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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Paper or voice dictation method

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

Pen computer with IR database

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

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

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

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

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

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

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

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

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

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

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

Robert C. Baldwin, CMRP, Editor

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

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

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

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

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

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

Robert M. Williamson, Strategic Work Systems, Inc.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

(R = e^-tl)

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

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

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

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

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

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

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

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

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

Equation 1. Energy demand

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

Equation 2. Energy demand between electric motors

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

MotorMaster+ Version 3.0 also includes the following features:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The key concepts that the system addresses:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The benefits of good planning

The benefits of good planning fall into several major categories:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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