• RCM analysis resulting in recommended RCM-based preventive maintenance (PM) tasks
• Carrying those RCM-based PM tasks to the plant floor (task packaging)
• Conducting the Living RCM Program to measure results and fine tune the process.

I found (much to my surprise at first) that successfully initiating and completing the first activity (analysis) was done with very little, if any, difficulty. The problems, however, with the other two activities were often extremely difficult, and sometimes catastrophic. These problems varied from site to site, but there are a handful of common topics:

Staff buy-in
Nothing new is ever successfully introduced into an operating plant, facility, or factory unless the people who are charged with the responsibility to do it are 100 percent behind it. You will obviously obtain some degree of acceptance of RCM simply by the successful completion of the analysis process on some complex plant systems. But this acceptance (buy-in) is very narrow, and, as a result, many practitioners often move on to task packaging without first obtaining a broader degree of ownership and buy-in from plant supervision and craft personnel. Without that broader acceptance, it is unlikely that any attempt to carry the RCM PM tasks to the floor will be successful. So, a carefully planned program of indoctrination and education must precede any attempt to actually do the RCM PM tasks, and the broadest possible inclusion of plant personnel in the analysis process itself should occur in order to systematically develop buy-in and ownership with the work force.

Equipment-oriented mindset
In a typical plant, we commonly find craft and supervisory leaders to be skilled and dedicated people who have spent many years of hands-on work with the equipment. In fact, their careers are focused on assuring that the equipment is always operating or available to operate if called upon. In other words, their job focus is equipment preservation. However, RCM takes a different view of what their job focus should be—namely, to assure that critical plant functions are always available when required. This is function preservation.

The shift in emphasis from equipment to function preservation frequently becomes a difficult concept to sell; yet it is the basis for all of the RCM-based PM tasks. Plant personnel need to have some grasp of the conceptual logic behind RCM, or they will have difficulty changing their old (and comfortable) ways of doing business.

New tasks, new technologies
Human beings resist change. We are comfortable with the status quo. Over the years, in comparing the content of existing PM programs versus a recommended RCM-based PM program, changes in the range of 40 to 80 percent occur. Clearly, plant staff personnel must have some appreciation of where changes of this magnitude come from and why they are very beneficial to do. But beyond that, other resistance factors enter the picture.

The RCM program will always introduce new PM tasks (it also will delete nonvalue-adding tasks). These new PM tasks will require new work orders, often completely new procedures, and perhaps also new tools and craft skills.

In a large number of cases, RCM will introduce predictive maintenance (PdM) tasks into the program. This will always require some degree of new tools and craft skills. So the shift to the RCM program is not just a buy in and function-oriented mindset; it is also a commitment to some degree of time and money to make it happen. Thus, various levels of management approval could be involved. And most certainly, a dedicated attitude among the craft personnel together with efficient resource planning is a must if successful implementation is to occur.

Robert C. Baldwin, CMRP, Editor

The gearhead mentality was first called to my attention by my son. He has been teaching electric guitar and bass for some years and applying his income toward his education. He is now in the home stretch of a master's degree. A number of his students have always wanted to spend the lesson time paid for by their parents in discussing the pros and cons of various models and brands of guitars, amplifiers, and effects pedals rather than on learning to play the instrument. He calls these students gearheads.

Music gear usually doesn't make much of a difference if you don't know how to play, or don't practice very often.

There are gearheads everywhere. Lots of them are in sports, looking for the best racket, club, ball, or shoe to give them that winning edge. In fencing, the sport in which I compete, the gearheads are easily sucked into discussion on the virtues of various sword handle designs—French, Belgian, Russian, Italian, American, Visconte, etc. It doesn't make much difference what kind of handle you use if your feet are slow, or you can't put your point on the target, or you can't make an effective parry.

Sports gear usually doesn't make much difference if you can't keep your eye on the ball. Laser guided rackets and clubs aren't available & yet. And when they arrive, the gearheads will have them, but performance in the new laser game will remain a function of conditioning, skill, and strategy.

There was a newspaper story recently about the initiative in Wyoming to connect every schoolroom in the state to the Internet, including a six-student school that meets in a mobile home. The author pointed out that those students were more interested in working the ranch than surfing the net.

Educational gear doesn't make much difference without a challenging lesson plan developed by an understanding teacher.

So, when it comes to gear, how different is reliability and maintenance than music, sports, or education? If you're a gearhead, it's time to grow up and work on the fundamentals instead of looking for some technology to save your skin. When you grow beyond the gearhead stage, our directory can help you in your search for the best software to execute your reliability strategy. MT

In enterprise asset management or computerized maintenance management system (EAM/CMMS) is fundamental to running a reliability and maintenance organization in a businesslike manner. Such a system has been keeping us on track since the late 1980s.

Our five facilities in Sturtevant, WI, produce the base polymers used by the SC Johnson family of companies. You'll find them in everything from floor coatings to, very likely, the ink and coating on the article you're reading now. We have 138 operators and staff supported by 10 maintenance technicians who, in turn, can be supplemented with staff from SC Johnson central maintenance.

As an ISO 9000 certified facility and member of the Chemical Manufacturers Association, we always desired to account for our maintenance operation. We had started our own stockroom to provide needed special parts and wanted to track work orders, parts, and other aspects of maintenance. We knew a computerized system would help us more efficiently meet and support our objectives and the regulatory requirements for maintenance integrity.

In the late 1980s, we selected Mainsaver as our EAM/CMMS and, from the get-go, employed the full system, including inventory control, purchasing, work order system, and predictive maintenance. We saved over $200,000 that first year through consolidating our purchasing power. We were able to demand better pricing and obtain shorter delivery times. In addition, we received savings from the efficiencies such an EAM/CMMS provides.

We have been able to maintain spares at a level that is both sufficient and cost-effective. Reports are generated and requisitions issued whenever quantities drop below a predetermined level. Sufficient stock is available for scheduled projects.

The purchasing module generates purchase orders (PO) for both stocked and nonstocked items, special orders, and services. It tracks open POs and generates a list of those that are past due. When we create a PO, our Finance Department pulls through the information for the accounts payable system, later matching up the PO with the vendor invoice.

Our system receives maintenance input, creates work orders, and tracks work in process. It provides a variety of reports, including work status and equipment availability, as well as cost and repair history. This is especially important for creating a maintenance program that's predictive and proactive.

Today we're tracking and performing predictive maintenance on 1300 various reactors, tanks, valves, pumps, and controllers. Each of these is identified in the system with its own equipment number. We track the history on each piece of equipment and can write work orders against all of them. We average 62 work orders a day.

In addition, each of these listed equipment products has many spare parts. In fact, we stock over 4000 unique items in our stockroom and turn this stock 1.3 times per year.

How our system works
It doesn't happen very often, but let's assume an equipment asset, such as a valve, breaks. First, a work order is written to repair Valve No. 1234. The appropriate spare parts, designated on the spares list, are checked from the stockroom and installed. We know when the failure occurred, what parts were issued, who repaired the valve, and when the problem was corrected.

In addition, we also will determine if the valve is to be disposed of or repaired. If repairable, a new work order is written. The valve is provided the spare parts it needs, as written on that work order, and rebuilt. It then is issued back to stock. Again, we can determine the materials and labor expense of fixing that valve.

Histories are analyzed and used to update the predictive maintenance needs of that valve application and whether it is economical to repair or dispose of such valves. More importantly, though, because of having the right spare parts on hand, when we have a breakdown, we can respond and repair more quickly to keep that line flowing.

Never having breakdowns or downtime is even better. That's where predictive maintenance comes in, and we count heavily on the EAM/CMMS to assist us. In addition to knowing the history of our equipment, we know the number of hours Valve No. 1234 should operate. We know its efficiencies from our automated processing system. That valve should be able to handle 100 gpm. If its efficiency slacks to 99 gpm, we need to keep an eye on it. Let's assume the line is scheduled to run for another 4 hr. We'll nurse it to avoid a breakdown or slowdown. The second the line stops, we're there to replace or repair that valve.

Our lines run 24/7 and can be in continuous operation for a month or two at a time. That's a maintenance nightmare. On the other hand, we do know when the plant is scheduled for a shutdown. So does the EAM/CMMS and, using it, we know what equipment needs to be updated during that shutdown, based on the tracking and histories of that equipment. We also know what parts are needed so, ahead of time, we order those we don't have and assure all required parts are in stock by shutdown.

For scheduled shutdowns, we quite often will hire two or three people from central maintenance to help our 10 staffers. Again, we know what the workload will be, based on histories of both equipment and labor time. Once that plant stops, we get to work, refurbish the plant in the limited time allotted, and assure that the facility is ready to go when production wants to turn on the switch.

Reports are vital
It's one thing to collect all the data. It's something else to get it into information that helps us manage. We can track our individual maintenance technician hours, even when nonmaintenance functions such as training or company meetings are attended. We break out that time so it's not allocated to actual maintenance work. We need to know the exact time spent on specific jobs. Knowing how long it takes to replace the typical Valve No. 1234, we know how much time to schedule for replacing 15 of these valves when we have a plant shutdown. We don't want to hire too many or not enough central maintenance help plus we can better schedule our own people.

A shiny future
We're not standing pat. During the second half of this year, we plan to switch our system from an IBM AS/400 computing platform to one using Microsoft Windows, which is no problem with Mainsaver EAM/CMMS. We're also looking at the web-enabled benefits. For instance, we have a sister plant in Delaware that's now on its own. With enterprise visibility, especially on key, expensive parts, we could increase our stocking power, minimizing the redundancy of stocking seldom used parts. We could make both plant maintenance operations more efficient by having even better histories on parts and suppliers.

The slogan of Johnson Polymer is "where solutions surface." We in maintenance also like to think of it as our own for our plants and, in turn, for our customers. MT

David J. Wenszell is stockroom manager and training coordinator–North American manufacturing at Johnson Polymer, Sturtevant, WI 5317l

This article will identify some of the sources of the problem and offer a few suggestions as to how to dramatically reduce the reoccurrence of failures due to misalignment.

Pre-alignment preparation
The amount of time spent going through a pre-alignment checklist directly affects the longevity of the equipment. Lists may range from a single sheet of paper with 10 items used at a wastewater treatment facility to a 100-pg document at a nuclear power station. It is important that each item on the list be addressed before attempting to perform an alignment on any piece of rotating equipment.

Soft foot correction
This is the most overlooked step in preparing to perform an alignment. If this step is neglected, hours can be spent trying to achieve the alignment tolerance required for the equipment. Time spent here will greatly speed up the alignment job and will contribute to the life of the machine.

Soft foot has been called machine frame distortion, coplanar correction, and several other names. The bottom line is that if all of the feet of both machine components do not rest firmly on the top of the baseplate, when the hold down bolts are tightened movement occurs.

The issue of torque wrenches also needs to be addressed. If craftspeople are spending an inordinate amount of time working on alignments and are getting frustrated with those moves that calculate out to add 0.005 in. and then remove 0.006 in., it is probably a good time to invest in a couple of good quality torque wrenches. If consistency cannot be achieved when tightening bolts, a lot of time and money is wasted.

Hardware setup
After each point on the list has been examined and all corrective action has been completed, alignment hardware can now be attached. It is always good practice to make sure that the tool is ready to perform its function. When using dial indicators, make sure the stem moves smoothly in and out, the bezel turns, and it is easy to read. If it is possible, bring an extra one along to the jobsite. Accidents do happen.

When using a computer- or a laser-based system to assist in obtaining measurements and calculating the needed corrections, make sure the batteries are in good condition and are fully charged. Dead or leaking batteries can cause serious problems and make the job take longer to complete.

Check the chains, rods, nuts, thumbscrews, etc., for rust and freedom of movement. Some of these tools sit on the shelf for long periods of time between uses. A quick shot of lubricant can help avoid a stuck or cross-threaded part.

Make sure to collect all the accessories and tools needed before going out to the jobsite. If the method or system has not been used for a while, make a quick review of the correct procedures. It can save a lot of time and frustration in the field.

While in the process of taking readings, make sure the readings are repeating. If the values are changing every time a set of readings is taken, there may be a problem with the hardware, in the bearings, or in the coupling. In addition to being repeatable, the readings also should be reproducible. Measurements should be reproducible to within 0.0005 in. to instill confidence in the installation. If they are not, a deeper investigation needs to be made as to the cause of the inconsistency.

Use the proper tools the right way
After obtaining a set of readings and determining that corrective action is required to achieve proper alignment tolerances, use the right tools.

When vertical corrections are called for, use pre-cut shims. Most shims available are made to close specifications and generally measure to within a half thousandth of the thickness indicated on the shim. It is always a good practice to check the shim before inserting it under a foot to be sure it is the correct thickness and to insure that one shim is not stuck to another, especially when using thin shims.

When raising the machine to insert shims, be careful. Personal safety is more important than anything else. A prybar can slip out from under the foot or the case and cause an injury. Parts can break off or bend. Lifting the machine with a chainfall or hoist is better. Hydraulic rams or mechanical jacks also can be used to lift or move the machine.

Horizontal movement of the machine is easier, but there are some things to watch for. If there are jackbolts present on the base of the machine, check to make sure they are lubricated and will turn smoothly. The bolts may be rusted in place and could require the use of a tap and die to restore freedom of movement.

Maintaining control and accurately measuring the amount of movement are essential. It is difficult to make precise moves with a sledgehammer, not to mention what that might do to bearings, seals, and couplings that were not designed to take heavy impacts or shocks.

Documentation
Always keep a record of the alignment work done. It is a good practice to record a set of as-found readings before making any corrections on the machine. After the alignment has been completed to within the manufacturer's or the facility's tolerances, make and keep a set of "as-left" or final alignment readings. These can be used the next time an alignment check is performed to see if any movement has occurred. A documented history of the work done on a pump and motor can be valuable in determining the life expectancy and overall operating condition of rotating equipment.

Record keeping forms and charts are available from most manufacturers and distributors of alignment hardware. Some have software packages that work in conjunction with their systems to provide a record of alignment jobs. Others also have the capability of downloading directly to a printer or to a personal computer to assist in generating documentation for future reference.

There are also several good maintenance management programs available that provide space for documenting alignment information along with vibration, infrared, ultrasonic, and lubrication analysis information.

The final argument
What is the response to "But you don't understand the people I work for. They will never give me the time to do all the things you have talked about."? Do the best possible job with the tools available, the level of knowledge available, and the amount of time given to perform the task. Most likely there will be the chance to work on that particular piece of equipment again in the not-too-distant future. For each opportunity, correct as many of the problems as possible and eventually everything on the list will be corrected. MT

Information supplied by Rob Collins, Mr. Shims, 729 N. Yale Ave., Villa Park, IL 60181; telephone (800) 727-4467

During the turbulent years of downsizing, restructuring, and globalization, another important change has been taking place, but largely off the radar screen of most observers of industrial management. It is the pursuit of corporate maintenance and reliability identity by major companies. As a witness to many of those "transformations," I have observed a number of common threads in many of the companies' success stories.

In the mid-1980s, after 25 years in the manufacturing plant environment at DuPont, I had an opportunity to serve in a role that called for an unrestrained look at maintenance and reliability practices outside of DuPont. It was during the early benchmarking work from 1987 through 1993 (the year I retired), that we in DuPont first began to observe the techniques and strategies used by other companies to drive improvement in their maintenance and reliability cultures. Since 1993, I have observed the strategies of several multi-site companies, small and large, including Alcoa, Amoco, Bayer, Clorox, Hercules, ICI, Rohm & Haas, Stepan Chemical, and the U.S. Postal Service.

The approaches used by some of these well-known companies indicate the presence of several common strategies.

Similar approaches: Evolving cultures
Basically, all the companies started their efforts with some form of assessment of their current capabilities and maintenance practices. Specifically, all the companies mentioned in this article started with the question "Where are we now?" What separated their assessments from more conventional maintenance audits was the concept of quantitative comparison with other companies' plants through a process called benchmarking. The benchmarking approach perhaps leads to the same conclusions as a conventional audit, except that it carries the credibility of validated (apples-to-apples) comparison data.

In all cases, benchmarking assessments provided a clear view of the plants' strengths and improvement opportunities. The documented strengths allowed for corporate sharing of pockets-of-excellence. The documented improvement opportunities provided a basis for each plant to develop a strategic plan for maintenance and reliability - a roadmap for future improvement. Taken collectively across multiple corporate sites, the improvement opportunities often underscore common issues that need to be addressed at a corporate level.

The natural consequence of benchmarking multiple sites, developing site strategies, and recognizing key common issues, was the commissioning of corporate steering teams that were created to address the common issues so plant sites did not have to "reinvent the wheel." These steering teams often became the consensus agents-of-change by:

• Determining strategies to address key corporate issues.
  
• Preparing corporate guidelines for the various segments of maintenance and reliability management (e.g., spare parts management, planning and scheduling, contracted maintenance).
  
• Providing training and training tools to assist plants' efforts in boosting awareness of the changing reliability culture.

Amoco (BP Amoco) in transition
In 1996, the Amoco Chemicals Manufacturing Council established 20 manufacturing metrics to measure performance of the chemical sector and the chemical plants. It also established five "Networks of Excellence" to drive improvement in these metrics. One of these networks, the Maintain Asset Network (MAN), served as a vehicle to substantially strengthen the culture of maintenance and reliability in Amoco's Chemical businesses over the past 5 years.

Initial MAN group activities centered on improving three primary metrics:

• Maintenance costs (as a percent of estimated replacement value)
  
• Availability ratio (reliability)
  
• Sustaining capital.

The baseline cost was established and a goal was set to reduce maintenance by 50 percent over a 3-year period. The group struggled with the magnitude of the goal, differing maintenance accounting practices, and the calculated replacement value of the plants. One network member was assigned the task to develop standard guidelines for maintenance cost accounting and replacement value calculations. The MAN members also devoted time to understand each other's organizations, work processes, current efforts, and opportunities.

The benefits of networking—working together to develop consensus and synergy—became evident. It was clear that the network approach would continue to be a key ingredient in setting priorities and allocating resources.

A strategy subcommittee decided that it would support a project to benchmark the maintenance and reliability practices at several representative Amoco plants. The first comprehensive report was issued in 1998 and was reviewed with the manufacturing council. The report found that there were several "pockets-of-excellence" in Amoco plants. Several data correlations also were made:

• Some plants with stronger commitments to support staffing have lower costs.
  
• Several plants with the greatest commitment of reliability resources have lower costs.
  
• Plants with more disciplined planning practices tend to have lower costs.
  
• Plants with the greatest productivity have well-staffed reliability functions and do the best job of planning and scheduling.

Numerous plant-specific recommendations were made in the individual plant reports, but there also were several recommendations for the sector as a whole, including:

• Prioritize work properly
  
• Train planners
  
• Develop long-range planning processes
  
• Close reliability staffing gaps
  
• Leverage pockets-of-excellence
  
• Reduce slow-moving inventory
  
• Reduce warehouse staffing

Based on the rolled up savings generated from the plants benchmark teams, the initial report estimated that the sector could reduce maintenance costs by 30 percent and estimated that it would take 3-5 years to realize this savings. Some of this work was described in "Strengthening Asset Management at Amoco Chemical" (MT 9/99, p 12).

Amoco, through the MAN group, developed an excellence model for maintenance and reliability that focused on condition monitoring and sound, basic preventive maintenance (PM) work. Subsequently, with the merger of Amoco and BP, the two companies merged their reliability networks into the Maintenance and Reliability Network (MRNet). The new network has issued a new global excellence model which it calls "Getting Maintenance and Reliability Right," or the GMRR Guide.The current BP Amoco Excellence Model contains eight key elements and 16 key maintenance and reliability processes. BP Amoco supports performance measures, with emphasis on asset utilization, equipment reliability, and financial results.

The 8 elements are leadership and accountability, people, health and safety, environment, productivity,strategy, reliability, and technology.

The sixteen processes include delivering assurance, performance targets, reliability management, computerized maintenance management system, equipment ownership, equipment improvement teams, root cause failure analysis, early equipment management, reactive to proactive maintenance, planning and scheduling, spare parts management, contractor management, turnaround processes, quipment inspection and integrity, knowledge management, and maintenance tool box.

Alcoa
Work with Alcoa began in 1994 with two unrelated requests. The first was from a plant in Iowa investigating the popular metric of maintenance cost as a percent of plant estimated replacement value (ERV). The second was through an organization in Australia conducting a benchmarking study on behalf of 12 Australian manufacturing plants, including an Alcoa smelter in the state of Victoria.

As a result of the work in the U.S. and Australia, two separate global studies were commissioned: One for the global smelting operations, one for the global refining operations. Early in the process, there was little networking with the formality or impact seen with DuPont or with BP Amoco. Both business divisions were simply trying to drive improvements at the plant level through benchmarking and identification of improvement opportunities. The assessments spanned mid-1994 through early 1997 and included 11 smelters, seven refineries, and three mining operations in six countries.

Both the Smelting Division and the Refining Division took the results seriously and drove hard to get the sites to develop improvement strategies. Shortly after the completion of assessments in two Italian smelters in early 1997, the Smelting Division assigned a new manager to meet with smelter engineering and maintenance managers in a networking environment. Their mission was to review key issues and to drive improvement. During the next 2 years, Alcoa went through a period of substantial change, with numerous mergers, acquisitions, organizational restructuring, and personnel retirements and reassignments. Continuity of efforts to improve maintenance and reliability in the Smelting Division was made difficult by the continuous sequence of changes taking place.

In 1999, a renewal of commitment appeared in the Smelting Division. Driven by the division's manufacturing director, the maintenance network began to meet and discuss priorities. As a corporation, Alcoa had decided to use its variation of the Toyota Production System (Alcoa Production System—APS) as a primary umbrella for change across the corporation. The Smelting Reliability and Maintenance Network saw this as an opportunity to drive reliability improvement and asset utilization concepts under the APS banner.

What began in 1994 as an assessment of maintenance costs, once again became an issue of driving reliability. The Maintenance Excellence Model that emerged at a corporate level highlighted 10 key elements as critical success competencies:

• Leadership
  
• Planned maintenance
  
• Preventive maintenance
  
• Predictive maintenance
  
• Reliability focus
  
• Materials management
  
• Contracted maintenance
  
• Human resources
  
• Research
  
• Networking

The primary focus for the Smelting Division for year 2000 has been training based on the 10 best practices identified in its excellence model and APS, with strong linkage between the two training schemes.

As with BP Amoco, Alcoa places strong emphasis on performance measurement. The primary metrics are contained in Alcoas concept of a "Balanced Scorecard" which looks at both leading and lagging indicators.

Leading indicators:

• Planned maintenance
• Preventive compliance
• Predictive maintenance
• Overtime
• Backlog

Lagging indicators:

• R&M cost per unit of product
• Safety
• Equipment availability
• Delivery performance
• Productivity

A third category of benchmark indicators is used to keep tabs on the progress of the "outside world."

As with BP Amoco, Alcoa uses today's Web technology to link locations, techniques, metrics, and information around the world.

DuPont
DuPont's efforts have been widely reported in this magazine and elsewhere. A brief sequential summary will serve to make the comparison of similar approaches taken by others.

DuPont, of course, is well known for its early work in benchmarking and reliability practices. In the late 1980s and early 1990s, DuPont plants evolved through improvement strategies, recognition processes, maintenance excellence models, and evaluation of Total Productive Maintenance (TPM) concepts. More recently, the focus has shifted from maintenance excellence to manufacturing excellence. What was once the Corporate Maintenance Leadership Team (CMLT) now falls under the umbrella of manufacturing excellence. Just as maintenance excellence is comprised of a number of best practices, maintenance excellence itself is a best practice of the manufacturing task.

DuPont, at a corporate level, is driving manufacturing excellence with the tenets of Six Sigma. In many ways, the company's approach parallels that of Alcoa with APS and BP Amoco with TPM. Networks are active, metrics are in place, the excellence models are developed, and progress continues. As with BP Amoco and Alcoa, DuPont uses the Intranet and Web technology to make information readily accessible.

FACILITIES CAPABILITY MODEL ROHM & HAAS: Example of an analysis of a unit’s asset utilization.

Rohm & Haas interacted with several benchmarking partners during the mid-1990s and used the resulting knowledge to develop its own view of world class maintenance practices. It then developed a two-tiered assessment process that:

1. Provides an initial assessment that is more subjective than benchmarking.
2. Provides a more in-depth look at a site's practices, with recommendations for improvement actions.

The process is team-based and develops a consensus set of priority key issues that the site team can use for the focus of its strategic planning. The process was outlined in "Assessing Maintenance Performance" (MT 11/97, p 13).

The second-tier process tends to be more quantitative, and results in scoring against a more rigorous excellence model. Again, the result focuses on issues for improvement, using the strategic planning process. It also provides a quantitative assessment of maintenance practices. The process today includes an analysis of the unit's asset utilization (AU) in an effort to bring attention to the business potential of improving reliability.

Today, Rohm & Haas thinks in terms of manufacturing excellence with reliability and maintenance as key ingredients. The maintenance excellence components of the Rohm & Haas "Reliability Policy and Best Practice Manual" are:

• Leadership
  
• Planned maintenance
  
• Process and equipment reliability
  
• Reliability-centered design
  
• Maintenance material management
  
• Contractor administration
• Human resource development
  
• Information systems
  
• Performance measures
  
• Assessments

Rohm & Haas has a well-developed maintenance and reliability network, coordinated from corporate offices in Bristol, PA. Performance measures are part of the company's culture today. Every operating area is encouraged to employ two principal measures: Asset utilization and maintenance cost. Additional measures are used as core result indicators and as input/output metrics for the functional activities outlined in the Best Practice Manual.

Rohm & Haas continues to evolve its philosophies and processes today. With its acquisition of Morton Salt, additional work is underway to broadcast the basic concepts of manufacturing excellence, and to continue the process of assessment, strategy development, and reliability improvement.

Common threads
By now, you have seen some of the common threads in the approaches used by these companies. These strategies have been observed in many companies' successful efforts to strengthen plant performance, reduce costs, and bolster business results. Perhaps the most consistently successful tools are:

• Use of peer networks to share knowledge and build consensus.
  
• Use of benchmarking or other assessment tools to identify both strengths and improvement opportunities.
  
• Strong focus on reliability, rather than on cost reduction.
  
• Development and use of an excellence model to describe and define corporate beliefs regarding maintenance and reliability.
  
• Extensive use of performance measures, with appropriate "target goals."

It is also clear that each of the companies discussed has made a concerted effort to incorporate its improvement strategies with other corporate initiatives, trying desperately to avoid the "program-of-the-month" syndrome. The best indication that these efforts have paid dividends rests in the durability and continuity of each companys journey to excellence.

The payoff
The payoff for each of these companies lies in improved business results. While we once considered success to be reflected in lower maintenance costs, we now hear many companies measuring their success through:

• Lower costs (maintenance and production costs)
  
• Higher equipment productivity
  
• Postponed plant expansions (deferring capital requirements)
  
• Improved morale
  
• Better housekeeping
  
• Improved safety

The typical benefit sequence is substantially lower costs during the early years, followed by continuously improving plant reliability and throughput that continues indefinitely.

For smaller companies?
Do these common threads and payoffs apply to smaller companies with only a few plants, or to single-plant companies? Yes, best practices still apply even to the smallest plants.

Best practices apply, regardless of organization structure. It becomes a matter of how to adapt the best practice concepts in a smaller plant's environment. Multi-plant networks become meaningless when you have a single plant. Writing volumes on maintenance excellence models becomes bureaucratic when you have only a few plants. Formal documents may become simple statements of beliefs, agreed to by the plants, and supported by the corporate manufacturing manager. Performance measures may be less formal and fewer in number, but thoroughly understood by all. What is absolutely essential is a commonly understood philosophy of maintenance and reliability practices.

Culture shifts occur slowly
While the improvement issues may be very clear, and the action items can be easily listed and prioritized, the actual act of changing a corporate maintenance and reliability culture will take time. Generally, the larger the corporation, the longer it will take to shift the culture. Substantial inroads can be made in 5 years. Don't expect to see substantial changes in employees' behaviors or beliefs during the first 2 years. We all resist change to some degree. Permanently changed beliefs and behaviors will take time to evolve.

You'll know you've made progress when you can begin to feel the employees embracing and driving the new concepts rather than resisting and doubting their effectiveness. To speed the cultural evolution (or revolution, if you're in a panic), involve employees early in the process. Involve employees at every level possible, as early as possible. Encourage consensus building; promote teams and sub-teams, focus on business outcomes. Include as many people in as many aspects of the effort as possible. Remember, it's hard to berate a strategy for the future when you've been part of its development.

Much has been said about the emerging global economy. Technology's pace is accelerating; companies are merging; organization structures are changing (and downsizing). Companies that adopted the status quo are already out of business. Those who improved too slowly are in peril. Those at the forefront of change, and continuously improving, will survive.

Most successful improvement efforts I have observed over the past 15 years have started with an honest assessment of current state. If you can see the landscape, pinpoint where you are, and pinpoint where you want to get to, the rest is strategy and execution. Not much different from football, really. Once you know youre on the 50-yard line, and you want to be in the end zone, the rest is strategy and execution. Wear your protective gear and have a safe journey. MT

Edwin K. Jones, P.E., is a consultant based in Newark, DE. He can be contacted at (302) 234-3438

Competition in the global economy has put industrial enterprises under intensive pressure. There have been significant shifts in the relationships between producers, suppliers, and consumers. The need for improved production reliability and reduced expenses is clearly demonstrated by production strategies that include just-in-time material supply and delivery. Both suppliers and consumers are working to optimize their cash flow by managing throughput and reducing the expense associated with maintaining excess inventories, while still ensuring that their product throughput requirements are met.

From just-in-time delivery to higher quality and increased technical support, customers are requiring more from their suppliers. Not only must the product be of high quality, and at the lowest possible price, but deliveries must be on time. Often severe financial penalties are imposed by an industrial partner consumer when a supplier fails to deliver on-time or at required quality thresholds. Consequently, the financial impact of unexpectedly stopping a production line or discarding a batch of a product can be devastating.

Because of the need to ensure that production commitments are achieved, companies increasingly are turning to plant asset management as an optimization strategy to improve their process efficiency and reduce maintenance, thus enhancing their return on assets. According to a June 1999 study by the ARC Advisory Group, companies are reporting as much as a 30 percent reduction in maintenance budgets and up to a 20 percent reduction in production downtime as a result of implementing a plant asset management strategy. Since as much as 40 percent of manufacturing revenues are budgeted for maintenance, these savings contribute significantly to a company's bottom line.

Maintenance strategies that once were "run-to-failure" now are "condition-based." Enterprise asset management (EAM) systems and computerized maintenance management systems (CMMS) are implemented to support maintenance scheduling, workflow management, inventory management, and purchasing, and to integrate these functions with automation, production scheduling, and manufacturing systems. Leading corporations now have direct connections from their EAM system to electronic-commerce maintenance, repair, & overhaul/operations (MRO) procurement systems, which allow paperless purchasing of parts and offer considerable time and cost savings compared with traditional purchasing methods.

Plant asset management (PAM) systems tie into a variety of plant information systems.

The purpose of a PAM system is to provide timely information to operations and maintenance (O&M) personnel in order to safely increase the total production output of a plant at a reduced cost per unit of output. These benefits occur as the manufacturing facility makes optimum operating and maintenance decisions through the application of a PAM system's information solution. O&M personnel are constantly faced with decision-making based on limited information. PAM systems make this decision-making job easier by providing knowledge about the current and future condition of vital production assets.

Maintenance support
PAM systems assist maintenance personnel in answering the following questions:

• What equipment may fail if it does not receive maintenance intervention?
  
• What intervention should we take and how soon?
  
• What parts should I order and how soon?
  
• What is the optimal blend of condition-based (CBM), calendar-based (PM), usage-based (PM), and run-to-failure maintenance for a given piece of equipment?

Operations support
PAM systems assist operators and production planning personnel in answering the questions:

• Should I make any adjustments to my process now to prolong the life of assets critical to my process?
  
• To what extent can I increase my process output without incurring an unacceptably high risk of unexpected process slowtime, downtime, quality problems, or safety shutdowns?
  
• What is the risk of successfully producing X amount of product next week given a projected process utilization rate of Y?

The role of the PAM system as it turns plant measurement data into actionable information and issues advisories to both maintenance and operation systems by synthesizing the asset measurements it has obtained is outlined in the accompanying diagram "Plant Information Systems." A PAM system contains eight modules: asset information register, data harvester, computed indicators calculator, data archiver, condition monitor, asset health analyzer, O&M advisory manager, and O&M gateway manager.

Asset information register
The first module of a PAM system is the asset information register. This module provides the rest of the PAM modules with information about the location of the asset and its criticality to the process, as well as asset-specific model data and nameplate information. Registers also need to store measurement location information, such as the type of transducer being used, the post-processing to perform on a measurement location, and the spatial orientation of orientation-sensitive measurements such as vibration locations. Some registers also keep information from a reliability study such as an RCM audit, as well as financial metrics that could influence decisions regarding the asset. Others include the dates of future maintenance tasks, such as planned overhauls, and can track work and failure histories on the asset through gateways to external systems.

Companies interested in open systems should look for register modules which support open asset information standards from open industry alliances such as the Machinery Information Management Open Systems Alliance (MIMOSA) which now publishes a universal set of codes for all asset equipment types, asset nameplate data, and measurement location types.

Data harvester
The next module of a PAM system is the data harvester. This module periodically gathers data from off-line and on-line measurements on assets ranging from smart valves to large turbines. In the off-line area, the harvester module contains interfaces to load and unload route-based schedules to various walk-around data collection devices, such as vibration data collectors, as well as operator inspection log devices and manually-entered inspection data related to assets. In the on-line area, the harvester module periodically extracts data from turbo-machinery protection monitoring systems, high-speed transient monitoring systems, periodic surveillance monitoring systems, control device monitoring systems, and process data historians.

The harvester synthesizes data from various monitoring technology systems, including shaft displacement, casing vibration, ultrasonic, electrical circuit, thermographic imaging, oil particulate, and oil chemical analysis systems. It correlates this condition-based monitoring data with the current process data in order for the PAM system to properly associate the dependent variables, such as vibration, with the independent variables, such as speed and load.

For companies looking for open systems, some suppliers of PAM data harvester modules now support open plant data access standards such as MIMOSA's Tech-File Import and Tech-XML Client interfaces (supporting both dynamic and scalar current value and historical data) and OPC Foundation's Data Access Client interface (for current scalar current value data only). These interfaces allow a harvester module to access any monitoring or measurement system that supports these universal data access standards.

Computed indicators calculator
A PAM system's computed indicators calculator module derives "features" to be extracted from the raw measurements and dynamic spectra as well as calculates "macro" indicators derived from multiple measurements (such as differential pressure). Calculations of rotating shaft and bearing vibration, sound, and electrical frequencies allow for a sophisticated "fingerprint" analysis of dynamic frequency data. These computed indicators are vital to properly discover early abnormalities in an asset. Some computed indicators calculator modules allow for the definition of a virtual sensor measurement, which is trended and treated as a physical measurement reading.

Data archiver
A PAM system's data archiver module provides long-term data storage of plant measurements with options for data error flagging, compression, and expiration. Data error flagging techniques include the tagging of data "outlyers" as well as the tagging of data with known data collection errors or data taken when the asset was off-line. Sophisticated data archivers also manage compression of the data by defining a "dead-band" range where a new data point must cross in order to be permanently stored. Archivers also manage data expiration and allow physical deletion from the on-line database, though many plants prefer to keep data in the archiver for up to 5 years in order to look at long-term trends in asset condition monitoring and performance data.

State-of-the-art archivers utilize industry-standard relational databases, such as Oracle and Microsofts SQL Server, and allow external access for distributed database management and other database administration functionality.

In the open systems arena, MIMOSA publishes an open Tech-XML Server and Tech-SQL Server interface (supporting both dynamic and scalar historical data) for data achivers (dynamic and scalar historical data) and the OPC Foundation publishes an OPC Historical Data Access Server interface (scalar historical data only) to allow archivers to "serve up" their data to other systems that support the same universal data access standards.

Condition monitor
A PAM system's condition monitor module facilitates the creation and maintenance of an asset baseline "profile" and then searches for abnormalities whenever new data or indicators enter the PAM system. The condition monitor module allows the end-user to establish normal and abnormal conditions for all measurements and computed indicators in the database. The measurements of interest can range from simple parameters such as temperature and oil particle count to complex data such as vibration spectra or infrared images. In all of these cases, the objective is to determine what is normal for the machine and identify the equipment in various abnormal "alarm" states.

Advanced PAM systems include inputs from process control data historians and sophisticated state-aware condition monitoring technology that can automatically set multiple "baselines" for equipment based on variable operating loads, speeds, and other process conditions. This allows the system to be sensitive to the current operational "state" so as not to over-alarm or under-alarm.

Asset health analyzer
The asset health analyzer acts on exceptions found by the condition-monitoring module. The analyzer module facilitates and permanently archives an analyst's evaluation of the current health of the asset in question. This process is assisted by integrating all relevant data into information displays that allow multi-disciplinary data (lubrication, vibration, thermographic, ultrasonic, process data, etc.) to be visually compared in multi-parameter plots and graphs. This asset health analysis is aided also through the use of automated diagnostic tools and rule sets.

After performing a diagnosis, a prognostic assessment is also needed to determine the future health of the asset in question and its projected time to failure and failure mode. An additional prognostic assessment also is required if the asset's failure mode will cause an impact on operations. This step is aided by tools that provide for easy review of the asset failure database, criticality analysis, failure modes and effects analysis, risk-based monitoring data, reliability-centered maintenance studies, and other reliability data. If production will be affected, then the asset health analyzer needs to store the projected process time to failure and failure mode.

To summarize, the analyzer records and stores the following output from the human analyst or diagnostic system:

• What data is truly abnormal for the process conditions? (asset symptoms)
  
• What could be causing the abnormality? (asset diagnosis)
  
• How and when will the asset fail if no action is taken? (asset prognosis)
  
• How and when will the process fail if no action is taken? (process prognosis)

In the area of open standards for asset health analyzer modules, MIMOSA publishes a universal set of codes of symptoms, diagnoses, and prognoses which assists companies who purchase MIMOSA-based PAM analysis systems to "mine" the asset health analyzer database to better understand which problems are being properly diagnosed and which ones are being overlooked.

A complete PAM system contains eight modules.

O&M gateway manager
The final module in a PAM system completes the transformation of data into actionable information. The O&M gateway manager module creates and manages gateways between the PAM system and a plant's operations and maintenance systems and personnel.

Most plants now have an EAM system or computerized maintenance management system (CMMS) which manages maintenance work management and parts management. The PAM gateway manager module establishes connectivity with the EAM/CMMS system. It issues and tracks work requests based on the asset's health analysis and retrieves work history information to facilitate better diagnosis and advisories. State-of-the-art gateway manager modules can submit work requests directly into an EAM/CMMS system, monitor the progress of the work order, and view equipment work histories in a table format or in a graphical Gantt chart. This allows the analyst to make better diagnostic decisions and to see the impact of maintenance on the condition of a piece of equipment. The EAM/CMMS then should be able to act on this information to order spare parts or issue a work order for repair, overhaul, or further monitoring.

PAM O&M gateway manager modules also require connectivity with the plant's automation systems in order to issue operational alarms and operation change requests. The modules should communicate urgent asset health alarms and recommendations to the human-machine interface (HMI) displays from a plant automation system (PAS) or distributed control system (DCS), which the operators are constantly reviewing. In addition, the module also should send operational change requests to the planning module of a manufacturing execution system (MES) in order to affect operational changes to extend a critical asset's useful life, thus optimizing production throughput and quality.

In order to communicate directly with O&M personnel, most state-of-the-art O&M gateway managers include e-mail and paging interfaces in order to notify plant personnel of urgent, impending asset failures. E-mail or paging message templates can be designed and then utilized when a given asset health condition warrants a transmission.

New XML-based integration standards from MIMOSA (Work-XML and Reg-XML Server) will allow bi-directional gateways to be built using universally, open systems. The XML framework allows for interoperability across intranets or even on the Internet. Companies desiring open systems should consider utilizing these industry standard interfaces wherever feasible.

Case study
Baltimore Gas & Electric Co. (BGE) is the first U.S. gas utility and one of the earliest electric utilities. In 1991, anticipating deregulation of the utility industry, BGE began developing a foundation to perform as a profitable, world-class energy company. To compete effectively in the deregulated market, BGE knew it needed to minimize costs and at the same time maximize the plants' power generation capacity. Since maintenance is one of a utility's largest controllable costs, the company began by looking for ways to improve operational efficiency and reduce operations and maintenance costs.

BGE implemented a plant asset management system in 1993 that integrated condition information from across all eight fossil-fuel power plants. BGE embraced a wide range of test technologies (oil analysis, vibration analysis, motor monitoring, etc.) in its facilities. The company documented cost savings of $16 million between 1994 and 1998 from this PAM system technology utilizing predictive maintenance to optimize operations and maintenance. In addition, it increased production by 14 percent while reducing fuel costs and improving heat rates.

Manufacturing and production enterprises are under intense pressure to achieve maximum efficiency. The winners will be those that maximize their investment in people and equipment assets to achieve highest profitability. For physical assets, the objective is to optimize the utilization of all plant assets—from entire process lines to individual pressure vessels, piping, process machinery, and vital machine components. The use of PAM systems is now making this a reality for state-of-the-art plants today. MT

Ken Bever is strategic project manager for Entek, 1700 Edison Dr., Milford, OH 45150; (513) 576-6151; Internet www.entek.com, and technical director for the Machinery Information Management Open Systems Alliance .