companies spend a lot of money training their maintenance personnel to troubleshoot hydraulic systems. If the focus were on preventing system failure, less time and money would be needed for troubleshooting.

We often accept hydraulic system failure as normal and use resources preparing for failure rather than deciding not to accept hydraulic failure as the norm and strive to eliminate it. When I worked for Kendall Co. in the 1980s, we changed our focus from reactive to proactive maintenance and practically eliminated unscheduled hydraulic failure.

Lack of maintenance of hydraulic systems is the leading cause of component and system failure, yet most maintenance personnel dont understand proper maintenance techniques of a hydraulic system. The basic foundation to perform proper maintenance on a hydraulic system has two areas of concern. The first area is preventive maintenance which is key to the success of any maintenance program whether in hydraulics or any equipment for which we need reliability. The second area is corrective maintenance, which in many cases can cause additional hydraulic component failure when it is not performed to standard.

Preventive maintenance
Preventive maintenance (PM) of a hydraulic system is basic and simple and, if followed properly, can eliminate most hydraulic component failure. PM is a discipline and must be followed as such in order to obtain results. We must view a PM program as performance oriented rather than activity oriented. Many organizations have good PM procedures, but do not require maintenance personnel to follow them or hold the personnel accountable for the proper execution of these procedures. In order to develop an effective preventive maintenance program for your system, you must follow these steps:

First, identify the system operating condition: Does the system operate 24 hours a day, 7 days a week? Does the system operate at maximum flow and pressure 70 percent or better during operation? Is the system located in a dirty or hot environment?

Second, what requirements does the equipment manufacturer state for preventive maintenance on the hydraulic system?

Third, what requirements and operating parameters does the component manufacturer state concerning the hydraulic fluid ISO particulate?

Fourth, what requirements and operating parameters does the filter company state concerning its filters ability to meet this requirement?

Fifth, what equipment history is available to verify the above procedures for the hydraulic system?

As in all PM programs, we must write procedures required for each PM task. These steps or procedures must be accurate and understandable by all maintenance personnel from entry level to master.

PM procedures must be part of the PM job plan that includes tools or special equipment required to perform the task, parts or material required to perform the procedure with store room number, safety precautions for this procedure, and environmental concerns or potential hazards.

Preventive maintenance tasks for a hydraulic system could include the following:

• Change the return or pressure hydraulic filter
• Obtain a hydraulic fluid sample
• Filter hydraulic fluid
• Check hydraulic actuators
• Clean the inside of a hydraulic reservoir
• Clean the outside of a hydraulic reservoir
• Check and record hydraulic pressures
• Check and record pump flow
• Check hydraulic hoses, tubing, and fittings
• Check and record voltage reading to proportional or servo valves
• Check and record vacuum on the suction side of the pump
• Check and record amperage on the main pump motor
• Check machine cycle time and record.

Preventive maintenance is the core support that a hydraulic system must have in order to maximize component and life and reduce system failure. PM procedures that are written properly and followed properly will allow equipment to operate to its full potential and life cycle. The process allows a maintenance department to control a hydraulic system rather than the system controlling the maintenance department. We exercise control by deciding when we will perform maintenance and how much money we will spend. The alternative is breakdown maintenance at a much higher cost.

Hydraulic knowledge
People say knowledge is power. This is also true in hydraulic maintenance. Many maintenance organizations do not know what knowledge and skills their maintenance personnel should possess. I believe hydraulic skills fall into two groups.

One includes the skills of the hydraulic troubleshooter, who must be the organizations expert in maintenance. In general, no more than 10 percent of your work force should be in the troubleshooter category. The remainder are general hydraulic maintenance personnel, who provide the preventive maintenance expertise. This ratio is based on a company developing a true preventive or proactive approach to maintaining its hydraulic systems. Typical skills for each group are outlined in the accompanying section "Hydraulic Technician Skill Sets."

Measuring success
In any program we must track success in order to have support from management and maintenance personnel. We also must understand that any action will have a reaction, negative or possible. We know successful maintenance programs will provide success but we must have a checks and balances system to ensure we are on track.

In order to measure success of a hydraulic maintenance program we must have a way of tracking success but first we need to establish a benchmark. A benchmark is a method by which we will establish certain key measurement tools that will tell you the current status of your hydraulic system and then tell you if you are succeeding in your maintenance program.

Before you begin the implementation of your new hydraulic maintenance program it would be helpful to identify and track the following information:

• Downtime (in minutes) on the hydraulic system. Record daily and answer the following questions.
  • What component failed?
  • Cause of failure?
  • Was the problem resolved?
  • Could this failure have been prevented?

• Cost associated with the downtime. Record the following daily.
  • Parts and material cost
  • Labor cost
  • Production downtime cost
  • Any other cost that can be associated with a hydraulic system failure.

• Hydraulic system fluid analysis results. Track the following from samples taken monthly.
  • Copper content
  • Silicon content
  • Water content
  • Iron content
  • ISO particulate count
  • Fluid condition (viscosity, additives, and oxidation).

When the tracking process begins, you need to trend the information that can be trended. This allows management the ability to identify trends that can lead to positive or negative consequences.

A computerized maintenance management system can track and trend most of this information accurately for you.

Root cause failure analysis
As in any proactive maintenance organization you must perform root cause failure analysis in order to eliminate future component failures. Most maintenance problems or failures will repeat themselves unless someone identifies what caused the failure and proactively eliminates it. A preferred method is to inspect and analyze all component failures. Identify the following: Component name and model number, location of component at the time of failure, sequence or activity the system was operating at when the failure occurred, what caused the failure, and how the failure will be prevented from happening again.

Failures are not caused by an unknown factor such as "bad luck" or "it just happened" or "the manufacturer made a bad part." We have found most failures can be analyzed and action taken to prevent their reoccurrence. Establishing teams to review each failure can produce major payback quickly.

Maintenance of a hydraulic system is the first line of defense to prevent component failure and thus improve equipment reliability. As spoken about earlier, discipline is the key to the success of any proactive maintenance program. MT

Ricky Smith is president of Technical Training Div., Life Cycle Engineering, Inc., 4360 Corporate Rd., Suite 100, North Charleston, SC 29405; (843) 744-7110

As many asset-intensive companies have increasingly searched for a competitive advantage, maintenance and reliability of assets have evolved as major contributors. Organizations are being challenged to improve efficiency and work with less. Various processes, such as reliability-centered maintenance (RCM), have been implemented throughout the years as part of improvement initiatives with varying degrees of success. Many of these initiatives result in some progress toward enhanced reliability of assets, but, to achieve world-class performance, a fundamental shift in the mindset of workers and the nature of work is needed. A holistic and evergreen approach to asset management processes provides the capability to change the nature of work and drive a reliability-centered culture.

The model presented here integrates "best" processes to create a world-class approach to asset management. It is illustrated in the accompanying diagram, which is divided into separate processes and sub-processes and shows the high-level flow between each. Criticality ranking, front-end failure analysis, equipment reliability strategy development, equipment reliability strategy implementation, work management, reliability analysis, and external processes comprise the model.

Elements of the model
The Asset Management Best Process Model provides the elements necessary to support a world-class asset management program. Many organizations have done a reasonable job at defining and executing standard business processes for work management. This is most often driven by a computerized maintenance management system (CMMS). The majority of new processes implemented by world-class performers have been proactive, reliability-focused processes and post-execution reliability analysis. Some organizations may find improvement by focusing on traditional work management, but to see quantum and long-term improvements, companies must implement these other processes.

A reliability-centered model for asset management seeks to better understand assets before failure, put in place proactive equipment reliability strategies to cost-effectively eliminate the likelihood and consequence of failures, and move toward an environment where the only equipment failures will be pre-determined and due to wear-out.

The Criticality Ranking Process is used to better understand and identify assets that are truly critical to the business. This process is essential to a cost-effective approach to implementing the model.

This provides the basis for focusing personnel and other resources on the equipment that has the most direct impact on the business. For instance, as a company prepares to roll out its RCM process or any other improvement initiative, this process guides the organization to that area of the facility where it should focus its efforts, along with the specific assets within that area that deserve the most attention.

Equipment identified as "critical" then enters into the Front-End Failure Analysis (FEFA) process. The FEFA process includes traditional RCM elements including identifying functional definitions for equipment (or groups of "like-kind" equipment), functional failures, failure modes and causes, and the expected functional life. The FEFA process is not dependent on equipment history, although comprehensive performance history and analyst experience will allow for better analysis and results.

Equipment Reliability Strategy Development is the natural extension of the Front-End Failure Analysis process. Equipment Reliability Strategies (e.g., one-time tasks, preventive maintenance (PM), predictive maintenance (PdM), etc.) then are developed for "critical" equipment and focus on the detection, mitigation, and/or elimination of the expected failure modes. The strategy's intent is to ensure the equipment continues to perform its intended functions for the expected functional life, within its current operating context.

Existing PM/PdM tasks, original equipment manufacturer (OEM) maintenance recommendations, and regulatory constraints will provide the basis for the strategies, but they often are improved based on a better understanding of the equipment gained through the analysis. For "non-critical" equipment, "template" equipment reliability strategies can be developed that provide a base strategy for optimal performance (most often defined by equipment type).

A key element of this model, which is often overlooked, is the Equipment Reliability Strategy Implementation process. A considerable amount of work is required to perform the front-end analysis and to develop equipment reliability strategies. Depending on the scope of assets involved and how well technology is leveraged, there also can be a sizable amount of work involved with implementation of the strategies' tasks. Once a strategy's tasks have been determined, the best implementation approach must be selected.

For instance, if the strategy calls for a recurring type of condition or process monitoring, a decision must be made whether it can be automated or not, whether it could or should be performed as part of an operator's round, or whether it should be part of a PM or other mode of implementation. There also will be opportunities to bundle tasks with consistent scheduling intervals so they can be handled more efficiently as one work effort.

The Work Management process in this model is extremely critical. Many organizations have focused on work management excellence, but in a "reactive" environment. The philosophy in a "reactive" environment is to "fix it when it breaks." This philosophy usually rewards personnel for making quick repairs at the sake of preserving evidence, understanding the cause, and updating the strategy to prevent the occurrence of that failure in the future. Elements of a traditional maintenance organization such as high percentage of reactive work, constant breaking of the schedule, little if any root cause investigation, minimal amounts of PM/PdM tasks, etc., are undeviating and perpetual. The prospect for breaking this "reactive" cycle is poor until an integrated process, focusing on proactive work, is established.

There is and always will be a place for fast and efficient repairs. However, the work management process in this model places the focus on other elements. Better work order prioritization methods based on criticality can be deployed. Proper analysis of the situation using nonintrusive condition monitoring can eliminate or delay unnecessary work. Inventory and spare parts can be forecast better through the understanding of equipment criticality. Forward-looking schedules can be planned and met. More PM/PdM tasks will be performed replacing "reactive" work. Better equipment history can be documented, providing valuable information necessary for failure and reliability analysis.

The Reliability Analysis process utilizes observed equipment behavior and compares it against the expected failure effects and modes identified as part of the FEFA, thus creating a continual or "evergreen" improvement process. This results in "evergreen" reliability strategies that are continually customized to ensure optimal performance for equipment.

The ultimate result of the "evergreen" process is to move toward an equipment-specific reliability strategy for each equipment item based on its actual performance. It is not likely that anyone would ever get to that point nor would it necessarily be prudent or cost effective, but the process provides a path to continually evaluate the actual observed conditions and create the optimal equipment reliability strategy for each asset.

This process enables the equipment reliability strategies to continually move away from a theoretical model to a realistic one based on actual performance. In other words, equipment covered by a template or equipment-group strategy will utilize the template strategy tasks as long as they are providing optimal performance. As observations are recorded, whether good performance, failures, degradation, or any other relevant information, the process provides a path to further customize the template or equipment-group based tasks to the individual equipment they are supporting, migrating from template to equipment-group to equipment-specific reliability strategies.

There are various types of reliability analyses that can be utilized. The "evergreen" process most often is triggered by a failure or other event. However, another aspect is to perform continual "ad hoc" reliability analyses. These can include the basic types of reporting such as Pareto or worst actor charts. As observed history becomes more accessible and accurate, advanced statistical modeling, such as distribution and trend analysis, can be used.

The Asset Management Best Process Model also identifies a number of important External Processes. These processes can (and many do) operate regardless of the status of this model. Each is considered important to the reliability of assets. The more integration with the external supporting processes, the better the overall enterprise asset management program.

Throughout the life of a facility, there are various Environmental/ Operational Factors that impact the Asset Management Best Process Model. The model must be flexible to respond to these factors, which include changes to business strategy, production targets, feedstock/raw material, regulatory compliance, etc. The entire model, its processes, and resulting data should be evaluated for validity upon the introduction of these factors.

For example, it is not uncommon for petroleum refiners to change their crude slate over time. In most cases, the plant was built originally to refine a "sweet" crude. If they make a decision to start using "sour" crude (indicates changing chemical composition of the crude), this has an effect on the type and frequency of deterioration expected by the equipment. With that in mind, equipment reliability strategies should be reviewed and optimized based on the expected impact of the different factors.

Implementation
The model provides the vision and the processes required to support a leading-edge asset management program based on our experiences in various asset-dependent industries and organizations. It is crucial that the implementation of this model be based on the individual needs of each organization. Each organization must evaluate how to best leverage the processes indicated in the model to meet its own strategies, goals, and objectives for asset management.

Implementation of this model also must take into account the effort required to optimize value as quickly as possible. The model, as represented, indicates a continual process, which over the long term can provide significant benefits. To see a quicker realization of benefits, implementation of certain prerequisites is necessary. These prerequisites include a short-term focus on work management basics and initial performance of the proactive elements of the model (e.g. criticality ranking, front-end failure analysis, and equipment reliability strategy development and implementation). Without the proactive elements in place for "critical" equipment, the value of the "evergreen" process is diminished.

Critical factors for successful implementation of this model include:

• Progressive vision for excellence
• Long-term commitment
• Short- and long-term objectives and goals (Key Performance Indicators)
• Build up basics while extending the model
• Leadership
• Communication
• Training
• Ownership and empowerment throughout the organization
• Technology

Benefits of the model
Significant cultural changes, cost savings, and increases in mechanical availability can be achieved by the implementation of the Asset Management Best Process Model. Short- and long-term benefits can be expected. Adoption of this model will provide the following representative benefits:

• Common vision for world-class asset management
• An excellence model to train all personnel involved with asset management
• Breakdown of departmental barriers and elimination of conflicting priorities traditionally found in organizations with a "reactive" culture
• Migration from "reactive" to "proactive and planned" reliability-centered work and culture
• Avoidance of significant events due to preventive tasks and predictive monitoring
• Increased mechanical availability/ decreased lost production opportunities
• Decreased maintenance and production costs
• Identified areas of focus for reliability improvement

Enhanced reliability of assets is a critical element in the survival of today's organizations. This recognition has brought forward the question of how to improve maintenance and reliability of assets while simultaneously freezing or trimming the maintenance budget. There are many sound methods and technologies that individually can provide significant incremental cost savings.

However, to reach quantum and long-term improvement, a change in mind-set and work is required. The reality is that this is a journey, not a destination, and unfortunately, there is no "holy grail" which will work for everyone. World-class performers are continuously pushing the envelope. Therefore, all organizations must continuously search for long-term improvement opportunities. Organizations that adopt a holistic and evergreen model such as the one presented here will set the marks for asset management excellence as we move into the 21st century.

Future articles will deal with the processes presented in this model, their interactions, and the controls an organization must provide to facilitate progress. It is our opinion that the key to world-class performance is to select and integrate the best practices available and adapt them to each organization's needs. MT

Darrell Ferguson is a senior consultant and services delivery manager within the Asset Management Consulting Group at Plumlee Associates, Inc., 2638 S. Sherwood Forest Blvd., Suite 200, Baton Rouge, LA 70816; (225) 292-4464

There are several good training companies that can do a good job of explaining why training is essential for a professional thermographer. Therefore, this article will address infrared inspection methods: what to test, when to test (scheduling), equipment prioritization, additional factors, and data collection methods. The last section will show reports and the analysis that can be derived when standard data collection methods are followed.

What to test and when?
The first question, What to test?, is answered by using or creating an equipment inventory as the cornerstone for infrared inspection accountability. The equipment inventory can be recorded on paper during the inspection and then transcribed into a spreadsheet or database. It can be printed from an existing computerized maintenance management system (CMMS), or it can be entered into an infrared database program while the inspection is being performed. Without an inventory, the thermographer cannot account for what was tested and what was not. A piece of equipment can go for years without being tested if no inspection record is kept. A company hiring a thermographer should receive an inventory report of equipment tested and not tested. It costs very little to build the inventory, and the benefits far outweigh the costs in the long run.

By recording the test status of each piece of equipment in the inventory list during the inspection, the thermographer can answer the question, What did you inspect? To provide full accountability, test status information should include the following points:

• Current test status
  
• Date the equipment was last tested
  
• Results of the previous test
  
• Reason equipment was not tested during the last inspection (if it was not)
  
• When equipment is due to be tested again, if not tested this time.

An example notation currently used in the field for test status of equipment is as follows:

TBT: To be tested. Starting test status for all equipment.
TESTED: Tested.
NTNL: Not tested, no load. Commonly seen, because not all equipment can have a load during the inspection
NTTC: Not tested, time constraint. Scheduled to be tested but time ran out
NTNS: Not tested, not specified. Not scheduled to be inspected this time
NTUR: Not tested, under repair.

Once an inventory has been created, it is advisable to assign a criticality to the operations value of each piece of equipment. This procedure helps prioritize equipment for testing schedules and repair priority when a problem is found.

The following list can serve as a basis for developing a site-specific equipment criticality-to-operations list and the corresponding inspection frequency set for each.

• Crucial criticality: Inspect every 3 mo
  
• Essential criticality: Inspect every 6 mo
  
• Nonessential criticality: Inspect once a year
  
• Followup on problems or repair: Inspect every 3 mo

Once an inventory has been set up and inspection test statuses have been integrated, the infrared program has accountability. When the criticality to operation criteria have been added, a prioritized inspection schedule and repair list is ready. Bar-code labels on the equipment can be helpful in streamlining equipment inventory management. Without a basic equipment inventory, there is no accountability, no prioritized inspection scheduling, and no reliable infrared program.

What pertinent data should be recorded?
Once an inventory has been set up and the equipment to test has been determined, the next questions are, Besides recording the temperature of the problem and the reference, what other information is pertinent and should be recorded? Other than the emissivity value that the camera stores, what factors could greatly influence temperature measurements?

One factor is the equipment load; whenever possible it is important to measure and record load data. As Bernard Lyon stated in a paper presented at Thermosense XXII, "Temperature is certainly an important factor in evaluating equipment. However, if you follow the guidelines that are based solely on absolute temperature measurement, or on a temperature rise (DT), you run the risk of incorrectly diagnosing your problems. The consequences of such actions can lead to a false sense of security, equipment failure, fire, and even the possibility of personal injury."

Another factor that should be recorded is wind speed. As shown in the wind effects experiment done by Robert Madding and Bernard Lyon and stated in their paper presented at Thermosense XXII, "The temperature rise was cut in half with just a little over 3 mph breeze." The options available include buying a $100 anemometer to try to accurately measure wind speed or picking up grass, dropping it, and estimating wind speed. Either way, in most cases, the wind speed will have to be an estimate because even an anemometer will be some distance from the equipment being inspected. This condition is especially true regarding power lines. The important point is to account for wind speed by the best available means and record it. This information is especially crucial if baseline trending is being done on a problem.

Another notable factor is environment. Was it a hot sunny day, rainy, snowing, or clear but freezing? Environmental factors such as solar loading or a cold rain can affect temperature measurements. Again, this information is especially crucial if baseline trending is being done on a piece of equipment located outdoors. What was the weather like the last time the inspection was done? How does this information correlate to the temperatures measured?

Equipment load, wind speed, and environment are not the only factors that are important to note when a problem is documented. Other information that is less important to the thermographer but may be more important to management is the manufacturer and type of fault for each problem found. This information allows reliability to be analyzed by manufacturer or equipment type. By comparing the cost of repairing observed problems, a maintenance manager can look at the impact by manufacturer on the total operating expense of a facility. This information, in turn, can be used to improve future buying decisions.

Data collection techniques
The infrared camera is just a tool, and the thermogram is just the starting point in the data gathering process. The next step is to establish methods to ensure efficient, accurate data collection. These methods should have built-in procedures to guarantee that data quality is consistent from inspection to inspection and from thermographer to thermographer. These methods must not impair the pace of the inspection but should help in expediting the collection of data and aid the thermographer in his ability to diagnose problem conditions in the field.

For many years, the simplest and cheapest way to record data has been manually on paper. If this method is used, preparing preprinted problem write-up sheets with blank data fields will increase consistency and standardize problem write-ups. When used with an inventory list produced by a spreadsheet program or a CMMS, the write-up sheet is the starting point of a standardized infrared inspection system. This method of manual data collection works if labor costs are relatively inexpensive. Another method that has been used for many years is recording problem write-ups with a voice dictation recorder.

Although these methods are convenient, there are pitfalls to using either method. In both instances, there is the risk of losing data and introducing errors from misinterpreting field notes when typing up the reports at the office. Furthermore, the thermographer in the field does not have in his hand the analysis of past problems and other information when it would be of most value to him.

With the advancement of pen computers and database software, a third method of data collection has evolved. Instead of trying to bring field data back to the office and enter it into a database on the computer, the technician brings the computer into the field to enter the data directly into the database during the inspection. This advancement has proved to be the most reliable method of data collection available today, as well as the most cost-effective solution over time.

One efficiency of the mobile database is the instant turnaround time of report generation. Because all of the necessary information is put into the database at the time of the inspection, the reports can be printed immediately at the end of the inspection. Using a pen computer with an infrared database in the field, a thermographer can double the number of problems written up in a day (from 50 to 100) and completely eliminate report generation time.

The following comparison of paper or voice dictation method to pen computer with IR database method lists typical inspection and report generation times. Report generation includes inventory of equipment and associated test statuses, prioritized list of problems, and documentation.

Paper or voice dictation method

• 50 problems per 8-hr day
  
• Report generation takes 6 hr
  
• Total: 50 problems in 14 hr

Pen computer with IR database

• 100 problems per 8-hr day
  
• Report generation automatic
  
• Total: 100 problems in 8 hr

Another efficiency of a database on a mobile pen computer is its ability to yield more consistent inspection results because testing procedures can be methodically followed. Key information can be selected from drop-down menus. Past problem conditions on a chronic problem are immediately displayed and can be reviewed in the context of the new problem. Furthermore, the redundancy of data collection can be eliminated because information that was stored in the past, such as location, does not need to be re-entered into the database. Maps, work orders, inspection procedures, and other pertinent documents can be brought into the field because the database also can work as an electronic document management system.

Now that the inspection has been completed and the data have been collected, what analyses can be formed from following these methods? The software to ensure write-up consistency is extremely efficient; it eliminates typing and syntax problems while improving data accuracy. This method has many benefits over conventional methods because data are entered only once.

Management reports and analysis
The analysis outlined in "Problem Profile Report: Key Equipment Failure Ratios," is from data collected for more than 10 years using the Thermal Trend Infrared PdM Inspection Management Database. Actual client and manufacturer names and specific products have been omitted to protect the clients and manufacturers. Data were collected from all over the world on many manufacturers' equipment and in all kinds of plant environments. The data included in this analysis come from hundreds of thousands of problems and pieces of equipment.

Tracking problems and categorizing them by their temperature rise reveals trends in facilities' health over time. Average temperature rise using all of the electrical problems documented in the database for electrical inspections as measured phase to phase is 54 deg F.

Problems in the database can be analyzed and ratios can be established for specific faults on key equipment by recording manufacturer and type of failure. This strategy leads to the ability to study the equipment thoroughly and analyze what factors play an important role in their failure, for example corrosion, overloading, or just a substandard piece of equipment. This analysis provides insight into the correct preventive maintenance measures to be taken so future problems will be minimized.

A cost breakeven report can be generated from materials and labor by recording equipment and labor costs before vs. after using an infrared inspection program. For example, 976 problems were documented at 55 industrial manufacturing sites. A cost-benefit analysis on the 976 problems shows a before vs. after failure savings on materials and labor of $408,040. The average cost saving per problem, if it is fixed before it fails works out to $418.07 for material and labor . This figure is very conservative and does not take into consideration the potential loss to revenue or to production, or the risk of financial loss from a major fire.

Analyzing cost savings reveals measurable results from implementing an infrared inspection program. On average, for every $1 spent on hiring a competent professional consultant to perform an infrared electrical inspection, there is a $4 return on investment for materials and labor to fix the problem equipment identified before it failed. This conservative 1:4 ratio clearly identifies the importance of maximizing the return on investment of implementing a comprehensive in-house or outsourced infrared inspection program. Furthermore, because of reduced losses and increased productivity, which in turn increase revenue, the return on investment ratio in some cases is closer to 1:20, depending on the industry.

Whether a thermographer uses a pad of paper or a pen computer, the data and methods followed are important to creating a standardized infrared inspection management program. Sufficient training and field experience cannot be emphasized enough as a basis to build a solid infrared program. Once components are in place, it is important to implement strong data collecting methods to get standardized results across multiple inspections and multiple thermographers. By recording appropriate supplementary information such as load, wind speed, and environment in addition to the thermographic image, a thermographer can better assess the severity of the situation.

By setting up a standardized infrared inspection program, tracking the pertinent information, and recording it consistently, a plant can manage and see the trends in the overall health of the facility. There is a wealth of information to gain by using these methods in a comprehensive infrared inspection management program. MT

Scott Cawlfield is president of Logos Computer Solutions, Inc., 3801 14^th Ave. West, Seattle, WA 98119; (206) 217-0577.

Robert C. Baldwin, CMRP, Editor

One of the more impressive parts of the tour of the Dofasco site in Hamilton, ON, was its electrical repair shop, a 25,000 sq ft facility where approximately 2500 motors and generators, plus 450 electrical breakers, are serviced each year. The operation, which is QS9000 certified and employs a staff of 42 people, has an annual budget of $5 million.

Realizing that equipment reliability was vital to improving product quality, production output, costs, and shareholder return, Dofasco managers initiated a strategic project in the early 1990s to research, develop, and implement the most advanced maintenance practices and information technologies to achieve maximum equipment reliability (the process is outlined in the article "Achieving Maximum Equipment Reliability" on page 28).

The motor repair shop is recognized as a core competency in the Dofasco asset management strategy. It produces an estimated repair work cost saving of $1.5 million per year and directly affects equipment reliability in the mill.

The shop emphasizes comprehensive record keeping. A new system now being rolled out will use a bar coding system driven by handheld data loggers to obtain real time motor data during the repair process. The system contains nameplate data, performance data, test and repair records, and reliability information on motors that affect manufacturing equipment reliability. Such information is a prerequisite for making informed business decisions about motor management.

Yes, most plants don't have the wherewithal to invest in motor management anywhere near the scope of the Dofasco program. But that is no excuse for not managing electric motors to provide reliable and energy efficient systems. The motor data to begin a program can be downloaded for free over the Internet. The article "Electric Motor Energy and Reliability Analysis" on page 17 provides the details.

If there is a valid excuse for not managing electric motors, I don't know what it is. It certainly isn't the expense of obtaining motor reliability and performance data. MT

Robert M. Williamson, Strategic Work Systems, Inc.

TPM Key Element 1: Improving equipment effectiveness by targeting the major losses. TPM activities should focus on results. One of the fundamental measures used in TPM is Overall Equipment Effectiveness (OEE) which includes the major losses that TPM seeks to eliminate. OEE = Equipment Availability x Performance Efficiency x Rate of Quality.

TPM Key Element 2: Involving operators in daily maintenance of their equipment. Operator involvement must be defined in ways that make sense in your work culture. There are tasks that operators can do without using any tools: Clean and inspect equipment. In every company that I have studied or visited or worked for, the thing that they get the most return on investment in the early stages of TPM is operators learning how to inspect their equipment and pay attention to key things. It doesn't take any tools or special skills; you just have to know what to look for. Maintenance people can teach the operators what to look and listen for.

TPM Key Element 3: Improving maintenance efficiency and effectiveness. This means improving all aspects of maintenance including spare parts, computerized maintenance management system, preventive maintenance, predictive maintenance, maintenance tools, work order system, planned and scheduled maintenance, and equipment histories. These are all part of TPM. They can't be separate or on the side. They must be woven in. For example, production, maintenance, purchasing, and shipping and receiving should use a computerized maintenance management system. It's not just a maintenance management system anymore; it's an equipment information management system.

TPM Key Element 4: Training to improve the skills of everyone involved. This means maintenance training, operations training, leadership training, training about root cause analysis of the major losses, reliability training, etc. The training should first address the very basic needs of the people and the equipment targeted for TPM. One of the most important basic training needs for TPM is designed to help the people involved understand what TPM is and why it is so important for the equipment and the business.

TPM Key Element 5: Life-cycle equipment management and maintenance prevention design. If you're going to design and develop new equipment or a major modification, involve those who are going to operate it and maintain it for the next 5, 10, or 15 years in the process. Use their ideas to make it easier to operate and easier to maintain.

Based on the past ten years' experience with TPM in America, a sixth key element is needed to truly recognize what is making TPM work. It is:

TPM Key Element 6: Wining with teamwork focused on common goals. Even with all of the emphasis on high-performing equipment the best equipment cannot consistently perform well without teamwork focused on common goals using common processes. In some facilities "Team" is a four-letter word that is often misunderstood. In TPM the sense of teamwork centers around the targeted equipment, then expands through all areas using TPM to improve their performance.

One of the biggest misunderstandings about the pillars of TPM deal with the first pillar–Improving Equipment Effectiveness by Targeting the Major Losses—and its relationship to the other pillars. All TPM activities, including the remaining pillars, are designed and developed to be measured by the first pillar. If a TPM activity does not result in, or contribute to, improved equipment effectiveness then we need to ask "Why are we doing it?"

Energy efficiency in electric motor systems presents significant opportunities within industry. In a 1998 U.S. Department of Energy (DOE) report provided by Xenergy, Burlington, MA, "In 1994, electric motor-driven systems used in industrial processes consumed 679 billion kWh23 percent of all electricity sold in the United States& . Implementation of all well-established motor system energy efficiency measures and practices that meet reasonable investment criteria will yield annual energy savings of 75-122 billion kWh, with a value of $3.6-$5.8 billion& ."

A number of organizations, including electric motor service centers, equipment manufacturers, and utilities, have been developing electric motor system maintenance and management programs since 1993. The concepts, in general, have been to include both energy and condition analysis to provide electric motor users with reliable and energy efficient motor systems. The planned result has been to provide a win-win solution for end-users to improve costs and cost avoidance, reduce power demands on utilities, and expand service capabilities for service companies.

In recognition of these efforts, and to support new efforts within industry, the DOE, the Electric Power Research Institute (EPRI), utilities, trade associations, and others have funded and supported a variety of informative materials, support lines, and software tools. The DOE Office of Industrial Technologies' Best Practices program offers a wide variety of information, tools, and support to assist industrial plants in identifying opportunities for energy efficiency in common systems such as compressed air, motor, steam and pumping systems; and in evaluating opportunities for application of new technologies.

The focus of this article is to outline the development of a motor maintenance and management program using the DOE's MotorMaster+ (MM+) free software and simple tools available within industry. We also shall discuss an industry-funded modification to MM+ designed to allow for a reliability assessment of electric motors combined with an economic analysis. The new version of MM+, which includes the recent changes for reliability assessment, is presently in use within industry on a number of projects implemented through companies and utilities such as Pacific Gas and Electric (PG&E); Dreisilker Electric Motors, Inc.; Nicor Gas; Fermi Lab; BJM Corp.; Pruftechnik, Inc.; and others. The new version of MM+ also is available to anyone for download at the OIT, Best Practices website.

Developing the program
The purpose of an energy and reliability program for electric motor systems is to decrease the cost of energy, production, and maintenance overheads associated with the production of a product—in effect, reducing the cost per production unit as effectively as possible. According to a PG&E application note, "Motor maintenance is more than making sure the motor itself is operating correctly. It also involves ensuring that power supplied to the motor is within acceptable tolerances, that the motor's output power is efficiently transmitted to the load, and that the load itself is properly maintained so as not to make the motor work harder than necessary."

The key components of a motor maintenance and management program include:

• Control of the electric motor system inventory in software
• Pre-made repair versus replace and retrofit decisions
• Predictive and preventive maintenance program implementation with a continuous improvement component
• Top management commitment
• An in-house energy coordinator
• Employee buy-in
• Pre-set energy conservation goals
• Partnerships between vendors and owners implemented with pre-planned decisions and shared information.

Such a program can result in improvements of 10-15 percent or more. These opportunities result from such simple improvements as replacing failed electric motors with energy efficient or premium efficient electric motors; scheduling proper greasing of electric motor bearings, reducing electric motor system friction losses; correcting impedance unbalance in motor windings and electrical systems; correcting belt tension and alignment; properly sizing electric motors to the load; testing questionable equipment before and after repair; and other measures that can be immediately implemented or implementation planned for outages. These examples and other related benefits can have energy, reliability, waste stream, and production financial impacts that more than justify the combined energy and reliability effort.

Reliability
In all dynamic systems, the chance that the system will operate as designed decreases over time. Electric motors are made up of a number of dynamic systems in which each has a reliability function that decreases as the motor ages. The purpose of a reliability-based motor program is to optimize the costs of operating the electric motor and equipment. Measuring the reliability of electric motor systems by quantifying the costs associated with unreliability places the reliability portion of the motor management program in the arena of business impact.

The reliability of the system, as defined within this article, is the measure of the chance that the equipment will operate over a period of time. One of the keys to understanding reliability is knowing the mean time between failures (MTBF). For instance, if an electric motor has a failure rate of 1 in 40,000 hours, the MTBF would be 40,000 hours. The failure rate for that motor would be 1/MTBF, or 0.000025 (identified as l).

Knowing the failure rate, the information can be applied to the reliability function

(R = e^-tl)

Therefore, the chance that the motor system will operate for 50,000 hours would be: R= e(50,000)(0.000025) = 0.287, or 28.7 percent. In a redundant (parallel) system, the overall system reliability increases. The result of a single parallel system is

R = R_a + R_b  (R_a)(R_b).

Using the previous example, the parallel system has a 49.2 percent chance of operating through 50,000 hours.

In an electric motor maintenance and management program, there are several points in which the system reliability can be influenced. These points include:

• Acceptance of new electric motors
  
• Acceptance of motor vendors
  
• Acceptance of repaired electric motors
  
• Acceptance of motor repair centers
  
• Tracking and correction of minor defects during the life cycle of the system (predictive and preventive maintenance, root cause analysis, reliability based maintenance, etc.).

It is important to note that the reliability of a vendor should be measured over time and not based upon singular visits and measurements. In particular, a series of specifications should be provided and the vendor measured against that specification over time.

The reliability costs of a motor system can be calculated. A motor fails twice per 50,000 hr, it takes 6 hr to repair the system upon each failure, the system operates 8760 hr/yr, production costs are $10,000/hr and maintenance costs are $100/hr (energy, motor repair or replacement, and waste costs not considered).

Should a maintenance and reliability program (for this one system of many) reduce the failures by half, the impact would be a cost of $58,300 over 50,000 hr, a reduction of $62,760 (52 percent).

Energy
There are two basic energy costs that must be observed in an energy and reliability program: life cycle or annual energy costs, and energy costs due to motor condition. In the first instance, the annual operating costs are based upon motor load, energy usage and demand charges, operating hours, and motor size and efficiency. When viewing energy costs due to condition, the increased losses due to phase unbalances or increased friction and windage (bearing failure, for instance) are taken into account.

Equation 1. Energy demand

kW usage = percent load x 0.746 x (horsepower/efficiency)

Equation 2. Energy demand between electric motors

kW = 0.746 x hp x percent L x (100/lower eff.  100/higher eff.)

When considering the previous (reliability) example as an 1800 rpm, 50 hp electric motor, 75 percent loaded, 92 percent efficient, operating 8760 hr/yr, the operating demand would be 30.4 kW. The annual usage would be 266,304 kWh. If the energy charges are an average of $14/kW demand and 0.06 cent/kWh usage, the associated costs would be (30.4 kW x $14/kW x 12 months) $5,107.20 demand and $15,978.24 usage per year for an annual energy bill of $21,085.44 or $120,397.86 over the 50,000 hr life cycle (5.7 years).

If the 50 hp electric motor is compared with a new, 95 percent energy efficient electric motor with a purchase price of $2400 and installation cost of $600, the annual cost savings would be $161.32 demand and $756.86 usage per year, or $918.18 total per year. This would yield a simple payback of 3.3 years ($3000 cost + installation/$918.18 annual savings). In many cases, companies will set a two-year payback as the minimum before performing a motor retrofit (replacing a working motor with a new energy efficient motor). However, when performing an economic (lifecycle) analysis, the before-tax benefit-to-cost ratio would be 1.62 and the after-tax return on investment would be 32.6 percent, which is normally an acceptable rate for a retrofit.

Should the 50 hp electric motor fail in operation, a repair versus replace scenario may be performed. The difference between the new motor cost and the repair cost is used to determine the simple payback. In this case, the repair costs $1250, resulting in a difference of $1150. The simple payback is 1.25 years ($1,150 cost/$918.18 energy savings) with a 5.53 after-tax benefit-to-cost ratio and 212.7 percent after-tax return-on-investment. Thus the motor should be replaced versus repaired.

The preceding examples assumed that only efficiency would be the appropriate evaluation. When considering condition, these numbers begin to change drastically. For the following example, a motor circuit analysis evaluation of impedance shall be reviewed. Impedance unbalance and voltage unbalance are similar as, per Ohm's Law: Current = Voltage/Impedance, resulting in the following examples being applicable to both voltage and impedance unbalance.

The purpose of an electric motor is to convert electrical energy to mechanical torque. It operates best when all three phases of a three-phase motor are 120 electrical degrees from each other and other stator, rotor, and friction losses are controlled. As the phases vary from 120 degrees from each other, the efficiency of the electric motor decreases because it becomes harder for the magnetic fields within the stator to turn the rotor, and, when far enough off, they interfere with each other. This effect is found in both voltage and impedance unbalances, including impacts to efficiency, reliability, and production.

A 50 hp electric motor, as shown in the previous examples, with a 3.5 percent impedance unbalance, would have a resulting efficiency of 89 percent (3 percent reduction due to heating). The resulting energy costs would be $5275.20 demand and $16,503.84 annual energy usage, totaling $21,779.00 per year, an increase of $689.64 per year.

Combined energy and reliability
When considering both energy and reliability, production losses can be incorporated as part of the costs. The following information is gathered for evaluation based upon the preceding examples:

• Electric motor: 50 hp, 1800 rpm, 75 percent loaded, 8760 hr/yr, 92 percent efficient with a 3.5 percent impedance unbalance (89 percent resulting efficiency)
• Electrical costs: $14/kW demand and 0.06 cent/kWh
• Reliability: 2 failures every 50,000 hours
• Lifecycle: For the purpose of this example, the lifecycle is 50,000 hours
• Replacement motor: 50 hp, 1800 rpm, premium efficient motor (95 percent), balanced phases that will reduce the failures to 1 in 50,000 hours.

Selection of program tools
As part of each successful electric motor energy and reliability program, a series of tools and software has to be selected in order to monitor and maintain the program. Several considerations must be made when putting together an energy and reliability toolkit—initial cost, training requirements, ergonomics, accuracy, and least invasive to the process.

These concepts were incorporated in a recent PG&E study that focused on electric motor energy and condition issues only. The purpose was to assemble a "tool kit" based upon independent research into a number of datalogging, efficiency, and condition analysis tools to determine energy and condition opportunities and how they interrelate. The initial areas of study were software, dataloggers, motor circuit analysis, vibration analysis, and infrared analysis. The results were to be developed into an Electric Motor Performance Analysis Tool (PAT) that would be used as part of a market transformation strategy. The tools that resulted from this study included the DOE's MM+, the Fluke 41B, the Summit Technology PowerSight 3000 datalogger, the BJM ALL-TEST IV Pro motor circuit analyzer, and the Pruftechnik Vibrotip. Infrared analysis was determined not to play a part in the motor only analysis, but would be an effective tool in a motor system analysis.

MotorMaster+
MotorMaster+ is used as a motor management support tool for commercial and industrial sites. It is designed for auditors, industrial energy coordinators, and plant or consulting engineers to provide the most efficient and cost effective decisions for electric motor and system planning. MotorMaster+ is used to identify inefficient, undersized, and oversized electric motors, and then calculate the energy and demand savings associated with the selection of energy efficient or premium efficient replacements.

The software tool contains a hierarchy of each plant being analyzed, a field data module, a motor price and performance database on over 20,000 new motors, energy conservation analysis, life cycle analysis, energy accounting capabilities, and even an environmental conservation capability.

The field data module serves as a motor inventory and field measurement storage repository. The module houses motor nameplate information, identification, process, and location codes; load type, operating hours and working environment descriptions; and such measured data as voltage, amperage, power factor, and speed at the load point.

The user can choose from a variety of descriptor-based motor inventory sorts within the Field Data Module. Motors operating under abnormal power supply conditions also can be detected. Measured values are used to determine existing motor loads and efficiencies. Batch analyses can be conducted automatically for populations of motors, determining the costs and energy savings due to changing out all motors in a given facility or process, or only those motors with simple paybacks below a stated value.

MotorMaster+ Version 3.0 also includes the following features:

• A database of performance and price information on more than 20,000 IEC (metric) and National Electric Manufacturers Association (NEMA) Design B, C, and D three-phase motors. The motors range from 1 to 4000 hp, with speeds of 900, 1200, 1800, and 3600 rpm, and open drip-proof (ODP), totally enclosed fan-cooled (TEFC), totally enclosed nonventilated (TENV), weather-protected (WP), totally enclosed air-over (TEAO), totally enclosed blower-cooled (TEBC), and explosion-proof (EXPL) enclosures. Motors rated to operate at 200, 208, 230, 460, 575, 220/440, 796, 2000, 4000, and 6600 V are included. Full- and part-load efficiency values are measured in accordance with the IEEE 112 protocol to guarantee consistency. Manufacturers supply the information, and the database is updated annually.
• Technical data that can help optimize a drive system, such as data on motor part-load efficiency and power factor; full-load speed; locked-rotor, breakdown, and full-load torque; and idle and locked-rotor amperage.
• Purchase information, including list price, warranty period, catalog number, motor weight, and manufacturer's address.
• Analysis features that calculate the energy savings, dollar savings, simple payback, cash flows, and after-tax rate of return-on-investment from using a particular energy efficient motor in a new purchase or retrofit application. Variables such as motor efficiency, purchase price, energy costs, hours of operation, load factor, and utility rebates are taken into account.
• Utility rate schedule and motor rebate program data, including minimum qualifying efficiency and rebate dollar values.
• Energy accounting, conservation savings tracking, and greenhouse gas emissions reduction reporting capabilities.
• Menus and extensive help screens that make MM+ easy to learn and use.

MotorMaster+ Version 3.0 contains many motor energy management features. An informed MM+ user can:

• Create a list of available new motors that meet purchase specifications.
• Determine both energy and dollar savings from selecting and operating an energy efficient motor model.
• Compute annual cash flows and the after-tax rate of return on a motor systems investment.
• Create a company motor inventory database and generate searches and reports based on motor and load descriptors.
• Initiate motor repair or replacement analyses for populations of motors within a company.
• Produce energy conservation summary, facility reduction in consumption, and greenhouse gas emissions reduction reports.

MM+ modification
A modification to the existing MM+ was necessary in order to perform the condition analysis portion of the PG&E market transformation project. The modification was to allow for the ability to enter and search phase balance data in resistance, impedance and inductance, insulation resistance, and vibration analysis data in velocity and shock pulse. BJM coordinated and led the effort to implement this "first ever" industry funded modification to the MM+ software. Other industry participants included Pruftechnik; Dreisilker; Washington State University; PG&E; Boeing; General Motors; Oak Ridge National Labs; the DOE; and many others. BJM, Dreisilker, Pruftechnik, and PG&E worked together to define and promote the MM+ modification. This group coordinated with Washington State University and the DOE to implement the change. The DOE and WSU welcomed the industry recommendations and financial support for the MM+ modification. The version of MM+ that includes this recent modification is available for anyone to download.

Electrical data collection, logging
There were two basic approaches selected for data collection. One was "snapshot" data collection for basic data entry into MM+ of voltage, current, power factor, and kW. The second was datalogging of these measurements over time.

The first instrument selected was the Fluke 41B which provided the snapshot measurements required for under $2K per instrument, was portable, and simple to learn. The datalogger selected was the PowerSight 3000 which provided the datalogging capabilities, ease of use, cost under $4K each, and was already on hand to the utility and its customers. FlowcareEngineering Inc., the primary contractor for the project, developed a special tool for consolidating the electrical data and providing it in a manner that data entry into MM+ was made much simpler.

Motor circuit analysis
A number of motor circuit analyzers were studied for implementation into the project. Both on-line and off-line instruments were reviewed and a number tested. On-line tests were found to have challenges when applied in certain electrical environments, including variable frequency drive outputs, and required a great deal of training and experience.

The All-Test IV Pro was selected because it was a static (off-line) impedance-based meter, which provided the necessary measurements of resistance, impedance, and inductance unbalance for the project. It was found to be the simplest to use, the most accurate, weighs less than 2 lb, was the least intrusive of the off-line tests (less than 4 min for a complete battery of tests), and cost under $8,000.

Vibration analysis
There was a much larger variety of vibration analyzers available for review. Based upon a survey of equipment users, ease of use, portability, and best cost (less than $10,000), the Pruftechnik Vibrotip was selected as the vibration analyzer of choice. It provided the necessary measurements of velocity, carpet shock pulse, and max shock pulse that allowed for a quicker determination of bearing condition. Shock pulse was selected because this measurement type was not proprietary to the equipment.

Equipment implementation costs
As part of the implementation phase of the utility study, a number of case studies are underway. The effectiveness of both a basic (electrical data only) and advanced (energy and condition data) industrial survey, reviewing best cost of training, personnel, equipment, and results, is being reviewed. A two-day training program covering data collection, data entry, equipment use and analysis, and report writing was developed, one of the benefits of the selected tools' ease of use. Equipment costs were as follows:

• Basic analysis equipment—datalogger and snapshot instrument with MM+ was $6000
• Advanced analysis equipment—datalogger, snapshot instrument, motor circuit analyzer, and vibration analyzer was $24,000

By using a variety of tools, more than one person may be collecting a variety of data at one time. Presently, systems to automate data entry are under development.

The first site selected was a paperboard plant where a study was performed by Newcomb Anderson and Associates. Forty electric motors ranging from 15-200 hp were found to yield annual savings of $15,000 per year based upon just the basic analysis and energy savings. The simple paybacks on all motors varied from 1-5 yr, the return on investment was well over 20 percent, and the benefit-to-cost ratio was over 2:1, with 16 motors found to be oversized, 2 overloaded, and 22 inefficient. This study provided a small sample of the electric motors within the selected plant and could be used to assist in the justification of a much larger survey.

Application of energy and condition analysis
In 1999, the University of Illinois at Chicago Energy Resources Center was contracted by Dreisilker to perform a combined energy and reliability assessment at a coal-fired power plant. The primary tool used for analysis was the MM+ software tool, Version 3.0. The project was a challenge as no listing or locations of electric motors existed for the plant. The survey was limited to support motors only.

The survey identified 366 motors for evaluation with 328 in-service and 38 spare electric motors. Of the in-service electric motors, 315 were Design B, 12 were Design C, and one was Design D. The Design B motors were primarily used with fans, pumps, and air compressors; the Design C motors were used for coal conveyors; and the Design D was a hopper motor. Of particular importance was the use of Design C motors for the incline coal conveyors. This is because of the particular torque requirements for the start-up and movement of the conveyors loaded with coal. The Design C motor is excellent for this type of application because of high start-up, pull-up, and breakdown torques. If a Design B motor were to be used in place of a Design C, as was the case at the plant prior to the survey, it most likely would stall during the pull-up torque portion of the torque curve.

Because of the age of the plant, a number of other considerations for retrofitting or repair versus replace decisions had to be observed:

• As many of the larger electric motors are original frame or U-frame, base retrofits or modifications have to be considered as an additional cost.
• Shaft couplings may have to be changed out to fit newer electric motors, due to different shaft sizes.
• Heaters, fuses, starters, and wiring must be properly sized to work with appropriate electric motors.
• Possibility of variable frequency drive applications for fans, pumps, and air compressors.
• Operating speed differences between newer energy efficient and older electric motors.

Through the use of MM+, retrofit and repair versus replace decisions were analyzed from an energy standpoint. For the purposes of the study, the following information was used: Estimated energy costs, $0.025/kWh usage and $10/kW demand; a 35 percent discount factor for a particular brand of electric motors selected by the plant; and a maximum 5-year payback. As a result, 15 of the in-service electric motors were found to be excellent retrofit candidates, with a use reduction of 68,705 kWh and a demand reduction of 8.2 kW for a 37 percent after-tax return on investment and a 1.7 benefit-to-cost ratio. In addition, 51 electric motors were found to be excellent replace instead of repair candidates with a use reduction of 197,254 kWh and 23.5 kW demand ending with a 92.9 percent return on investment and a 3.2 benefit-to-cost ratio.

MotorMaster+ then was used to analyze the in-plant spare motors. Of the 38 electric motors in stock:

• When comparing the existing in-use motors to the spares, it was found that 23 of the 38 electric motors did not match any motors in the plant.
• Of the remaining electric motors, due to storage practices, not a single spare was ready for use. The majority were rusty with seized shafts and the remainder were failed motors.

Finally, a reliability, preventive, predictive, root cause analysis, and corrective maintenance program was recommended. The MM+ database and capabilities were implemented as part of the program. It was determined that program implementation, including equipment costs, would have an initial 3 month simple payback and a 0.5 month annual cost payback due to reduction in failures, downtime, and corrective action costs.

Conclusion
A combined energy and reliability program, using MM+ and selected logging and analysis tools, will have a tremendous payback in energy and industrial assessment programs. With the latest improvement within MM+, electric motors found in poor electrical or mechanical condition can be analyzed for repair versus replace using an energy-based financial assessment. The fact that the necessary modifications were fully funded by industrial users shows that industry recognizes the potential impact of this type of analysis. The combined energy, reliability, waste stream, and production cost avoidance impact in virtually any type of industrial or commercial facility is staggering, allowing for the improved competitiveness of U.S. industry.

Presently, energy and reliability assessments are under way with commercial buildings in Chicago, a national lab in association with a motor repair center and utility, a number of industrial sites including chemical and petroleum, and as case studies for at least one utility. It is expected that overall operating costs will be improved by at least 10 percent at each of the facilities. MT

Howard W. Penrose, Ph.D., is the director of the BJM Corp. Electric Motor System Testing and R&D Division, Old Saybrook, CT (860) 399-5937. He is a past chair of the Chicago Section of the Institute of Electrical and Electronic Engineers (IEEE) and past chair of both the IEEE Dielectrics and Electrical Insulation Society and Power Electronics Society for IEEE Chicago.

Project Contributors
Howard W. Penrose, Ph.D, BJM Corp., All-Test Div.
Jim Hanna, Pacific Gas & Electric
Johnny Douglas, Washington State University
Chris Cockrull, U.S. Department of Energy
Greg Lee, Pruftechnik, Inc.
Dave Van Horn, Dreisilker Electric Motors, Inc.

Knowing what is the right maintenance program for a company's assets is no easy task. It might seem that the longer the company has been around the more effective its maintenance program would be. Unfortunately that assumption is not always true. In fact, the effectiveness of the maintenance program has absolutely nothing to do with the number of years the company has been doing maintenance. Most companies are doing too much maintenance too early, or too little too late, either of which has cost consequences to the organization.

Most organizations are continually attempting to improve their bottom lines through improved maintenance practices. Why do only a few achieve their objectives? Unfortunately, trying to improve without the right business focus, alignment of practices, and enabling tools can make matters worse. The required information and know-how for the most part already exists in the company but is so scattered throughout the organization that inconsistency rules.

Dofasco, Inc., formulated advanced maintenance practices and combined information technology to develop a unique equipment reliability program that has made a significant impact on the company's bottom line. Canada's second largest steel manufacturer, the company produces 4.5 million tons of flat-rolled steel a year. The company has revenues of more than $3 billion and employs 7000 people in its Hamilton, ON, plant. The plant's equipment replacement value is $5 billion.

Motivation to improve
In the 1980s the steel business was good. However, in the late 80s and early 90s circumstances began to change. Globalization was beginning to influence the market, imports started arriving at lower prices and higher quality, hangover from the 1970s inflation saw costs rising and prices dropping, there was a shift from a sellers to a buyers market, and shareholder returns were beginning to erode.

Dofasco took a step back and evaluated its maintenance performance and found that 70 percent of maintenance work was reactive and only 30 percent was proactive. The rate of product quality improvement was flat, and average equipment availability was only 78 percent. At that point managers realized that equipment reliability was vital to improving product quality, production output, costs, and shareholder return. They initiated a strategic project to research, develop, and implement the most advanced maintenance practices and information technologies to achieve maximum equipment reliability.

The project
As they started the project they found four main issues that had to be addressed:

• The existing culture stressed equipment repair over asset management. They needed to adopt an equipment reliability business process.
• Many improvement efforts were ongoing in the plant, but they were inconsistent. Dofasco decided to develop a critical few fundamental business practices.
• The ongoing improvement efforts were typically short lived. They needed to develop a sound implementation methodology.
• Islands of data were not readily available to maintenance. Data systems needed to be integrated with expertise to convert the data into usable information.

The ability to come up with an innovative software system to support the first three requirements was going to make or break the initiative.

The practices
The company was in a fairly typical situation. Information was scattered throughout the organization in the form of original equipment manuals, computer databases, experience and knowledge of tradespeople, and many reports. However, none of the information was easily accessible to the people who planned the maintenance work; the result was inconsistent actions. The planners had no way to know what work they should be planning at what time.

By developing an equipment reliability business process, Dofasco believed that it would be able to identify the knowledge or information that needed to be managed. Establishing business practices would ensure consistent behavior to support the business process. A sound implementation methodology would allow planners to extract the required knowledge and make it easily accessible to everyone, resulting in consistent action or the ability to do "the right work at the right time." And finally, an enabling information infrastructure would help turn the data into usable information.

The equipment reliability business process they developed revolves around quality issues. The processes that made up the overall equipment reliability business process were quality planning, quality improvement, quality control, and quality assessment.

The next step was to develop practices to support these processes. The practices involved in quality planning were designed to ensure that personnel understood business unit goals and how assets would contribute to these goals. By understanding this they could now target equipment reliability efforts on the assets that contribute to business unit goals.

Quality improvement practices were designed to ensure they were identifying the proper maintenance program for their assets. Work identification is fundamental to equipment reliability because if the proper work is not identified, other practices are irrelevant.

Quality control practices address the efficiency of the maintenance department. Again, without proper work identification the quality control process does not matter. Technicians will just be doing the wrong work more efficiently.

Quality assessment practices assess the work that has been done to determine if the work was accurately identified in the first place. They provide an opportunity to continuously improve work identification practices.

At this point the company had a process and practices to support it, but the next step was the most difficultimplementing the processes and practices. The implementation methodology involves 10 steps. An implementation step addresses each of the business processes that had been defined. The steps include reliability-centered maintenance (RCM) analysis, predictive maintenance needs assessment, criticality analysis, and hierarchy development.

The technology
Once the practices were in place the company needed a computerized system to help ensure that these new practices would be easy to follow. One of the first tasks was to define content versus computer. The business process, business practices, and implementation methodology all ensured that the content of maintenance work is effective at achieving equipment reliability. The computer system would act as an enabler in conducting the business process and business practices most efficiently.

The company already had a computerized maintenance management system (CMMS) but determined that this program could not satisfy all of its needs. A CMMS is work-order based and is really about improving maintenance efficiency. Therefore it addressed the quality control aspects of the processes (work planning, work scheduling, and work execution).

However, something was needed to help identify what work needed to be executed and the right time to do it.

After unsuccessfully searching for a commercial package that could satisfy its needs, Dofasco decided to develop its own system. The result was the Intelligent Condition Monitoring System (ICMS), which is being commercialized and marketed by Ivara Corp. under the name Ivara.EXP (Expert Maintenance Program). This software supports the quality planning and quality improvement processes that were in place. It helps manage the effectiveness of maintenance operations and complements the existing CMMS.

The ICMS software collects the islands of data and analyses the information by using expert systems technology. It predicts potential problems and triggers an alarm to pinpoint the specific problem. Once it has identified the problem, it recommends the corrective action needed to prevent equipment failure.

The ICMS system collects a variety of information, such as visual inspection results, operator observations, vibration characteristics, process parameters, lubricant test results, electrical diagnostics, and thermographic images and trends. The data are collected electronically where possible by integrating to predictive maintenance devices and data historians. In other situations the system uploads to handheld data loggers to allow people to conduct accurate and efficient inspections.

The ICMS system then analyses the data using defined rules and triggers alarms as necessary. The planners can then use the information provided and review graphs showing trends on the asset. They send out a work request that triggers a work order in the CMMS. The work is then planned and scheduled for tradespeople to execute.

The key concepts that the system addresses:

• It consolidates and leverages maintenance and operations data and makes the information usable
• It captures plant expertise in a comprehensive equipment maintenance program (EMP) that includes preventive, predictive, and corrective activities
• It provides immediate visibility of problems that can be traced back to the data that triggered the alarm
• It integrates with the CMMS so that planners do not have to duplicate efforts in two systems.

Everything starts with the EMP. Planners identify the preventive, predictive, and corrective activities that need to be performed on an asset. They set up inspection templates, preventive maintenance routines, and standard jobs to make setup easier. The computer captures all relevant information for an asset, including what activities to perform and how often and when they were last performed.

The EMP also allows planners to set up equipment condition indicators. These indicators can come from metered or predictive technology readings such as temperature, mileage, pressure, and vibration as well as from visual inspections, and allow them to capture consistent information such as clogged, cracked, or normal. Once planners have specified the condition indicators to track on an asset, they can set up the rules that will trigger alarms and the recommended actions to take when alarms are triggered. The rules can include calculations such as engineering computations as well as failure modes, which combine multiple indicators.

Dofasco does use reliability-centered maintenance, so they devised the system to provide full support for RCM methodology linked directly to the EMP. This arrangement allows planners to see if the task they are performing is based on their RCM analysis.

Data are collected in a variety of ways. For example, operator checksheet data used to be kept on clipboards near the equipment and was rarely used by maintenance. Now operators help monitor equipment condition by entering their checksheet data into the computer system.

Planners also collect inspection data from tradespeople and technical staff. Before the new system was instituted, a person would be given a work order that said "Inspect Boiler 3." The inspector would then enter comments on the work order such as "OK." Planners could not do anything with this information.

Now inspections are defined with equipment condition indicators. The inspector gets a paper checksheet, or downloads the checksheet to a portable datalogger that has a predefined list of choices. This strategy ensures that inspectors collect uniform data that can be used to analyze equipment condition. The inspector also gets immediate feedback on any alarms that are triggered while he is entering data. Thus he can ensure that he is entering valid data, or he can fix the problem immediately if possible.

Condition indicator values also are extracted from predictive technologies such as thermographic peak and vibration resonance. Other condition indicator values are collected from plant floor data collectors such as data historians, programmable controllers, and distributed control systems. All of these methods are used to collect the right data at the right time to ensure that equipment is performing as expected.

Then the data can be used to make informed maintenance decisions following rules defined in the EMP. These rules trigger alarms and recommend corrective actions when equipment is performing outside of desired operating parameters. Nonnormal equipment status is readily visible to maintenance personnel. They can then examine and analyze trends in the condition data. If necessary, corrective actions can then be taken to return the equipment to its desired operating state.

The results
Dofasco used these innovative practices and technologies to completely change the way its maintenance departments operate and saved millions of dollars. They now do 75 percent or more proactive work. Equipment availability increased more than 10 percent and product quality yield rose from 76 to 91 percent. The maintenance workforce has declined, through voluntary attrition, from 3678 to 1734. The parts inventory was reduced from $110 million to $70 million with a goal to get to $50 million by 2001.

At the recent 11th Annual Canadian Maintenance Management Congress in Toronto, Dofasco walked away with two prestigious awards. The first was for Best Maintained Large Plant/Facility and the second for Best Use of Technology/Maintenance Innovation of the Year.

In March 1999 Dofasco joined with Ivara Corp., a leading developer of enterprise asset management solutions, to bring this innovative technology to market. MT

David Liptrot is marketing manager at Ivara Corp., Burlington, ON; telephone 905-632-8000 ext. 249. Gino Palarchio is equipment reliability manager at Dofasco Inc., Hamilton, ON

The rush to reliability, fueled by rising global competition, high fixed costs, capital intensity, and the pressure for greater on-stream performance, is providing the planning and scheduling function with an opportunity to add further value to its business objectives. The maintenance planner might better be described as asset reliability coordinator.

Across the landscape of industrial plant maintenance, the asset performance picture is not all that good. Consider the following:

• Thirty percent of newly overhauled machines fail on startup
  
• An estimated one-third of the money spent on preventive maintenance is wasted
  
• Sixty percent of premature bearing failures are due to improper fitting, maintenance, and handling
  
• Maintenance and operation account for 70 percent of the money spent on pumps.

To rise above these shortcomings, plants have redundant systems and spared equipment to assure process availability. The average refinery runs at nearly 95 percent average availability, but studies have shown that downtime affects the bottom line by smaller profit margins, decreased yield and quality, reduced safety, additional environmental incidents, and missed delivery dates.

Additionally, plants have had to spend scarce capital to build more capacity to meet the fluctuations in their demand patterns and compensate for process unreliability.

Use of maintenance craft resources is even more alarming: average craft productivity, measured through "wrench time" studies, is typically in the 25 to 35 percent range. Productive work is held up by time spent waiting for materials, tools, instructions, and clearance and time spent traveling to the job.

Inefficiencies in craft utilization, many of which are beyond the individual craftperson's control, contribute to additional expense for outside contractors, rush charges for materials not planned to be on hand, excessive overtime, and work that had been identified but was not performed in a timely manner.

Perhaps the greatest cost for these inefficiencies is lost production resulting from process interruptions from unreliable equipment. Some examples illustrate the magnitude of benefits that flow from improved asset reliability:

• If an average size refinery were to increase its availability from 92 to 96 percent, with a $3/barrel margin, it would generate an additional $6 million/year.
  
• For an electric utility with a 1000 MW steam system, each 1 percent availability improvement might be worth over $300,000/yr in power transaction capability.
  
• Each 100 Btu/kWh improvement in efficiency might be worth over $400,000/yr.
  
• A 1 percent sustainable improvement in availability for a 1000 MW system means 10 MW of future power plant that does not have to be built. When construction prices are $1200/kW, which is worth $12 million in capital expenditures.

One of the best weapons for fighting these deficiencies in maintenance performance is the competent planning and scheduling of maintenance activities.

The benefits of good planning

The benefits of good planning fall into several major categories:

1. Productivity. Planning affects productivity most in the reduction of delays. Implementing a fundamental planning and scheduling system should help improve productivity to about 45 percent. Then, as files become developed to prevent recurrence of problems of past jobs, productivity should increase to 50 percent. Finally, a good enterprise asset management (EAM) system should boost productivity to more than 55 percent. This increase in productivity alone, from 35 percent to 55 percent, boosts a 90 person maintenance workforce to the equivalent of 141 people.
2. Quality. Having the work scope, instructions, parts, tools, and crafts all correctly identified and ready before the job starts has a direct positive effect on quality. Quality is indirectly affected by the boost in productivity because the freed-up workforce can spend more time on difficult jobs and proactive work.
3. Shift to proactive work. Proactive work includes root cause failure analyses on repair jobs and corrective maintenance to fix small problems before they get out of hand. It also includes project work to improve less reliable equipment and increased attention to preventive and predictive maintenance. Greater productivity creates, in effect, greater resources. In a company with much reactive work, these additional resources are used to put out fires. A company with reactive work under control can leverage the additional resources to do more proactive maintenance work, dealing efficiently with situations and preventing fires. World-class companies with preventive maintenance well in hand invest those resources in training to further increase labor skills and in projects to improve equipment or other work processes.
4. Increased availability. When more time is spent in proactive and preventive work, process interruptions become less frequent and less severe. With more time to plan ahead and anticipate equipment needs, planners can develop a more closely integrated schedule that accommodates both production and maintenance needs. A collateral effect is the reduction in on-hand maintenance, repair, and operating (MRO) inventories and total spending on spares.
5. Improved efficiency. Almost by definition, better-running equipment and processes provide improved quality in terms of both final product and conversion of raw materials into finished products.
6. Deferred capital investment. When the availability of existing equipment is increased, the need for additional new capacity can be postponed. Or in situations with relatively stable demand, the number of productive assets can simply be reduced. Either situation can have a considerable financial benefit to the company and its shareholders.
7. Reduced unit costs. When all of the potential benefits are consolidated, per-unit costs are reduced, providing a sustainable competitive advantage for the already efficient producer and a potential lifeline for the substandard producer. Thus, as process efficiencies level off, or as additional gains are no longer cost effective, asset performance and reliability become central to profitability. One of the key drivers for additional reliability is the ability to integrate production and maintenance activities into a single, comprehensive plan that maximizes output at lowest possible costs.

At this point, the asset reliability coordinator assumes a pivotal role.

Asset reliability coordinator
Traditionally, the maintenance planner has been selected for personal knowledge of the technical side of maintenance (the whos and whats of equipment care), rather than the management side (the whys and whens). There is a need for personnel who understand the value of objective data on equipment condition, reasons for failure, and the protection of the economic value created by asset reliability.

Following are summary descriptions of the responsibilities of the recast asset reliability coordinator, using new tools and techniques to focus on asset reliability and availability, by making the crews not only more productive, but "smarter" by arming them with increased knowledge:

Job planner role
Central to the coordinator's ability to add value is his or her primary work product: highly focused work packages that contain not only a listing of which craft skills are required for what periods of time, and the likely parts to be used, but more supporting documentation, for example:

• The location of the MRO parts that have been kitted or delivered to the jobsite
  
• Digital photographs of the asset and work area
  
• Safety procedures, including lockout-tagout requirements, zero-energy requirements, process safety requirements, confined entry permit forms, and environmental concerns
  
• Original manufacturer and internal documentation of wiring, layouts, dimensions, and tolerances
  
• A full bill of materials, with stores catalog numbers, in the event unanticipated damage is found
  
• Special equipment and tools that may be required
  
• A history of the most recent condition readings and work performed on the asset (repairs and replacements, preventive maintenance checks, predictive maintenance findings, instrumentation readings, operator logbook entries, etc.)
  
• Results of the coordinator's jobsite visit and comments on the work to be done
  
• A feedback form to record "found, fix, and fault" information by the crew.

The level of documentation should be commensurate with the requirements of the work. Routine repetitive work should require relatively little documentation, probably nothing more than a standard job template, which exists in a library of such plans.

Work scheduler role
The second primary work product of the coordinator is the work schedule, actually a series of interlocking schedules with progressively more detail as the anticipated work time draws closer. In industries such as petrochemicals, with major turnarounds and long lead times, a long planning and scheduling horizon is critical to success.

The schedules are a joint product of operations, maintenance, and engineering and reflect all of the work to be accomplished. The coordinator generally chairs the scheduling meetings and comes prepared with a standard schedule incorporating production requirements (and windows of opportunity that normally arise), the condition of operating equipment and potential liabilities, and the manpower that will be available for the upcoming time period. Best practices call for detailed scheduling at least a week ahead, with less stringent requirements for the upcoming two weeks. Each functional group will have reviewed the work-order backlog to ensure that critical work has been identified, planned, and made ready for scheduling.

Analyst role
A longer-range and potentially more critical function of the coordinator is to develop the ability to forecast future maintenance requirements. Today's EAM systems allow for a three-way view of asset performance: historical, looking backward to determine the most common root failure causes; real-time condition monitoring (typically through the plant's distributed control systems); and forward, analyzing each asset's mean time between failure and forecasting when the asset is most likely to affect the production process again. Failure information is critical to these views, and the coordinator must be zealous in gathering and recording that information.

The coordinator is also the database administrator for the records maintained in the EAM equipment history and condition files and the person in charge of the open backlog. This second function is extremely important in providing life-cycle management of all work requests and work orders. Timely and accurate knowledge of the current status of all open work orders allows maintenance and operations to take advantage of unforeseen opportunities and maximize the use of unscheduled downtime.

Facilitator role
A key trait for success is the coordinator's ability to influence the actions of others. In most organizations, the planner, now coordinator, has no staff, no organizational authority, and no budget. But he or she is charged with coordinating the activities of a diverse group whose short-term goals may or may not be in alignment. Facilitation skills and a clear vision of the longer-term objectives will serve the coordinator, and his organization, well. Such skills can be learned and will improve with repeated practice.

Communicator role
Finally, the coordinator must be able to clearly communicate the desired direction he or she is recommending, in terms that are relevant to the audience, whether it is operations (more throughput), maintenance (fewer breakdowns), or management (financial impact). Again, such skills can be learned.

Technology support
None of the higher-level functional requirements of the coordinator can be achieved without enabling technologies. At a minimum, the support systems must include the following:

• A modern EAM system capable of capturing and analyzing both static and dynamic information on equipment condition and the likely time frame to the next critical production interruption.The system must contain critical equipment information, including performance parameters, bills of material, and component-level tracking, and be fully integrated with the human resources and financial systems. Additionally, the system, or allied systems, must be able to display, manage, and distribute documents and perform higher-level analytical functions on data in the system. The coordinator must be trained to easily navigate the complexities of these systems and to interpret the details and convert them into usable information.
• Man-machine interface software connected to the EAM that monitors equipment parameters and downloads the information directly. Using previously established set points, the EAM system may generate a predictive or corrective maintenance work order before a costly and disruptive process interruption occurs.
• A decision-support system that integrates the information from multiple systems and promotes data-based decisions. The information model developed by the Machinery Information Management Open System Alliance (MIMOSA) provides an excellent definition of how an integrated system would function.
• Standards-based, distributed-component architecture that facilitates the adoption of enhancements as they become available. Considerable efforts have been devoted to removing the "islands of information" situations in which plants with multiple systems find themselves.

Best business practices
No functional area exists in a vacuum. The relationships among various functions are described by business rules that specify roles and responsibilities, decision points, data flows, and evaluation criteria.

A starting point is the description of a vision of how the company's assets will be maintained:

To ensure that the assets of the company will be reliable. This goal will be achieved by anticipating deterioration and addressing its root cause by technical means and education of company personnel. The timing at which these actions will be initiated will be set through a mature financial appreciation that takes into account the optimum time at which items can be removed from service.

The next step is to define the relationship between operations and maintenance. The elements of such a definition might include the following:

1. Production owns downtime data and meticulously records failures, being particularly careful to log the reason for downtime.
2. Production attempts limited inspections, in keeping with their technical expertise, but raising their awareness of the condition of the assets they use.
3. Production moves to a greater sense of ownership of the assets, demanding more detailed information from maintenance regarding the condition of the equipment and the service provided and required by maintenance.
4. Maintenance reviews the history of their performance, particularly focusing on breakdowns. Where could work have been anticipated?

The two groups jointly review the inspection program in the light of information raised under items 2 and 4.

Additionally, the basics of asset care must be in place and rigorously practiced every day:

• Work is identified early and jointly approved by maintenance and operations
• Work packages are developed reflecting the nature, scope, and complexity of the work to be performed
  
• Work schedules are developed in accordance with the lowest-cost combination of maintenance, operations, and asset repair and replacement elements
  
• Asset care is based on historical information of performance and current condition monitoring
  
• Rigorous attention is given to understanding, capturing, and analyzing the root causes of asset failures.

The starting point for improving maintenance planning is the interface between operations and maintenance, to identify sources of uncertainty that would adversely affect planning and scheduling and the execution of maintenance tasks. In particular, the focus needs to be on the ability of the two groups to work together to reduce the total costs of operating.

The most critical skill required for improving reliability and availability is understanding the root causes of failure. This knowledge, in turn, leads to the development of an intelligent and cost-optimized plan for asset care and the prevention of production interruptions.

The asset reliability coordinator is in a pivotal role to use information available through a combined view of historical, current, and forecast asset performance. MT

Robert Wilson is director of client assessments at Performance Consulting Associates, Duluth, GA; (770) 717-2737

Most people involved with the maintenance function, a function that is slow to accept change and innovation, have viewed all of the talk of the new economy like outsiders. It's like watching a parade through a store window. It's bright and colorful, but there's something between you and it that makes it seem less real.

There are a number of reasons for this conundrum. For all of the hype of the new visions toward management and leadership, the maintenance business is a work-based business (something that is often foreign to Internet startup companies). For all of the innovation in the field, the rise of computerized maintenance management systems and other tools, there has been little or no change in the core business that is maintenance. The role of leaders in maintenance is often the same as it was two decades ago: maintain the assets of the company to the maximum capability for the least amount of money.

As one maintenance manager put it to me, "Computers can tell you when to work on something, but in the end, turning a wrench is still turning a wrench." It's hard to argue with someone who is dead-on right—at least at a tactical level.

So what is different with the rise of the new economy? For one thing, it has accelerated companies' expectations of maintenance doing much more for much less cost. As the trickle of technology reaches maintenance departments, they are expected (as if by magic) to be able to do a great deal more with these tools. There is a perception that if personal computers are delivered, if infrared gear or handheld data collectors are provided, productivity will increase enough to offset the costs.

In reality, technology is a tool that can allow a maintenance manager to reduce costs. What drives that, however, is not the tools.

It's the leadership.

What the new economy is doing is forcing more traditional maintenance managers to alter their roles to become process managers and financial control managers. They are expected to understand their business at a tactical hands-on level, while at the same time understanding how to set a strategy for maintenance operations and drive to that strategy.

This expectation is not necessarily a bad thing, despite the grumblings of some managers who resist any or all change. Present-day leaders in maintenance have to look at the new tools they can lay hands on as only part of an overall solution. It is up to them to map out a means to implement these solutions, to leverage the tools and technology so that they can achieve the savings expected or even demanded by upper management.

From a leadership perspective, contemporary maintenance managers must have a full understanding of the processes that drive their business. They must comprehend the technology that they have, and what's available. When they view technology, the new leaders in our business must be able to see not just the tools, but the way to make the tools work. They must see not threats to their jobs or pains in their rumps, but means for them to alter their processes to make a difference in their jobs.

More important, maintenance leaders who want to be successful in bringing technology to bear against their problems must have the capability to lead and develop their people along with the processes changes and technology. They must be able to communicate what their vision looks like to the rank and file, and more important, they must know the best way to deal with resistance to change.

We've all seen new technology tools fail because they were implemented poorly. But the new economy demands change, constant change. Being able to wrap one's hands around the new tools, and to find ways to implement those new tools and change the supporting processes, is critical.

Robert C. Baldwin, CMRP, Editor

While attending the International Maintenance Conference (IMC) last month in Nashville, I had time to rethink my stand and see the flip side of my gearhead prejudice. Conference speakers and attendees explored the pros and cons of various tactical solutions to maintenance problems. A number of presentations focused on gear, with the thought that understanding technology will increase options for the strategist.

Like most of my conference presentations, my talk at IMC made reference to material from The Book of Five Rings (Go Rin No Sho), a classic guide to strategy by the 16th-century samurai, Miyamoto Musashi. I pointed out that, according to Musashi, "You should not have a favorite weapon. To become over-familiar with one weapon is as much a fault as not knowing it sufficiently well. You should not copy others, but use weapons which you can handle properly."

On the flip side, without understanding a variety of weapons, the strategy of the warrior (or the reliability and maintenance professional) can be limited severely.

There is a difference between a gearhead's compulsion to own the latest technology and what should be a reliability and maintenance strategist's compulsion to understand technology and choose the solutions that are most congruent with the organization's strategy.

Although I have urged gearheads to grow up by trading their technology fixation for a broader strategic view of reliability and maintenance strategy, I'm also now advocating the flip side—suggesting that reliability and maintenance leaders should cultivate the gearhead's thirst for information about technology. After all, if you don't keep up with technology, you're like a manager of financial assets that doesn't bother to monitor interest rates or check out various investment vehicles.

If you are being paid to fight for reliability and availability of equipment assets, you should become familiar with all the weapons in the reliability arsenal. MT

• Abrasive wear is the result of hard particles coming in contact with internal components. Such particles include dirt and a variety of wear metals. Using a filtration process can reduce abrasive wear which will, in turn, ensure that vents, breathers, and seals are working properly.
• Adhesive wear occurs when two metal surfaces come in contact, allowing particles to break away from the components. Insufficient lubrication or lubricant contamination normally causes this condition. Ensuring that the proper viscosity-grade lubricant is used can reduce adhesive wear. Reducing contamination in the oil also helps eliminate adhesive wear.
• Cavitation occurs when entrained air or gas bubbles collapse. When the collapse occurs against the surface of internal components, cracks and pits can be formed. Controlling foaming characteristics of oil with an antifoam additive can help reduce cavitation.
• Corrosive wear is caused by a chemical reaction that actually removes material from a component surface. Corrosion can be a direct result of acidic oxidation. A random electrical current also can cause corrosion. Electrical current corrosion results in welding and pitting of the wear surface. The presence of water or combustion products can promote corrosive wear.
• Cutting wear can be caused when an abrasive particle has embedded itself in a soft surface. Equipment imbalance or misalignment can contribute to cutting wear. Proper filtration and equipment maintenance are imperative to reducing cutting wear.
• Fatigue wear results when cracks develop in the component surface, allowing the generation and removal of particles. Leading causes of fatigue wear include insufficient lubrication, lubricant contamination, and component fatigue.
• Sliding wear is caused by equipment stress. Subjecting equipment to excessive speeds or loads can result in sliding wear. The excess heat in an overload situation weakens the lubricant and can result in metal-to-metal contact. When a moving part comes in contact with a stationary part, sliding wear becomes an issue. Providing proper lubrication, filtration, and equipment maintenance can reduce much of the wear that occurs inside of equipment. Potential problems can be identified with predictive maintenance techniques such as vibration, infrared thermography, and oil analysis. By monitoring the equipment's condition with oil analysis, a plant can identify various types of wear and take corrective action before failure occurs. In many cases, oil analysis can identify problems with rotating equipment even before vibration analysis detects it.
• When an oil analysis condition monitoring program is implemented, it is important to select tests that will identify abnormal wear particles in the oil. When components inside the equipment wear, debris is generated. Identifying the wear debris can establish the source of the problem. Here are some examples of laboratory tests that can help identify wear.
• Spectrometric analysis is the most commonly used technology for trending concentrations of wear metals. The main focus of this technology is to trend the accumulation of small wear metals and elemental constituents of additives, and identify possible contaminants. The results are typically reported in parts per million. This technology monitors only the smaller particles present in the oil. Any large wear-metal particles will not be detected or reported.
• Particle counting tracks all ranges of particles found in the sample. However, particle counting does not differentiate the composition of materials present. Its main focus is to identify the number of particles in the sample. The results are typically reported in certain size ranges per milliliter or per 100 milliliters of sample.
• Direct-reading ferrography monitors and trends the relative concentration of ferrous wear particles and determines a ratio of large to small ferrous particles to provide insight into the wear rate of the lubricated component. This method can be used as a tracking and trending tool, especially in systems that generate a high rate of particles.
• Analytical ferrography uses microscopic analysis to identify the composition of the material present. This technology differentiates the type of material contained within the sample and determines the wearing component from which it was generated. It is used to determine characteristics of a machine by evaluating particle type, size, concentration, distribution, and morphology. This information assists in determining the source and resolution of the problem.

Each laboratory test has limitations. A well-balanced test package will correctly identify potential problems in equipment. Many of the laboratory tests actually complement each other.

The purpose of an oil analysis program should not be to merely check the lubricant's condition. The real maintenance savings from utilizing oil analysis occur when equipment problems are detected. Break-in wear, normal wear, and abnormal wear are the three phases of wear that exist in equipment. Break-in wear occurs during the startup of a new component. It typically generates significant wear-metal debris that will be removed during the first couple of oil changes. Normal wear occurs after the break-in stage. During this stage the component becomes more stabilized. The proportion of wear metals increases with equipment usage and decreases when makeup oil is added or oil is changed. Abnormal wear occurs as a result of some form of lubricant, machinery, or maintenance problem. During this stage the wear metals increase significantly.

When oil analysis is used routinely, a baseline for each piece of equipment can be established. As the oil analysis data deviate from the established baseline, abnormal wear modes can be identified. Once abnormal wear modes have been identified, corrective action can be planned.

Implementation of an oil analysis program with analyses consistent with the goals of the program significantly reduces maintenance costs and improves plant reliability and safety. Lubricant analysis for the purpose of machinery conditioning monitoring is at its best with a significant amount of historical data. It is important to establish a baseline for each piece of equipment. Certain analytical results may change with lubricant oxidation and degradation from normal use; the major changes occur because of contamination from environmental factors and machinery wear debris. The analytical costs of a properly implemented program should be covered by the extension of the lubricant change interval. Increased reliability and availability, and the prevention of unanticipated failures and downtime are added benefits. MT

Information supplied by PdMA Corp., Tampa, FL 33610; telephone (800) 476-6463; e-mail Lana@pdma.com; Internet www.pdma.com/.

Measures of maintenance cost have contributed to the decline of more than a few reliability professionals' careers. From a 35-year career in maintenance and reliability, I have observed that tracking maintenance costs exists in one form or another, even where no other performance measures are in place. As some of you have heard me say (tongue in cheek): "Maintenance managers have always had measures of performance, usually cost and head count. Any other measures are just background noise."

Another basic observation is that if you spend enough time in a manufacturing facility with responsibility for cost and performance, cynicism tends to creep into your philosophical views.

Maintenance costs have been measured, are being measured, and will be measured in the future. The question is, How to do it properly, and how to keep it in balance with other important measures?

Historical measures of maintenance cost
Essentially every manufacturing process has a manufacturing cost sheet to accumulate the costs of manufacturing a product. These costs include variable costs, such as raw materials, utilities, and energy, as well as fixed costs, such as labor, benefits, depreciation, and overhead. Maintenance costs are usually viewed as fixed costs with components of labor, benefits, materials, contractor labor, salaries, and overhead. If no other maintenance cost measures exist, most manufacturing managers can look at manufacturing cost sheets and extract the key components of maintenance cost.

The most basic measure of maintenance cost is a sum of extracted components from a manufacturing cost sheet, and is simply total maintenance cost. This measure can vary greatly by interpretation of what is or is not included.

Perhaps the most commonly calculated form of maintenance cost is the one required annually by the Securities and Exchange Commission (SEC), the so-called 10K filing. The 10K report has specific definitions for elements of cost, most commonly maintenance, repair, and service. If every company read and interpreted the 10K guidelines the same way, there would be a reasonably consistent basis to compare total maintenance costs with the outside world. My experience suggests that there are wide variances in how 10K costs are reported.

Various organizations have attempted to compare maintenance costs using 10K data for both maintenance cost numbers and historical investment values. Although the cost values are subject to interpretation of the 10K rules, the historical investment values are, perhaps, even more questionable. One organization has tracked and published maintenance costs for an industry sector, using a measure roughly equivalent to 10K Maintenance Cost/Historical Investment. In the 1970s and 1980s, it was basically the only tool available to look at performance.

This concept of measurement has led to various measures of maintenance cost using some form of investment value as a normalizing denominator. Measures of cost in relation to replacement value have emerged as a standard form of cost comparison. Consequently, there is a substantial interest in the methods for calculating estimated replacement values (ERV).

Using plant investment to normalize maintenance costs
Using investment in the calculation of maintenance costs provides a convenient basis for comparing plants of a similar type but which vary in size. Within a reasonable range, using the ERV in the cost calculation (dollar cost/dollar ERV) is a valid mechanism for comparing plants that differ in size. The rationale for using the estimated replacement value, rather than the original cost of the plant is the effect of construction cost escalation over time (inflation). Two relatively new plants built 10 years apart could have original costs that vary by 50 to 100 percent.

Using the maintenance cost/ERV metric
Any manufacturing facility has maintenance costs that vary from month to month. Cost fluctuations may represent scheduled maintenance shutdowns, unexpected shutdowns, seasonal maintenance work, or preventive maintenance tasks. Because some fluctuation in maintenance cost is normal, looking at maintenance costs monthly is best done by comparison with budget. Looking at maintenance cost/estimated replacement value is best done quarterly and annually to ascertain the long-term trend.

In the final analysis, anyone who has responsibility for maintenance and reliability has two primary business contributions: highly reliable equipment and the lowest consistent maintenance cost. Measures for each of these functions tend to be trended over time. The maintenance cost/ERV measure is best considered as a component of a total measurement model, such as the one outlined in the accompanying diagram.

The pitfalls of estimated replacement value
The first basic requirement is to ensure that the maintenance costs you have assembled and the replacement investment value you are using are calculated on the same basis, and that the costs collected represent maintenance expenditures on the investment considered. A potential stumbling block is to discover that the ERV does not agree with an insurance value. In that case, some investigation is in order to establish what was included in the insurance value.

Another pitfall is discovering that not all corporations use the same indexes when calculating inflation factors. Some use Bureau of Labor Statistics factors (Construction Cost Index or other); some use the Marshall-Swift index; some large corporations have established their own factors, based on corporate construction history. For older plants, these factors can present substantially different views of replacement value. And when a plant is bought or sold, its current value may be established as the purchase price, rather than an indexed original cost.

Finally, some tax rules allow depreciation of a plant to the value in use. So the real trap is that a plant's actual value, original or current, may be a mystery. When the plant's investment books are clouded by some of the pitfalls mentioned previously, I tend to rely on the insurance value as the best available estimate of a plant's current value.

What is included in calculation of maintenance costs?
Simply stated, maintenance costs include direct labor with benefits, materials, labor by contractors, and salaries and overhead. The sum of these components should be considered total maintenance cost. Each of these components has a definition that should be consistently applied. The safest approach is to use the definitions required in the SEC 10K report.

How to calculate replacement value
Once you have established that the original equipment investment figures reasonably agree with equipment actually in use (and being maintained), the next step is to identify clusters of equipment by the year in which they were acquired. This activity will allow you to consider each cluster of investment and escalate it to a current value, using the selected index. Your company may already use a preferred index, or you may choose the index protocol you believe to be most accurate. I prefer to use the Bureau of Labor Statistics Construction Cost Index (BLS CCI). There are variations in index methods, and the variations become magnified with older plant and equipment.

The next step is to sum the indexed clusters of investment to get a total current value of plant and equipment. It is a good idea, at this stage, to compare the indexed value of the plant with other plants recently built, adjusting for size and available insurance values.

Even when a company is self-insured, there is normally an established "insurance value" to help define the financial exposure the company risks. These values are typically prepared by an insurance underwriter, even if the plant is self-insured. Underwriters follow a procedure very similar to the one described.

What are the merits of tracking cost/ERV?
Looking at maintenance costs per investment dollar recognizes that costs go up with increasing amounts of equipment. Using ERV in the denominator helps to place the amount of equipment in consistent terms, that is, today's dollars.

By normalizing size and age of plant, it is possible to compare performance with a much wider base of data. The adage that an older plant will cost more to maintain is not supported by data, at least over the first 25 or 30 years of its life. A poorly maintained 10-year-old plant may be in much worse shape and cost more to maintain than a properly maintained 25-year-old plant. The cost versus age curve is far from a linear relationship. If maintained properly over time, a plant is continually being restored to as-new condition, a basic tenet of the total productive maintenance philosophy.

Maintenance cost/estimated replacement value is a standard barometer of maintenance performance. For all its limitations, it is a useful and widely accepted measure.

Limitations of the cost/ERV metric
Aside from the difficulties of determining the original cost and selecting an appropriate index protocol, there are other problems and stigmas attached to the use of ERV.

It is a measure that has often been used to browbeat maintenance managers. It may steal focus from reliability issues or total cost of manufacture (for example, cost per pound). It may become the only measure managers look at—versus a balanced set of measures.

Basic tenets of benchmarking
There are some very basic and standard warnings in benchmarking:

• Never, never use a single metric to draw conclusions. It takes sets of three or four metrics to produce a sound conclusion.
• Look at cost, but also look at equipment reliability, staffing, basic practices in use, and stores and spare parts management.
• Benchmark across similar and dissimilar industries, but look more closely at those in similar industries. You can learn from both.
• Use benchmarking as a method to highlight opportunities for improvement, not as an end in itself. Be prepared to use the results to create or reshape a strategic plan.
• Use many measures for benchmarking. Use a focused, abbreviated set of measures for performance tracking. Some of the measures will be the same; some will differ.

Maintenance cost/ERV. Use it or not?
I say yes. Understand the limitations, understand the implications, and measure cost/ERV consistently. Use cost/ERV to set long-term goals, along with targets for plant reliability. Cost/ERV is one of the most widely used metrics available. World-class plants tend to fall in the range of 1 to 2.5 percent MT

Edwin K. Jones, P.E., is a consultant based in Newark, DE. He can be contacted at (302) 234-3438; e-mail jjones1432@aol.com.