Archive | April, 1997

613

3:14 am
April 2, 1997
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Beyond Reliability To Profitability

In the modern industrial environment, equipment reliability and reliability improvement must offer solid financial justification. Profit-centered maintenance shows how to meet the challenge.

Financial considerations, namely profitability, drive most aspects of modern process and manufacturing operations. The premise of profitability is the basis for profit-centered maintenance (PCM), a continuous process of reliability and administrative improvement and optimization. It requires a culture change to make decisions based on value, to re-engineer the administration of maintenance, and to enable the people performing and administering maintenance to make the most of available maintenance information technology.

Profit-Centered Maintenance Task SelectionThe key steps in the process are optimizing the physical function of maintenance and resolving recurring maintenance problems to reduce the need for maintenance. PCM is more than just an attitude–it is a path to profitability.

In the past, maintenance program improvements have been limited to the realm of the maintenance practitioner. Maintenance improvements have not been major business issues. Most executive and financial managers are unaware of the added value and profitability inherent in an optimized maintenance program. This attitude will change as companies increase efforts to enhance their competitive advantage.

Reliability and profitability
Most managers view plant machinery reliability as the capability to operate in its prescribed manner. This capability is the end product of design, manufacture, operation, and maintenance. Reliability is not automatic nor is it cheap. In consideration of individual equipment, its residual capability to operate beyond its nominal capability can be compared to money in a shoe box–once spent it is gone. Plantwide, reliability is frequently manifested by expensive equipment redundancy that all too often proves ineffective.

To compound the assault on competitiveness, current plant maintenance people strive to meet goals based on generalized, outdated maintenance benchmarks. To meet competitive pressures in the future, maintenance must become good at improving plant availability and asset utilization.

Certain discretionary actions, usually considered necessary to force short-term availability or to maintain a service level or production run, can lessen equipment reliability. For example, consider the continued operation of a critical machine with a known high bearing vibration level. It is understood that replacing a bearing is less costly than repairing a seized shaft. When machinery is operated to a point that wear rates increase, reliability is correspondingly degraded. Whether or not this action causes permanent degradation and required derating, repair, or replacement, repeating this action will eventually lead to a shorter life and premature capital expenditures. Furthermore, when equipment is operated extensively beyond its limits, the result may be failure.

The driving force behind occasional abnormal operations is the need to continue the revenue stream or to obtain profits, certainly not to wear out equipment faster. Profit needs must be faced square on, and managers must find opportunities for increasing profitability through reliability investments and decisions based on value. It becomes necessary to apply business methods to smaller investment decisions.

A firm basis focused on return on investment for reliability costs allows profitability decisions to fall into place. Investments for added reliability such as purchasing more robust equipment, requiring better installation, and insisting on enlightened maintenance practices become justifiable with a solid financial basis. Pressures to revert to reactive or breakdown maintenance can be countered with a return-on-investment analysis that gathers support from senior executives and financial management. Maintenance decisions and approach are thus centered on contributions to profitability, or on profit-centered maintenance.

PCM begins with the premise that financial considerations, namely profitability, drive most aspects of modern process and manufacturing operations. In the modern industrial environment, equipment reliability and reliability improvement must have a solid financial justification. If not, an equipment manufacturer offering only significantly improved reliability at a premium price will find few buyers because business decisions may not support a high price for reliability only.

PCM is a continuum of optimizing the physical function of maintenance, improving asset reliability, and improving maintenance administration. The major activity required for its implementation is optimization of the maintenance function. Once that is done, the continuous improvement loop may perform only the fine tuning of specific maintenance tasks.

The principal components of PCM are

  • Insistence on maximum value over least costs
  • Optimization of the physical function of maintenance to achieve the blend of condition-based, time-based, and run-to-failure maintenance that returns maximum value
  • Reduction of the need for maintenance to permanently reduce maintenance cost
  • Re-engineering of maintenance administration, eliminating non-value-adding activities and waste
  • Enabling the maintenance workforce to extract maximum value from maintenance information management systems.

Maximum value over least cost
Insisting on maximum value over least costs is a long-term commitment that belongs in the culture change category. It is simple to say and superficially easy to understand. Establishing the concept as the normal way of doing business is the hard part.

Return on investment and net present value are two conventional ways to calculate the relative value of projects or decisions to objectively determine maximum value. The harder issue is to frame operational issues and schedule-impacting maintenance decisions in value terms. The typical maintenance organization, trained to think of minimizing costs, may find the concept of maximum value equivalent to the more familiar least costs method. It is not the same, and the best way to appreciate the difference is to recognize that maximum value achieves its payback over a longer period of time than usually considered.

Hypothetically, the high-level vibration condition discussed previously could be repaired right away with obvious maintenance costs and production loss. This action would be much less expensive than letting the bearing run to failure, increasing the damage and the corrective maintenance cost.

However, in this example the bearing failure could have been caused by imperfect alignment resulting from errors made by the alignment technician conducting a reverse dial indicator alignment procedure. Had the technician been better trained, the alignment might have been performed with minimal error, reducing the failure-causing forces on the bearing.

Optimizing physical maintenance
Maintenance personnel recognize that maximum value in maintenance has generally been obtained from a condition-based program. PCM also includes a complementary condition-directed element, a time-based element, and in rare situations when best served by it, a run-to-failure element. The optimizing or blending of maintenance is driven by the quality and quantity of existing maintenance programs. It uses maintenance effectiveness assessments, reliability-centered maintenance (failure modes and effects analyses), and root cause analyses as tools. The main product from optimization is a maintenance program based on maximum value.

A method for optimizing maintenance processes is outlined in the flow chart, “Profit-Centered Maintenance Task Selection.” Most existing plant applications take the path to the left, through the maintenance effectiveness assessment block, the blending review of existing preventive maintenance items, and the option for root cause analysis, and then through the sorting process resulting in the task that provides the maximum value. This process results in an optimized program that includes condition-based and time-based tasks that are applicable and effective in preventing or mitigating known failure modes.

The repair part of maintenance is not included in optimization. However, repair efforts benefit from greater investigative capabilities developed within the maintenance organization, and often show in advance the scope of damage. In time, if optimized tasks work as prescribed, repairs should be infrequent and of minimal significance.

Reducing the need for maintenance
The only way to permanently reduce maintenance costs is to reduce the need for maintenance. Reducing the need for maintenance comes from diligent efforts to improve materials, designs, maintainability, and operations. Here are some examples:

  • Change materials where possible to reduce the strength of a galvanic cell in the seal gland, reducing corrosion and the need for maintenance
  • Install permanently mounted vibration sensors to monitor the gearboxes on the cooling tower fans without endangering personnel or missing the opportunity to monitor gearbox degradation
  • Provide bearing-specific lubrication oil sampling points to make possible bearing-specific physical, chemical, and wear particle analyses for the turbine lubrication oil system.
  • Often, the opportunity to reduce the need for maintenance arises from root cause analysis. This analysis does not have to conform to a particular format. A curious inquiry by a knowledgeable person can often suffice.
Cost Of Maintenance

Profit-centered maintenance can decrease maintenance costs significantly.

Re-engineering maintenance administration
Most business processes within the enterprises of competitive leaders have been re-engineered to improve cost effectiveness, but the administration of maintenance probably has not. Re-engineering is defined as the fundamental rethinking and radical redesign of business processes to achieve dramatic improvements in critical, contemporary measures of performance. In other words, start over, reinvent the administration of maintenance, throw out the old, and bring in the new. The need for regulatory compliance requires care and extra communications to ensure legal responsibilities are met.

Once a company is engaged in a re-engineering effort, strong candidate characteristics for elimination include compartmentalization, excessive hand-offs, and redundant approvals. Attributes to be streamlined include coordination, communications, and supervisory functions. Attributes to be retained include the qualities of ownership, responsibility, and accountability.

To enable maintenance personnel, hardware and software and training are required. The maintenance information system must be modernized to provide information, not just disconnected data, to maintenance technicians and support people where and when they need it. This directive means not only sufficient computer resources, but also reworking of the manner in which computers process maintenance data and present it as information.

Management investment
Over the years, the electric power industry has generally accepted the fact that moving from breakdown to predictive maintenance saves money. A 1986 study by the Electric Power Research Institute showing plant maintenance cost per total horsepower per year has become so widespread an indicator that it has achieved status as a standard. It is used in many industries to demonstrate the relative improvement of shifting maintenance from breakdown mode to predictive. The chart, “Cost of Maintenance,” shows the study’s original results with a projection for anticipated savings accruing from implementation of PCM.

Maintenance is changing from a concept focused on how well a process or an individual machine works to a more complex concern with safety, quality, commercial availability, and unit cost efficiency. Computerized maintenance management systems are changing from programs constructed to control the worker to integrated maintenance information systems that support self-managing maintenance technicians. For senior managers and maintenance personnel alike to accept these changes requires better communications than presently exist. It is important for both sectors to communicate in terms the other understands. The maintenance practitioner must learn to prepare reports in relevant business terms. Nontechnical senior management must learn enough technical terms to ask relevant questions and to understand the answers.

Embracing PCM is tantamount to committing to culture change. No successful culture change will occur without thorough involvement by senior management. You cannot change the culture without top-down leadership. Although it is said that business is constantly changing, the culture of an individual workplace seldom accepts radical change. Game theory in business applications shows that a reluctance to change leads to loss of market share. Successful organizations are willing to both change and manage the process of change.

Senior managers will best appreciate quality and costs. The concept of “trade-ons” where higher quality and lower costs both occur fits nicely with PCM’s benefits and results.

Implementing PCM
At this point, industry executives may feel that they have a maintenance program that is not realizing its potential, or they may have dismissed this whole approach, or most likely, they may realize that they do not really know if or how their maintenance function contributes to company profitability. Managers in the unsure category must conduct an orderly examination of maintenance and determine its cost effectiveness.

The assessment will involve examining records, conducting interviews, and observing maintenance operations. The record of the assessment and the recommendations emanating from it must be based on objective determinations and factual conclusions. When done well, this assessment can form the basis for budgetary input, a business plan for the maintenance department, or justification of company investment in a sophisticated maintenance program.

Some smart industry executives may decide that PCM does not apply to them because they cannot establish maintenance as a profit center in their accounting system. Maintenance as a profit center is more an attitude than an accounting change. How the accounting department treats money spent in the management of assets is best left to management. It is hoped that the accounting department will recognize increases in profitability when they occur.

In the initial logic diagram describing the selection of PCM tasks, the path through the existing program will usually be the choice. For new plants, plants with new systems, or plants with old systems without any substantive program, the reliability-centered maintenance option may provide better results.

When working through the task selection flow chart, most users will need to conduct the maintenance effectiveness assessment to determine the status of existing programs. The key step is to evaluate the effectiveness of existing preventive maintenance tasks in the task optimization step. Those tasks that should be changed will be subjected to the test to see which condition-monitoring, condition-directed, or time-directed task is dictated. Should no condition or time-based tasks prove both applicable and effective, a cost-benefits analysis is then conducted to document the rationale for a breakdown task.

During the implementation phase, an unresolved recurring maintenance problem may be recognized. This problem will need root cause analysis to determine permanent corrective action or redesign. Root cause analyses of various complexities are frequently conducted. It is important for analysis to identify a confident solution. Good documentation of what took place, the results, and the rationale are all important for resolution of future issues.

Other than conducting the full maintenance effectiveness assessment, management can take a quick test to determine if the maintenance program is profit centered. It involves satisfying the following criteria:

  • Maintenance decisions stress maximum value, not least costs.
  • Maintenance tasks include a blend of condition-based, time-based, and breakdown tasks. Machinery does not fail without its condition being recognized.
  • Root causes of recurring maintenance tasks are determined and effective action is taken to preclude recurrence.
  • Administration of maintenance is a lean and trim operation without excessive non-value-adding activities or waste.
  • Maintenance personnel get full measure from maintenance information systems and keep technologically current.
  • Plant and company enjoy increased profitability that stems from changes in maintenance practices.

It is not enough to stress just reliability. There is a continuing need for profitability. Increased pressures from competition mean that every effort to enhance profitability must be carefully examined. Maintenance offers that opportunity, and the solution is PCM.

Full benefits come from complete implementation, which will optimize the physical function of maintenance, re-engineer maintenance administration, resolve recurring maintenance problems to reduce the need for maintenance, and enable maintenance personnel to extract full measure from the developing integrated machinery information systems. In a nutshell, it is to obtain maximum value in asset management instead of accepting least costs in maintenance. MT


Tom Bond provides consulting services in management and predictive maintenance through Thomas Bond Consultants, 4259 Niagara Ave., San Diego, CA 92107-2909; (619) 226-2244; e-mail tbond@mimosa.com.

John Mitchell is a consultant at 31882 Paseo Alto Plano, San Juan Capistrano, CA 92675; (714) 496-0873; e-mail jsmitchell@worldnet.att.net. Both authors are part of the Machinery Information Management Open Systems Alliance (MIMOSA), http://www.hsb.com/pcm/mimosa/mimosa.html.

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143

12:15 am
April 2, 1997
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A New Approach to Maintaining Process Control Field Devices

Adding microprocessors to field instruments has transformed them into data acquisition systems and transmission terminals. Now technicians can use well-designed software to see what is happening inside plant instrumentation.

 

asset_management

When asset management software is used, devices that need service can signal the operator or maintenance shop before they fail, lowering maintenance or repair costs and reducing the risk of unscheduled shutdown.

Instrumentation technicians responsible for reliable operation of thousands of field devices commonly receive calls from operators who are having trouble controlling a piece of production equipment, a reactor for example. If the plant is equipped with state-of-the-art asset management software, the technician can quickly determine which devices are associated with that reactor and which ones could be causing problems.

 

Rather than going into the plant, the technician can evaluate each smart device from a personal computer in the instrument shop. For example, a quick computer check of the condition of each field device serving that reactor might reveal a travel deviation alert from one control valve, indicating a significant difference between the valve set point and its actual position–a situation requiring attention. The technician is spared long hours of checking out individual devices on the plant floor and knows exactly what must be done to correct the problem.

Although the poorly functioning valve in the reactor is hypothetical, the solution to this common problem is not. Up to 60 percent of instrument maintenance labor dollars are spent on devices where no problem exists or for routine checks to verify the condition of properly functioning devices. These requests often occur because an operator has no means of checking on the health and validity of field instrumentation and therefore calls the instrument shop when a problem is suspected. The most time-consuming and expensive service calls are those that conclude with no problem found.

Now, instrumentation technicians have a way to see what is happening inside plant instrumentation by using well-designed software in conjunction with intelligent field devices and new standard communications. These technologies allow technicians to

  • Make sure field devices deliver optimum performance
  • Use predictive maintenance to maximize service and repair resources
  • Perform configurations and calibrations in half the normal time
  • Document maintenance as required by industry regulators.

From a broader perspective, the integration and use of information acquired from intelligent field devices eliminates unexpected shutdowns, reduces downtime, and improves overall equipment performance.

Intelligent field devices
The process control system is designed for tight control of valves, motors, heaters, etc., in real time to manage feed stocks and make quality products. However, to increase the reliability and maintainability of plant instrumentation and process equipment and to lower the mean time between failures and time to accomplish repairs, a vast amount of information is needed about the condition and status of field equipment. The increase in smart instruments throughout the process industry makes it both practical and economical to use all the information they generate. It is estimated that 30 times more information is available from smart instruments than the simple variables required for process control.

Consider a smart pressure transmitter. Beyond providing basic pressure data, it can produce information relative to an overpressure condition (which can lead to inaccurate readings), an overtemperature condition (which can cause premature failure), a loss of signal, a stuck signal, and more. In the case of a control valve, the number of times the valve has cycled is a key indicator of how much work it has done and can be used in predicting its useful life. As the reactor example mentioned previously suggests, the internal position of a valve stem versus where it is supposed to be is critically important to the reliable operation of that piece of equipment. Smart valves routinely provide this kind of information.

The accuracy of field measurements and the reliability of field instrumentation are influenced by internal conditions that can be reported only by intelligent devices, and those conditions can have a direct impact on the availability or reliability of the process itself. Demand to make use of such data is growing. The acquired information must be made available well beyond the process control system.

Communicating the data
Automation architectures are evolving to deliver information from intelligent field devices, acting as information servers, around the control system to computers where the information can be used for diagnostic and maintenance purposes, for reliability analysis, for purchasing and inventory control systems, and for the overall management of plant assets.

General-purpose field communications protocols capable of transmitting large volumes of information for these purposes are currently in use. Today, the Highway Addressable Remote Transducer (HART) protocol offers the broadest range of user benefits and is supported by a wide range of vendors. Unlike proprietary communications technologies that lock users into field devices from a single manufacturer, the HART protocol is an open communications standard that works alongside any control system without interrupting the flow of process data.

Whereas HART transmits both analog and digital signals, the emerging Foundation Fieldbus protocol will be used with all-digital systems. Profibus is another new protocol under development. These sophisticated protocols are capable of carrying complex messages. Their use enables technicians to examine an instrument’s self-diagnostics and also run extensive diagnostics programs on each device.

Using the information
For field data to be turned into useful knowledge, a reliable method of receiving, processing, and presenting it is required. Maintenance personnel require information on the condition of equipment, while operations personnel want other information and purchasing or inventory control requires something different. Each group needs information tailored to specific requirements. For example, the enhancement most desired by maintenance supervisors is seamless access to maintenance-related data. Advanced software applications are performing that function now.

Monitoring the intelligent devices installed in a plant and viewing their self-diagnostics probably are the most common functions of the instrumentation technician. Most smart instruments provide extensive information about their own health. Access to on-line device status provides a way to monitor and ensure proper device performance. The technician calls up the information device by device to see if any faults are flagged.

Automatic alert monitoring also is available to automatically scan devices on a user-determined schedule. If device problems exist, the information is posted to an alert monitor list. If no specific problems are found but something is suspected, it may be possible, depending on the software package, to use on-demand diagnostics. Certain operating parameters may be changed slightly to see if the device responds. For example, safety valves might be moved slightly to determine that the valve is not stuck and actuator pressures are sufficient to move the valve.

Automatic scanning of devices requires a higher level of sophistication. Such scans may uncover devices that need immediate attention, or they might generate lists of devices due for calibration. Some software is designed to interface with computerized maintenance management systems that track maintenance schedules and alert technicians when maintenance is due. Sophisticated software that identifies a need for instrument calibration combined with intelligent calibrators may also be able to automatically perform configurations and calibrations in a fraction of the time required for conventional calibrations.

Advanced, maintenance-oriented software permits maximum use of the information transmitted through a general-purpose protocol. The more advanced software receives the data, organizes it into open databases, and makes it available to other applications within the organization. Predictive maintenance is one of the key attributes of such systems. When the software makes a prediction about the expected service life of any piece of equipment, knowledgeable decisions can be made as to when repair or replacement will cause the least disruption to production.

Decisions such as run until failure, continue to run at reduced load, run until a scheduled shutdown, or repair immediately are based on highly reliable information, including the importance of the piece of equipment to the process. This approach helps focus limited resources on problems that warrant attention rather than wasting time on devices expected to continue working properly. In this way, instruments and control systems can be maintained in a high state of continued reliability.

What to look for
It is not difficult to obtain a communications and software package capable of accessing information generated by smart instruments, but not all software is created equal. First, potential buyers should be sure that nothing done with this ancillary information degrades the performance of the control system. Users of heavily loaded control systems may want to reserve all remaining control system capacity for future process control needs. Solutions available from various vendors of HART-compatible devices will carry the information through multiplexing, through intrinsic safety barrier panels, and through intelligent termination panels where information can be accessed by computers without using control system communications and computation resources.

However, data acquisition by itself does not provide the cost and time-saving benefits most maintenance managers are seeking. A flexible, maintenance-oriented, modular software platform that is both expandable and scalable must be found. Such software can provide access to a single device or to highly integrated client/server solutions for large multi-instrument plants.

In addition, the software should use device descriptions (DD), which are essentially files of field device attributes residing in the host application. The DD is essential to the interoperability of devices, allowing users to choose those that best meet their needs, regardless of manufacturer. As each new device is introduced, the description of attributes and capabilities is loaded into the host, providing complete data about each device in the plant. The DD technology is fundamental to the HART and Fieldbus protocols.

To be most useful, the software must accommodate the broadest range of field devices. It should support virtually all current HART and future Fieldbus devices, not just those manufactured by one company. In other words, the company should choose a technology to accommodate the widest range of applications needed to meet current and future plant and business needs. A number of good solutions are available. However, many tend to focus on a specific vendor’s field instrumentation, which does not generally solve the problem of the large multi-instrument user.

Finally, it must be possible to integrate data from the field management software with any computerized maintenance management system the plant is running. An integrated solution is essential to realize the greatest value from information derived from intelligent field devices, transported through a state-of-the-art data highway, and processed in sophisticated, maintenance-oriented software.

Estimates show that one-third of all dollars spent on maintenance are wasted because of unnecessary work or ineffective practices. This trend can be reversed through the application of information generated by intelligent field devices and acceptance of the concept of predictive maintenance. The result can be a significant contribution to a plant’s profitability.

It is not necessary to totally restructure maintenance practices. A plant can start small and expand the use of process floor information as needs dictate and budgets allow. The key is to begin building a database from the smart devices now in operation and expand the use of the available information as the number of such devices grows. A scalable and expandable platform can grow into a plantwide system that supports the reliability and maintainability of all field instrumentation. MT


Thomas Wallace is program manager, asset management solutions, at Fisher-Rosemount Systems, Inc., 12000 Portland Ave., S., Burnsville, MN 55337; (612) 895-2380; e-mail tomwall@frmail.frco.com.

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180

12:15 am
April 2, 1997
Print Friendly

A New Approach to Maintaining Process Control Field Devices

Adding microprocessors to field instruments has transformed them into data acquisition systems and transmission terminals. Now technicians can use well-designed software to see what is happening inside plant instrumentation.

asset_management

When asset management software is used, devices that need service can signal the operator or maintenance shop before they fail, lowering maintenance or repair costs and reducing the risk of unscheduled shutdown.

Instrumentation technicians responsible for reliable operation of thousands of field devices commonly receive calls from operators who are having trouble controlling a piece of production equipment, a reactor for example. If the plant is equipped with state-of-the-art asset management software, the technician can quickly determine which devices are associated with that reactor and which ones could be causing problems.

Rather than going into the plant, the technician can evaluate each smart device from a personal computer in the instrument shop. For example, a quick computer check of the condition of each field device serving that reactor might reveal a travel deviation alert from one control valve, indicating a significant difference between the valve set point and its actual position–a situation requiring attention. The technician is spared long hours of checking out individual devices on the plant floor and knows exactly what must be done to correct the problem.

Although the poorly functioning valve in the reactor is hypothetical, the solution to this common problem is not. Up to 60 percent of instrument maintenance labor dollars are spent on devices where no problem exists or for routine checks to verify the condition of properly functioning devices. These requests often occur because an operator has no means of checking on the health and validity of field instrumentation and therefore calls the instrument shop when a problem is suspected. The most time-consuming and expensive service calls are those that conclude with no problem found.

Now, instrumentation technicians have a way to see what is happening inside plant instrumentation by using well-designed software in conjunction with intelligent field devices and new standard communications. These technologies allow technicians to

  • Make sure field devices deliver optimum performance
  • Use predictive maintenance to maximize service and repair resources
  • Perform configurations and calibrations in half the normal time
  • Document maintenance as required by industry regulators.

From a broader perspective, the integration and use of information acquired from intelligent field devices eliminates unexpected shutdowns, reduces downtime, and improves overall equipment performance.

Intelligent field devices
The process control system is designed for tight control of valves, motors, heaters, etc., in real time to manage feed stocks and make quality products. However, to increase the reliability and maintainability of plant instrumentation and process equipment and to lower the mean time between failures and time to accomplish repairs, a vast amount of information is needed about the condition and status of field equipment. The increase in smart instruments throughout the process industry makes it both practical and economical to use all the information they generate. It is estimated that 30 times more information is available from smart instruments than the simple variables required for process control.

Consider a smart pressure transmitter. Beyond providing basic pressure data, it can produce information relative to an overpressure condition (which can lead to inaccurate readings), an overtemperature condition (which can cause premature failure), a loss of signal, a stuck signal, and more. In the case of a control valve, the number of times the valve has cycled is a key indicator of how much work it has done and can be used in predicting its useful life. As the reactor example mentioned previously suggests, the internal position of a valve stem versus where it is supposed to be is critically important to the reliable operation of that piece of equipment. Smart valves routinely provide this kind of information.

The accuracy of field measurements and the reliability of field instrumentation are influenced by internal conditions that can be reported only by intelligent devices, and those conditions can have a direct impact on the availability or reliability of the process itself. Demand to make use of such data is growing. The acquired information must be made available well beyond the process control system.

Communicating the data
Automation architectures are evolving to deliver information from intelligent field devices, acting as information servers, around the control system to computers where the information can be used for diagnostic and maintenance purposes, for reliability analysis, for purchasing and inventory control systems, and for the overall management of plant assets.

General-purpose field communications protocols capable of transmitting large volumes of information for these purposes are currently in use. Today, the Highway Addressable Remote Transducer (HART) protocol offers the broadest range of user benefits and is supported by a wide range of vendors. Unlike proprietary communications technologies that lock users into field devices from a single manufacturer, the HART protocol is an open communications standard that works alongside any control system without interrupting the flow of process data.

Whereas HART transmits both analog and digital signals, the emerging Foundation Fieldbus protocol will be used with all-digital systems. Profibus is another new protocol under development. These sophisticated protocols are capable of carrying complex messages. Their use enables technicians to examine an instrument’s self-diagnostics and also run extensive diagnostics programs on each device.

Using the information
For field data to be turned into useful knowledge, a reliable method of receiving, processing, and presenting it is required. Maintenance personnel require information on the condition of equipment, while operations personnel want other information and purchasing or inventory control requires something different. Each group needs information tailored to specific requirements. For example, the enhancement most desired by maintenance supervisors is seamless access to maintenance-related data. Advanced software applications are performing that function now.

Monitoring the intelligent devices installed in a plant and viewing their self-diagnostics probably are the most common functions of the instrumentation technician. Most smart instruments provide extensive information about their own health. Access to on-line device status provides a way to monitor and ensure proper device performance. The technician calls up the information device by device to see if any faults are flagged.

Automatic alert monitoring also is available to automatically scan devices on a user-determined schedule. If device problems exist, the information is posted to an alert monitor list. If no specific problems are found but something is suspected, it may be possible, depending on the software package, to use on-demand diagnostics. Certain operating parameters may be changed slightly to see if the device responds. For example, safety valves might be moved slightly to determine that the valve is not stuck and actuator pressures are sufficient to move the valve.

Automatic scanning of devices requires a higher level of sophistication. Such scans may uncover devices that need immediate attention, or they might generate lists of devices due for calibration. Some software is designed to interface with computerized maintenance management systems that track maintenance schedules and alert technicians when maintenance is due. Sophisticated software that identifies a need for instrument calibration combined with intelligent calibrators may also be able to automatically perform configurations and calibrations in a fraction of the time required for conventional calibrations.

Advanced, maintenance-oriented software permits maximum use of the information transmitted through a general-purpose protocol. The more advanced software receives the data, organizes it into open databases, and makes it available to other applications within the organization. Predictive maintenance is one of the key attributes of such systems. When the software makes a prediction about the expected service life of any piece of equipment, knowledgeable decisions can be made as to when repair or replacement will cause the least disruption to production.

Decisions such as run until failure, continue to run at reduced load, run until a scheduled shutdown, or repair immediately are based on highly reliable information, including the importance of the piece of equipment to the process. This approach helps focus limited resources on problems that warrant attention rather than wasting time on devices expected to continue working properly. In this way, instruments and control systems can be maintained in a high state of continued reliability.

What to look for
It is not difficult to obtain a communications and software package capable of accessing information generated by smart instruments, but not all software is created equal. First, potential buyers should be sure that nothing done with this ancillary information degrades the performance of the control system. Users of heavily loaded control systems may want to reserve all remaining control system capacity for future process control needs. Solutions available from various vendors of HART-compatible devices will carry the information through multiplexing, through intrinsic safety barrier panels, and through intelligent termination panels where information can be accessed by computers without using control system communications and computation resources.

However, data acquisition by itself does not provide the cost and time-saving benefits most maintenance managers are seeking. A flexible, maintenance-oriented, modular software platform that is both expandable and scalable must be found. Such software can provide access to a single device or to highly integrated client/server solutions for large multi-instrument plants.

In addition, the software should use device descriptions (DD), which are essentially files of field device attributes residing in the host application. The DD is essential to the interoperability of devices, allowing users to choose those that best meet their needs, regardless of manufacturer. As each new device is introduced, the description of attributes and capabilities is loaded into the host, providing complete data about each device in the plant. The DD technology is fundamental to the HART and Fieldbus protocols.

To be most useful, the software must accommodate the broadest range of field devices. It should support virtually all current HART and future Fieldbus devices, not just those manufactured by one company. In other words, the company should choose a technology to accommodate the widest range of applications needed to meet current and future plant and business needs. A number of good solutions are available. However, many tend to focus on a specific vendor’s field instrumentation, which does not generally solve the problem of the large multi-instrument user.

Finally, it must be possible to integrate data from the field management software with any computerized maintenance management system the plant is running. An integrated solution is essential to realize the greatest value from information derived from intelligent field devices, transported through a state-of-the-art data highway, and processed in sophisticated, maintenance-oriented software.

Estimates show that one-third of all dollars spent on maintenance are wasted because of unnecessary work or ineffective practices. This trend can be reversed through the application of information generated by intelligent field devices and acceptance of the concept of predictive maintenance. The result can be a significant contribution to a plant’s profitability.

It is not necessary to totally restructure maintenance practices. A plant can start small and expand the use of process floor information as needs dictate and budgets allow. The key is to begin building a database from the smart devices now in operation and expand the use of the available information as the number of such devices grows. A scalable and expandable platform can grow into a plantwide system that supports the reliability and maintainability of all field instrumentation. MT


Thomas Wallace is program manager, asset management solutions, at Fisher-Rosemount Systems, Inc., 12000 Portland Ave., S., Burnsville, MN 55337; (612) 895-2380; e-mail tomwall@frmail.frco.com.

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198

9:50 pm
April 1, 1997
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Maintenance Training into the 21st Century

Old tried-and-true training methods often fail to achieve the desired results in today’s maintenance and reliability improvement environment. Much has changed in recent years because of workforce in transition, skills shortages, new equipment technologies, downsizing, and cost cutting. The next logical step is to fundamentally rethink our training approaches. Accelerating the maintenance and reliability learning process is essential for the success of modern industry.

New and renewed organizations often include a smaller workforce, fewer, if any, middle managers, new job designs, overhauled compensation and reward programs, delegated responsibilities, empowered work groups, and a relentless focus on results. Many of the old ways of working have changed, often not by choice but rather out of the need to survive in a new world order, and in a new work order. In this new work order, training methods must be transformed by taking into account how adults best learn, how to accelerate the learning process, how equipment works, and how to improve performance.

Here are four steps to improving training and learning effectiveness and efficiency.

First, adults learn best through applied learning methods that are immediately applicable to their needs and interests. Classroom or large group training classes are the most ineffective and inefficient ways for adults to learn. In general, every person in today’s job roles has different learning needs. Although adults may require the same skills, they enter the learning environment with vastly different experiences, aptitudes, and abilities. Here are a few key points to help adults learn maintenance and reliability improvement skills:

  • Focus on the needs of the individual and the needs of the business and the equipment or process. Adults learn what they want to learn.
  • Involve the employees in developing the learning content and approach. Buying training in a can and delivering it does not work.

Second, the learning process must become more efficient and more effective than in the past. With many training methods and learning technologies available there is no need to stick with one method or format of training media. The media must fit the subject matter and the learner and also must be applied in the right setting, where learning will be most effective. Here are a few hints:

  • Match the subject matter and the training method with the media and the subject being taught. For example, teach coupling alignment or bolt tightening with a brief video, followed by a hands-on demonstration and practice until each person demonstrates proficiency. Discuss and demonstrate related information such as proper tool selection, safety, record keeping, applicable company procedures, and the results of doing or not doing the task correctly.
  • Do not use a video program by itself to train an employee and then send the learner into the workplace “trained” to perform the task correctly. This method is highly ineffective and dangerous.
  • Some tasks are best taught one on one in the plant on the equipment. However, avoid an informal buddy method.

Third, the more employees understand about how the equipment and processes work the easier their jobs become. Quite often, such knowledge is withheld from personnel who operate and maintain the equipment in an attempt to keep jobs simple. Many businesses have learned the power of engaging people with manufacturing and equipment processes. Learning how to maintain, repair, troubleshoot, and improve equipment is accelerated if people know how and why equipment does what it is supposed to do.

Fourth, all learning must focus on measurable results in the workplace. Improved performance of the individual and the equipment is possible within a few hours or days of completing training. Training focused on the needs of the plant, equipment, and process as well as the needs of the individual employees becomes highly effective. Focusing on equipment performance problems heightens return on the training/learning investment.

Training for the sake of training or training in general subjects rarely leads to a sizable and sustained return on the investment.

By following these steps to improving training and learning effectiveness, employers and employees will find that training is no longer a cost but rather an investment in improving equipment effectiveness and process reliability. MT

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200

9:47 pm
April 1, 1997
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Star Watching

bob_baldwinGeorge Lucas’s three Star Wars films are very important to me. I had the pleasure of viewing each one in a large theater with my children. The films provided our family with entertainment experiences to be savored for the rest of our lives. The recent release of the Star Wars Trilogy special edition 20 years after the original film gave me an opportunity to relive those experiences. I was delighted to view the enhanced version of these films, again in a large theater, and with my adult children who were visiting.

Because Star Wars was such a big thing around our house 20 years ago and remembered so fondly, I followed the promotional hype about the enhancements to the films, including several interviews with writer, director, and producer, George Lucas.

Lucas had a grand vision of his project. He knew what he wanted to do and he went about doing it. But his vision was ahead of film technology at the time, so he pushed the envelope with special effects and the audience was blown away by the results.

I couldn’t help but contrast Lucas’s outlook 20 years ago with that of many maintenance and reliability managers today. Lucas pushed the technology envelope to achieve a grand vision, whereas maintenance organizations have affordable technology available everywhere but most lack the vision and commitment to use it effectively.

Fortunately, when Lucas was working on his visionary film 20 years ago, some maintenance professionals and computer professionals were working to render visionary maintenance information models in computer code. Those maintenance information models have evolved into truly spectacular client-server computer applications capable of bringing information on all aspects of the enterprise to the people who need it.

Control hardware also has evolved. It is estimated that 30 times more information is available from smart instruments than the simple variables required for process control. Control networks make this information available in the instrument maintenance shop as well as the control room. Modern rules-based software can take plant data, filter and analyze it, assess equipment condition, and take appropriate action without human intervention.

There is plenty of technology waiting for organizations with the vision to take advantage of it, and there is also the force of competition waiting to bury the organizations who don’t.

Thanks for stopping by,

rcb

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364

8:56 pm
April 1, 1997
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Evaluating Maintenance Information Management Systems

The level of detail to consider in determining requirements and evaluating vendors is critical.

It is not uncommon for evaluation and selection of a computerized maintenance management system (CMMS) to take 6 months to a year. Too much detail can lead to cumbersome evaluations and comparisons and can create a “paralysis by analysis” situation. Too much detail also can lead to trying to design a system rather than configuring an existing package to the company’s maintenance business needs. Too little detail leads to poor selection of software and subsequent failure of CMMS implementation.

Define requirements
Plant and facility managers must first understand what maintenance information management is and why it is needed. A maintenance information management system should support company missions, goals, and objectives for the maintenance and materials organization. Understanding asset information management software depends on what is driving the need for change. CMMSs go beyond the “point solution” mentality; they can affect the entire organization. Without reliable equipment at an effective price, and an information tool for managing activities, a company simply cannot achieve competitiveness. Because the CMMS affects the entire organization, implementation must not be considered trivial.

Form an evaluation team
After the goals for the CMMS have been analyzed, the selection team can be formed. The prospective users are the field experts best qualified to evaluate its capacity in their functional areas.

Team members should be prepared to be involved for a period of 2 to 6 months, depending on their experience and the complexity of the requirements. Traditionally, new systems require various forms of interfacing and integration, and Information Services (IS) representatives have been the primary evaluators. Today, however, although IS should be part of the team, advances in information technology allow more end users to configure a system and change its look and feel. Of course, the system must be configured under a detailed and controlled process.

If the company has little or no experience with this type of evaluation, including consultants or maintenance business integrators on the team can be helpful. Maintenance consultants can provide an outsider’s experienced perspective in analyzing business processes and focusing on optimization of these processes. They also can ensure that the new system’s requirements are driven by business processes supporting overall goals and not by the software vendor’s promotional literature.

The selection team’s responsibilities include determining business process requirements, creating initial vendor requests for proposals (RFP), evaluating products through scripted demonstrations, compiling results, and making final recommendations.

Determine business process requirements
The underlying concept of business process analysis or “mapping” is an event-driven process chain that illustrates the maintenance business in a logical, consistent manner. Optimization begins with breaking out of old patterns and searching for profitable improvement opportunities.

Configuring a CMMS in the way that the business should work, rather than forcing the business to conform to the structure of the CMMS, maintains a process-centric approach.

Maintenance business processes must be integrated across all information systems–from asset care work order management to inventory management to purchasing to accounting and personnel management. Business process requirements define the boundaries of the system, the interfaces and integration to it, the functionality contained within it, and the type of technological environment desired.

Modeling a company’s essential maintenance elements and their relationships with other processes can significantly strengthen the overall effectiveness of the execution process when an asset information management system is integrated.

Create a vendor list
While they are evaluating maintenance business processes, the selection team can begin creating a list of potential products and vendors that meet the initial phase of requirements. Reading about various vendors, reviewing their marketing materials, and reviewing high-level demonstrations give the team a chance to see what is available from both technology and functionality standpoints.

Typical information sources include trade and professional publications, software directories, and the maintenance consultant’s experience. The number of potential vendors at this stage should be 10 or 12.

Develop and submit requirements document
Detailed requirements help vendors identify product “fit” and can help in estimating costs. The more concise and complete the documentation is, the less risk exists for future cost overruns and delays. Submitting a detailed request for proposal that contains the requirements is the recommended approach. Vendors are asked to address the RFP point by point whether the software complies or requires custom work.

Hold vendor demonstrations
After the RFP responses have been analyzed, the number of vendors should be reduced to two or three. Meetings with those vendors can accomplish several goals:

  • Clarifying issues and understanding the vendor’s response to the RFP
  • Assessing the vendor’s ability as a business partner
  • Assessing the vendor’s capability in modeling business processes
  • Setting up visits to reference sites.

Select the software
There is no simple “one size fits all” solution to making the final decision. Multiple factors must be considered, and the choice will be different for each company, depending on the company’s vision, organizational readiness, and end user level of acceptance. The final selection should use three major criteria:

  • The functional aspects of the product: Does it meet business process requirements?
  • The technical aspects of the product: Does it meet technical IS requirements?
  • The business aspects of the product and vendor: Are pricing and the cost for support acceptable? Will the vendor be easy to work with?

Creating a scoring matrix will aid in making the decision. The matrix should be built on the business process models and include technical and support issues. The matrix should also forecast return on investment weighting.

The keys to optimizing maintenance business are effective assessment, application, and optimization of maintenance management information systems.

The best investment protection for a CMMS is a thorough understanding of the existing maintenance processes and application of the maintenance system in concert with these processes.

This statement is true regardless of how big the organization is, or whether the new CMMS will replace an existing system or is the current system at the site. MT


Nicholas Phillippi is a project manager for HSB Reliability Technologies, 1901 N. Beauregard St., Suite 600, Alexandria, VA 22311; telephone (612) 943-7287.

Steps In Selecting Maintenance Information Management Systems

  • Define Requirements
  • Form evaluation team
  • Determine business process requirements
  • Create vendor list
  • Develop and submit requirements document
  • Hold vendor demonstrations
  • Select software

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