Recent discussions with industry leaders make it clear that a process for equipment reliability management is emerging. The process seems industry independent and includes several generic principles. Those out in front of this movement recognize the necessity to express reliability issues in financial terms.

Interest, involvement, and drive from the top are characteristic of leaders. Leaders value people and recognize that people, not things, create value. They recognize that maintenance is not a stand-alone, stovepipe we run it, you fix it process but rather a vital, inseparable part of manufacturing. Some call it capacity management, others TPM. In truth, it is both and much more.

There is a growing recognition that equipment effectiveness, maintenance and reliability improvement, and the heavily promoted TLA (three-letter acronym) solutions are worthless unless they can conclusively demonstrate improvements in availability, production output, quality, and conversion cost. If you can't prove it, you don't get it--or, if you have it, it might be taken away.

Leaders identify deficiencies that detract from production objectives by occurrence, cost, and lost opportunity. The information leads to a prioritized action plan. Those following this process recognize that the mix and priority of deficiencies shift with changes in market conditions and completion of improvement initiatives. We're dealing with a moving target.

Several readers commented that corporate downsizing and managerial indifference had eroded competency in such vital areas as predictive monitoring, precision alignment, and balancing. I'll bet those indifferent managers's eyes would light up if we talk financial numbers.

Let's begin with the big picture. Authoritative sources report that North American manufacturing spends between $200 billion and half a trillion dollars a year on maintenance. An article in this magazine a couple of years ago asserted that over 60 percent of maintenance is preventable. A reduction of just 15 percent represents a minimum of $30 billion. Most industry leaders are going for 25 percent minimum--$50 billion at the lower estimate of maintenance expenditures.

With this huge opportunity, the big puzzle is why isn't the maintenance optimization industry humming along? Paraphrasing Pogo, the swamp sage, perhaps the enemy is us.

I suggest both the opportunity and means are totally within our control. Those who are complaining about not being listened to, and having their efforts hampered by people with the interest and attention span of a five-year-old, should think back to their first difficult problem. Most technical experts developed their expertise with interest, enthusiasm, curiosity, education, time, and observing a lot of perplexing problems up front and personal. We're now finding that technical expertise and knowledge that we're doing things right isn't enough. The value of our efforts must be proven in thousands of dollars.

What are the barriers that keep reliability experts from learning the skills necessary to connect technical results to improvements in production effectiveness and business performance? I suggest the conditions are exactly the same as when today's reliability experts viewed their first frequency spectrum, balanced their first fan, repaired their first pump, performed their first shaft alignment. Today there is an advantage--recognition that technical knowledge must be reinforced with compelling financial justification demonstrating value. Think of your first complex problem. Everyone recalls being confused, uncertain, and more than a bit inadequate. What did you do? You learned and added to your knowledge. That's called experience.

Today we're faced with another challenge. Have you asked yourself what are the top five concerns of your plant manager? More importantly, how can you contribute to the manager's success and security in those areas? Find out, learn how, gather experience, and increase your personal satisfaction and worth. MT

Maintain Assets Network (MAN) has served as a vehicle to substantially strengthen the culture of maintenance and reliability in Amoco's chemical businesses over the past two years. It is one of five "networks of excellence" established by the Amoco Chemicals Manufacturing Council in 1996 to drive improvement in 20 manufacturing metrics established to measure performance of the company's chemical sector and chemical plants.

MAN met for the first time in late 1996 and consisted of representatives from nine U.S. chemical plants, three non-U.S. chemical plants, and one representative for eight fabrics and fibers plants. The group met bimonthly and began to set priorities, with initial activities centered on improving three metrics:

1. Maintenance costs, as a percent of estimated replacement value (ERV)
2. Availability ratio (reliability)
3. Sustaining capital

Baseline costs were established and a goal set for 1999 to reduce maintenance costs by 50 percent. 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 of developing standard guidelines for maintenance cost accounting and replacement value calculations. MAN members also devoted time to understand each other's organizations, work processes, current improvement activities, and opportunities.

Strategy development
Early in 1997, it became apparent that the group had to move beyond discussing the merits of the metrics and start to impact them. The network established five subcommittees to cover:

1. Long-term MAN strategy
2. Reliability improvement
3. Pumps
4. Centrifuge
5. Product change

The first subcommittee mission was to develop long-term MAN strategies to give the group needed direction. The other four subcommittees were to research and recommend best practices in their assigned areas that could be implemented at the plants to quickly improve equipment reliability and to reduce maintenance costs. They covered equipment reliability, pump maintenance and reliability, centrifuge maintenance and reliability, and reducing lost capacity from product changes.

It was believed that all of these efforts, if embraced by the plants, would deliver the overall asset effectiveness (OAE) goal of a 25 percent increase and the maintenance cost goal of a 50 percent reduction. The MAN strategy is summarized in the section "Three-Tiered Strategy."

Networking activities
The Reliability Subcommittee explored reliability best practices inside and outside the chemical sector and the company and reported to the network in December 1997. It recommended the use of 12 reliability practices and six reliability tools:
Reliability practices

• Elements of preventive maintenance
• Equipment repair history
• Corrosion monitoring
• Portable vibration monitoring
• On-line vibration monitoring
• Infrared thermography
• Positive material identification
• Rotating equipment alignment
• Steam trap monitoring
• Lube oil analysis
• Rotating equipment balancing
• Critical equipment monitoring

Reliability tools

• Reliability in engineering
• Reliability modeling
• Equipment maintenance plans
• Root cause failure analysis
• Reliability centered maintenance
• Data recording and analysis

All documents were placed on the Amoco Web page and updated as needed. The Reliability Subcommittee developed a self-assessment process for the plants that serves as the basis for "scorecards" developed by a new Measurements Steering Committee. The subcommittee's official task is complete, but the company continues to benefit from the relationships and networks that exist between the plant representatives, and the group plans to meet at least twice a year to share successes and problems they are experiencing in the reliability arena.

The Pumps Subcommittee also met extensively in 1997 and 1998 to explore and recommend best practices relating to pump maintenance and reliability in the same fashion as the Reliability Subcommittee. It completed its work in 1998 and issued seven best practice documents: pump repair procedures, pump repair documentation, pump repair training, condition monitoring, preventive maintenance, mechanical seals, and root cause failure analysis.

These documents are on the Amoco Web page, and the group also made recommendations to the Measurements Steering Committee to follow progress of the implementation of these practices. Amoco continues to benefit from the relationships and informal networks that remained in place.

The two other subcommittees produced best practice documents that were distributed throughout the chemical sector.

Benchmarking
The benchmarking process used by Edwin K. Jones, P.E., Inc. is conducted in three steps and focuses on a model of seven best practices:

• Leadership
• Planning & scheduling
• Preventive & predictive maintenance
• Reliability improvement
• Spare parts management
• Contract maintenance management
• Human resource development and training

The first stage of the assessment process was a kickoff meeting at each plant. It was designed to form the plant's benchmark team, define the roles of team members, review the benchmarking process, and provide an initial tour of the plant. A data questionnaire was left for the benchmark team to complete.

The second stage was a two-day meeting referred to as the validation visit. During this stage, key data are validated to be consistent with the comparison database. There are also interviews with maintenance craftsmen, maintenance supervision, operators, operator supervision, stores employees, reliability/maintenance engineers, contractor supervision, training coordinators, and maintenance planners and schedulers. A preliminary, verbal report of the findings is made to the Plant Leadership Team at the conclusion of the validation visit.

At this point, interpreting the comparison data, the interview issues, and the plant condition is initiated with discussion among team members. These issues are included in the final report, along with the observations of the "unbiased, external, calibrated resources," highlighting the opportunities for improvement. The final report has a balanced mix of team observations of maintenance practices and validated comparison data displayed in graphic plots along with data from "World-Class" plants.

The final stage, another two-day meeting, takes place approximately one month after the validation visit. The plant usually receives a benchmark report about a week before the third visit. The report includes plant data compared with other Amoco plants and with a selected set of "World-Class" plant data. Also provided is an initial estimate of the potential savings that might be obtained if the plant could close the gaps with the World-Class plants.

This third visit concludes the assessment process with a plant-wide review of the benchmark report. A great deal of emphasis is placed on shifting from the "assessment mode" to a "strategy development mode." The basic concept is: "OK, now that we have a better idea of where we are, where do we go from here?" The second day of this visit is then devoted to jump-starting the beginning of a Maintenance and Reliability Strategic Plan. The team selects areas to be improved, then lists specific tasks to deliver the desired results. Champions, resources, and dates are assigned to each task. The benchmark team then completes the strategic plan development over the ensuing two to three months.

Benchmarking results are summarized in the section "16 Plants Benchmarked." Each site's plan usually includes an overview of the maintenance strategy and how it fits with the plant's overall manufacturing strategy. It also includes some analysis of the savings potential that results from executing the plan. Savings are viewed in two categories: maintenance cost savings and business benefits of improved equipment reliability and availability. The plan lists the areas of improvement, the key issues, specific actions to be taken, metrics to be tracked, and a Gantt chart showing a timeline for all of the tasks to be completed. Seven plants have presented their plans to the network, with the remaining plants scheduled to do so in 1999.

Total Productive Maintenance (TPM)
After a TPM presentation to the Manufacturing Council in July 1998, the TPM Steering Committee (TPMSC) started to develop details around the essential TPM elements Amoco planned to pursue. These elements included:

• Equipment improvement teams (EIT)
• Asset ownership (autonomous maintenance)
• Asset reliability
• Maintenance effectiveness
• Early equipment management
• Training

The TPMSC included in its TPM model all known best practices from the subcommittees, the pockets-of-excellence from the benchmarking initiative, and other best practices gleaned from networking with other TPM companies and consultants. Because much of what was included already existed somewhere in Amoco, the TPMSC developed a site assessment tool to enable the plants to assess the quantity of work required in each of the TPM elements. This enabled plants to develop short-term strategies for the elements that were in use, and longer-term strategies for the elements requiring more time and effort.

The TPMSC then selected four areas of TPM as good places to start. They were autonomous maintenance/clean to inspect; process recording and data entry (PRIDE), an operator-based data gathering process using a combination bar code reader and data entry tool; equipment improvement teams; and work order prioritization.

These "places to start" provided a means to quickly immerse the plant in a TPM culture using best practices that had proven successful within Amoco. Plants could quickly link up with other plants that had implemented a given process, learn from their experience, and generate early success while developing their longer-range plans.

"Clean to Inspect," a process taught by Productivity, Inc., a TPM consulting firm, works on the principal that as you clean equipment, you inspect it thoroughly in the process. The detailed inspection identifies small abnormalities that could lead to poor performance or a breakdown. In other words, if you take care of all the little things, the big things will take care of themselves. It also has several ancillary benefits in that the employees who return equipment to like-new condition will work to keep it in like-new condition. During the process, cross-functional teams look for opportunities to improve the performance and maintainability of the equipment. It has been very successful at two sites in transforming operators from merely operators of the equipment into equipment caretakers.

PRIDE is an Amoco data-gathering tool that also can transform the operator into an equipment reliability resource. Using the Equipment Specific Maintenance Plans (ESMP), employees can select the equipment reliability data to monitor the equipment condition, predict impending failures, and help troubleshoot the root cause of breakdowns. This information can then be trended and used by the equipment improvement teams.

Equipment Improvement Teams (EIT) exist in some form at most of the plants. They are cross-functional teams that are given the time, training, and resources to address the root cause of poor equipment performance or breakdowns. Several plants have well-established EIT programs that serve as the cornerstone of their TPM effort. Other plants use them sporadically to solve major problems. The intent of TPMSC is to upgrade plants' use of EIT.

As cited in the benchmarking report, work order prioritization, misuse, and abuse were barriers to plants being able to plan and schedule their work. The Texas City plant recognized this in 1996 and learned a process called the Ranking Index of Maintenance Expenditures (RIME) at a planning and scheduling workshop at the Marshall Institute. It is a process where criticality of the equipment and the importance of the different types of work determine priority with minimum interference from people. Its use dramatically reduced the number of urgent work orders and it was cited as a pocket-of-excellence during benchmarking. It was thought that by using RIME, all plants could do more and better planning and scheduling to reduce costs and take a first step away from reactive unplanned maintenance.

The TPMSC also researched job postings for TPM coordinators, external TPM consultants, and Amoco technical experts for specific elements and tools, as well as suggested training and training material. All of this was assembled into a TPM Manual to assist the plants with developing their implementation plans.

TPM workshops
TPMSC realized there was a need for a wider base of TPM knowledge throughout the sector. As plants discussed TPM with their employees, inaccurate statements were causing resistance to the initiative. A three-day workshop was designed to teach the attendees the fundamentals of TPM, let them meet people who were already doing TPM, see TPM in action at a plant, learn about site implementations, and learn about "good places to start." It was hoped that the attendees could then return to their plants and accurately describe TPM and start to develop implementation plans.

By September 1998, five more workshops were held. In all a total of 325 people were trained, giving the sector the knowledge base it needed to move forward.

TPM implementation plans
Most plants now have TPM implementation plans. Several sites have appointed full time TPM coordinators, most have EIT, half are committed to installing PRIDE, and six have contracted with external resources and have done "Clean to Inspect" training. More than half has instituted RIME.

The TPMSC continues to meet every two to three weeks, usually via teleconference, to discuss progress. It advertises successes and assigned action items to investigate areas where progress is slow or lacking. A TPM activity scorecard is used to track progress and TPM metrics are being incorporated into computerized maintenance management system (CMMS) software. In 1999, the TPMSC plans to initiate a TPM Users Forum so people from across the sector can come together to share successes, work on common issues, and look for help in problem areas. The committee will make detailed assessments of the issues at each of these sites to develop the topics for the forum.

The TPMSC has asked MAN to further develop a vision and training for Asset Reliability/Reliability Engineering and for Maintenance Effectiveness/Planning and Scheduling. MAN commissioned these steering committees in August 1998. These visions are described in the section "Planning and Scheduling" and the section "Reliability Engineering."

Best practices implementation
MAN established the Best Practices Steering Committee (BPSC) to facilitate implementation of the best practices recommended by the Reliability and Pumps Subcommittees and to investigate new best practices for new issues. The BPSC charter ncludes:

• Place best practices in the "top drawer" of people who use them everyday. Make available expert maintenance resources to all levels of personnel. Provide a Web page search engine to obtain easy access to these practices and resources.
• Best practices and resources will be investigated and recommended to the plants by the BPSC. Each plant will be urged to evaluate the strategic fit of these practices and tools to their business. If applicable, they will perform a cost/benefit analysis to determine the priority of implementation.

Metrics and measurements
Because the plants used different computer systems and accounting practices, getting consistent unmanipulated data for measurements has been a major problem for MAN. With the impending start up a new company-wide system, MAN commissioned the Measurements Steering Committee (MSC) to develop standard measures. Its objectives are:

• Establish standard CMMS cost reports for all U.S. chemical plants.
• Consolidate MAN best practice scorecards for the purpose of measuring progress.
• Select and define key CMMS metrics to be used and recommend targets.
• Investigate reporting for non-CMMS and non-U.S. plants.

Effects of strategy
The most dramatic effect of MAN has been the downward trend in maintenance costs. Cost performance has closely followed the goals set forth in the three-tiered strategy and was reduced by 30 percent in two years. However, the improvements in reliability measures did not materialize as quickly as expected but their goals are still expected to be met.

Several of the activities sponsored by MAN should deliver additional benefits in 1999 and 2000. The Maintenance and Reliability Strategic Plans at each of the plants were completed in 1998 and should have a substantial impact as they are fully implemented. Most of the pump and reliability best practices have been migrated to the plants and are beginning to have an impact on performance. Plants will be implementing their TPM plans, and Reliability Engineering will be significantly upgraded in 1999.

Together these two initiatives will fundamentally change maintenance in Amoco's chemical sector from reactive to proactive and should dramatically impact the availability ratio and OAE for Amoco Chemical's manufacturing assets. MT

Edwin K. Jones is principal of Edwin K. Jones, P.E., Inc., 28 Quartz Mill Rd., Newark, DE 19711; (302) 234-3438; e-mail JJones1432@aol.com. Mark E. Lawrence is an internal maintenance and reliability consultant and is the coordinator for the Maintenance and Reliability Network (MRNet) at BPAmoco, WL4 Room 1794B, 200 Westlake Blvd., Houston, TX 77079-2682; (281) 560-4411; e-mail lawrenme@bp.com.

Manufacturing and production enterprises are under intense pressure to achieve maximum efficiency. The winners will be those that use their people and equipment assets most effectively. 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.

Optimized asset profiles
But what does an optimized asset look like? To start on the road to optimization, it is vital to first decide on the metrics to define the state of optimized asset utilization. Input must be solicited from the engineering, operations, reliability, maintenance, purchasing, safety, regulatory, and risk management departments within an organization to develop these Optimized Asset Profiles (OAP). Members of this multi-disciplinary team bring their own slices of information to the group to use in specifying the required performance/uptime measurements and maximum cost metrics for each service location.

The OAP must be closely aligned with business objectives. The use of financial benchmark metrics is essential for gaining senior management support. A comprehensive OAP considers the total life-time financial impact that any asset installed at a service location has on production, quality, safety, hazardous waste disposal, and costs of maintenance, conversion, inventory, insurance, purchasing, installation, overhaul, and final disposal.

In the power generation industry, OAP metrics for a steam turbine generator system might include:

• Asset kilowatt hour (kWh) output per year
• Asset operations cost (steam cost, control systems, and labor) per kWh
• Asset maintenance cost (preventive maintenance, health monitoring, spare parts, labor, major overhaul, and inventory) per kWh
• Asset utilities cost (feed water and auxiliary electrical costs) per kWh
• Asset insurance cost per kWh
• Asset abnormal situation cost (annualized estimate of unbudgeted safety risks and mechanical failure risks) per kWh

One paper producer is attempting to measure daily asset profitability for each paper machine. The equation to calculate this number is:

Daily Asset Profitability ($) = Income from Sellable Tons Produced Today  All Daily Costs

The following items must be considered in the daily costs:

• Cost of capital today
• Cost of raw materials for tons produced today
• Operations cost today
• Maintenance cost today
• Utilities cost today
• Insurance cost today
• Unplanned event risk cost today

Information required for optimization
Because business requirements change daily, the OAP also will change daily and need continuous refinement. Evaluating the current state of each process equipment asset versus its OAP also requires a constant feed of information. Performance, reliability, and asset health analysis is regularly needed in order for operations and maintenance to make adjustments to assets in order to align with the OAP.

An example of the need for continuously updated OAP data is the new deregulated power generation marketplace where power stations need to track the hourly cost of each kilowatt-hour of electricity they generate and compare it to the current market price. As the price of each kWh drops, the profitability of operating a higher-cost plant diminishes. If plants have implemented OAP metrics, management has access to the information it needs to make timely, optimum decisions.

Information paths that have an influence on optimized equipment asset utilization are illustrated in the accompanying diagram. Each data node on the optimized asset utilization star has important asset information which needs to be synchronized with other data nodes and merged into comprehensive asset information. The goal is to make timely and informed decisions to safely and profitably maximize the value of the respective assets.

The data domains that affect asset optimization include the following sectors:

• Engineering design and configuration management
• Operations planning
• Safety, regulatory, and insurance compliance
• Process execution
• Reliability planning and analysis
• Maintenance execution
• Asset health monitoring and analysis
• Inventory, MRO purchasing, and financial

Engineering design and configuration management
Design specifications for the process equipment and its function in a plant process or machine train are fundamental to asset management. Process and instrumentation diagrams, drawings, manuals, and revision histories for plant production processes and equipment functionality are obviously required to maximize the use of equipment assets. The configuration management data provide the understanding of the design of the process and the specification for the purchasing of the proper asset, which will meet the tolerances of the system without wasting energy resources.

Quantitative process and component-level risk assessments are also an important guide to understanding the most likely failure modes and the effects of these failures on the plant. These assessments can then guide the condition monitoring and nondestructive testing efforts. If a piece of equipment fails and a new one needs to be ordered, the design specification of the failed component is required to be certain that the new replacement asset meets all operational requirements.

Safety, regulatory, and insurance compliance
Understanding the safety issues related to the installation, operations, and maintenance of the equipment assets and production processes is also crucial. Safety concerns affect decisions on when to perform certain high-risk repairs and how long to operate an asset which is in critical need of repair.

Although the environmental regulatory requirements which govern the process (government-required pollution controls, hazardous material disposal, local noise regulations, etc.) may not vary on a daily basis, their proper interpretation is vital in making decisions related to operations and maintenance. An asset optimization team must understand these limits as it makes decisions to run, reduce loading, shut down, or schedule various maintenance tasks. An understanding of equipment repair and inspection regulations, such as regulatory pressure vessel codes, jurisdictional inspections for boilers and pressure vessels, and insurance-driven inspections, also is necessary.

Decisions regarding equipment assets can affect the availability, cost, terms, and conditions of purchasing insurance. A plant with a high asset failure history will normally be underwritten differently than one with a low frequency of significant failures. Understanding the business aspects of a process is essential to properly operating and maintaining it to an optimum level.

Operations planning
The asset optimization team needs to know the current, planned, and historical production and efficiency levels of the process line assets and have the ability to plan modifications to these levels. Demands for the current time period must be balanced with future needs. In some cases, over-production carries a penalty because of warehouse limitations or other business factors.

The incoming process inputs, fuel, electricity, steam, cooling water, etc., need to be reviewed for availability and quality. This is especially important where the process input varies widely. Scheduled downtime or turnaround times are also important information.

Many companies are turning to enterprise resource planning (ERP) systems as the core information technology for their operations. These systems can tie all aspects of the supply chain together, usually within a single data warehouse structure. Production planning and scheduling is one of the important functions of the ERP system.

Process execution
The operations execution plan with the actual scheduling of manufacturing personnel and production equipment is an important source of data. Understanding the backlogs or bottlenecks in the current production stream can assist in asset optimization.

The process control and monitoring systems are commonly called distributed control systems (DCS). These production control systems work in conjunction with local programmable logic controllers to control a process and monitor its current state. The actual production data on current load, speed, temperature, and other process variables are essential to understanding the current health of an asset.

Quality assurance stipulations, including compliance with ISO 90xx standards, are required in many industries. Data regarding the quality of manufactured goods during the production process should be accessible to the asset optimization team.

Reliability planning and analysis
Reliability planning is a vital step toward improving asset utilization. The process begins with the identification of appropriate business metrics, which then are communicated to the asset optimization team for tracking. Typical targets for improvement include unscheduled production downtime and slowtime, maintenance overtime costs, and the cost of spare parts.

After setting the targets for improvement, the next step involves the study of the criticality of all production assets related to their impact on future production requirements, safety, regulatory compliance, spare parts costs, and unplanned failure costs. The definition of what constitutes a failure for a piece of equipment is normally broadened to include speed and load reductions that impact production. Structured approaches such as reliability-centered maintenance (RCM) facilitate this study. The results of this study involve a customized maintenance plan for equipment assets, specifying an optimized combination of condition based maintenance (predictive maintenance), time/usage-based maintenance (preventive maintenance), and failure-based maintenance (reactive maintenance). The output of this analysis will shape reliability-driven maintenance execution and reliability feedback activities.

Reliability analysts also regularly review failures and near misses. After a failure occurs, reliability analysts perform structured root cause analysis to determine the causes of the failure, and modifications are then made in the reliability plan to prevent future occurrences. This might include monitoring additional factors that could have signaled impending failure. An enterprise asset reliability system captures the reliability plan and logs the failures. The system facilitates reliability studies using a variety of software tools.

Maintenance execution
Maintenance execution processes should be based on the output of the preceding reliability planning step. An enterprise asset management (EAM) system or computerized maintenance management system (CMMS) assists in planning and scheduling maintenance manpower and tools. Traditionally, the maintenance organization was defined by the number of major overhauls it could staff and manage, the overtime hours worked against budget, wrench time, control of backlog, and emergency response. Now, the targets are not activity-based, but focused on reliability metrics, increased production output, and expense controls.

Information related to maintenance execution is of great interest to the asset optimization team. Much of the required data relates to the asset nameplate data (manufacturer, model, and specification), maintenance tool availability, and problem histories. Work order planning, scheduling, and tracking are other data sources. This information is useful for knowing what steps have been completed and then specifying the future direction of maintenance activities.

Asset health monitoring and analysis
Most machine and process characteristics which affect quality, availability, capacity, safety, risk, and cost can be continually evaluated throughout the life of an asset. Because this information is a vital feedback loop to modify the current reliability plan based on real-time signals, enhanced reliability organizations are now focusing attention on finding signs of impending failure.

The actual conditions of an asset are conveyed through various sensors. Asset health monitoring, also called condition monitoring, measures critical areas from the reliability plan which were designated as requiring condition based maintenance. Monitoring techniques include vibration signature analysis, lubricating oil analysis, electrical circuit analysis, and thermographic imaging.

The current health of process equipment forms another important node of information for the asset optimization team. Data from operations, protection, on-line condition monitoring, and off-line condition monitoring systems are needed in order to synchronize the various signals for diagnosis and prognosis of asset health.

Best results are obtained by collectively evaluating a complementary mix of characteristics, selected to provide the most accurate measure of overall condition on the specific type of equipment. Specialized analysis tools such as operating deflection shape analysis, virtual sensor analysis, and transient data analysis assist the equipment analyst.

Operators do not normally desire the detailed raw monitoring data gathered by the various technologies, but do require an integrated health analysis, augmented with clear recommendations and forecasts. New enterprise asset health (EAH) systems combine all available health monitoring data to assist an analyst in recognizing abnormal patterns and diagnosing problems. These enterprise-wide systems contain a large database of all condition monitoring indicators and sophisticated multi-parameter alarming techniques. They also provide a platform for automated analysis and communication of health advisories and action requests to a process control system, an enterprise asset maintenance system, and an enterprise asset reliability system.

Inventory, MRO purchasing, and financial
The inventory of replacement assets and spare parts currently on site or in storage is important to the asset optimization equation. The asset optimization team requires information from this area in order to optimize the specification of additional spare equipment and parts. An oversupply of spares takes up costly storage space and ties up excess capital. However, too few spares could cause a lengthy production downtime.

The maintenance, repair, and operations (MRO) purchasing department houses information on preferred vendor arrangements and lead-time-to-delivery of replacement parts. This information avoids rush purchases and allows just-in-time delivery of parts. Cost savings from the use of preferred vendors are also facilitated.

Financial systems tie inventory, purchasing, labor, and materials costs together for management reporting. These systems normally need to be fed information on the utilization of the asset and the manpower utilized.

Data integration issues
Integration of data between various asset software systems is the key to providing timely information to decision-makers to safely and profitably manage equipment assets. The challenge of communicating with the same language between engineering design (CAD and parts library), operations planning (ERP), operations execution (DCS), reliability, maintenance execution (EAM and CMMS), asset health monitoring and analysis (EAH systems), inventory, purchasing, and financial systems is formidable.

Most software providers within each system group are accustomed to a single information and functional structure. Many lack awareness of the potential value of information from other sources and characteristics that must be accommodated to gain full value.

Today, most systems store their information in a proprietary database format with little concern for external program requests for maintenance histories, spare parts availability, and failure events. Process control systems generate archive log data, each with its own file format and structure. Complementary condition measurements are typically gathered by separate systems that cannot communicate or share data for collective comparison. The process is so difficult, expensive, and time-consuming that vital comparisons to confirm accurate status and to predict lifetime are seldom made.

The results of vibration analysis, oil analysis, and other crucial tests are not easily available to a complete machinery diagnostic/prognostic expert system, or to a maintenance system for maintenance or operations to be adjusted. Data from the process control system are not readily available to a vibration condition monitoring system to analyze exception events. The needed link between engineering, enterprise resource planning, process control, maintenance management, and asset health systems has never materialized for many plants and is thwarting the promise of optimum asset utilization.

The value of integration The value of integrating asset systems can be seen from documented results at the largest power-producing utility in the United States, Southern Co. In a 2-year integrated monitoring and maintenance pilot system across five plants, the company has documented more than 100 instances in which information available from equipment health analysis was used to influence maintenance decisions.

During slightly over 1 year, potential savings and avoided costs of about $1 million resulted from deferring planned maintenance on healthy machines and from identifying problems in time to schedule repairs and avoid equipment failures.

In one case, time-based preventive maintenance was eliminated for major plant fans. Technicians now rely on vibration, oil, motor current, and temperature condition based monitoring techniques to determine which fans, gearboxes, and motors to maintain. In one planned plant outage, this resulted in savings of 340 man-hours because the fans did not have to be individually inspected for potential repairs. This reduced maintenance hours associated with these fans by 54 percent.

Open path to integration
Industrial users who desire to integrate their systems have three choices: attempt to buy all software from one vendor, launch in-house integration efforts, or utilize industry-standard open system interfaces from equipment software providers.

Arguably, there is not one software provider that provides a complete system for optimum asset management today. Some companies offer a much broader array of software with a single database platform that will operate with each other.

Today, users who want to provide interoperability between their plant information systems seem to be left with little choice except to hire a system integration company to piece the various systems together. This is usually cost-prohibitive and requires regular updates to the glue software any time one vendor's database format changes.

The cost of developing custom links between various systems can be extremely high and the cost of maintaining each of these links has been estimated at an annual rate of 40 percent of the initial development effort. For example, an $800,000 integration effort will require an on-going annual cost of $320,000 for software maintenance and upgrades.

A better long-term strategy is to purchase systems that utilize industry-standard open system interfaces. The benefits include:

• Lower cost for electronic exchange of vital information between proprietary systems
• Freedom to assemble plug-and-play information systems from multi-source best-for-application components
• Assurance of continuing least-cost upward growth and expansion to gain maximum advantages from improvements in knowledge, technology, practice, performance, and product features
• Increased value through maximum use of economical high performance consumer components with proven reliability, multi-source support, and rapid evolution to meet requirements of larger markets
• Reduced need for costly integration software
• Reduced integration software maintenance costs

Partners for integration
Currently, there are four organizations that are addressing industrial standards for system integration: International Standards Organization (ISO), Open Applications Group (OSG), OPC Foundation, and Machinery Information Management Open Systems Alliance (MIMOSA). In a system integration project, a company should review the specifications from these groups to see if an open protocol can be utilized. An overview is provided in the section Organizations for Open Systems Standards. The choice of suppliers who will partner with a plant in supporting its goals for optimizing the utilization of its assets is critical. Plants may wish to avoid software systems that utilize proprietary closed databases and architectures. A plant should consider the following questions before purchasing manufacturing technology systems:

• Does the supplier have a history of providing systems that are open and utilize industry standards wherever possible?
• Do the modules I purchase from this supplier integrate among themselves, possibly using different databases and architectures?
• Are the products I purchase certified as compliant with current industry standards?
• Are the software modules I am purchasing from this vendor costly to interface to other systems?

Plants are being forced to achieve higher profitability. To increase a plant's profitability, the optimized utilization of equipment assets is essential. To perform this optimization, plants require timely access to integrated data. The cost of this integration is normally a barrier to many plants moving to this optimization level. The use of open systems is lowering this barrier and allowing plants to begin to make strategic use of vital information. Manufacturing companies who commit to partnering with suppliers who provide systems that support open integration architectures will speed down the road to optimizing their valuable equipment assets. MT

Ken Bever, who serves on the board of directors of MIMOSA, is strategic project manager, Advanced Enterprise Systems Group, ENTEK IRD International, 1700 Edison Dr., Milford, OH 45150; telephone (513) 576-6151; e-mail kbever@entek.com; Internet www.entek.com