Archive | 2005

188

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December 1, 2005
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Beyond RCM

Balancing asset availability and utilization to improve business performance

What I’m about to say is going to sound like heresy to many of today’s RCM-focused maintenance professionals: maximizing the availability of industrial assets—even critical assets—is not always the best business strategy.

Please hear me out and note the intentional underlining of the word “always,” because the time factor is critical here.

Sure, chances are, as a maintenance professional, your performance is measured (and rewarded) based on how well you keep the plant running while containing costs. But, to succeed in today’s global industrial environment, companies must manage their manufacturing plants to meet ever-changing business objectives.

For example, in a production-constrained environment, where high demand and limited capacity mean that you can sell as much of a commodity product as you can make and charge pretty much whatever the market will bear, then sometimes a “run to failure” approach that utilizes assets to the max (even if only temporarily) can actually be the best overall business strategy to follow (if not the best maintenance strategy).

Clearly, what’s needed is an approach that enables you to balance industrial asset availability and utilization in a manner that allows you to maximize overall business value. Our organization calls this approach, “asset performance management.”

The problem is that while the maintenance staff in an industrial plant is typically measured on asset availability, the operations staff is typically measured on asset utilization. Beyond the obvious Maintenance/Operations organizational issues, the respective measures are inverse functions. That is, they tend to fight each other, especially as a plant approaches the maximum points for each.

For example, a well-maintained valve, pump, motor, heat exchanger or entire process unit that is hardly ever used—or used at a small percentage of its rated capacity—will almost always be available. Conversely, when operated non-stop for extended periods at or above their rated capacities, the availability of these plant assets will likely be seriously compromised (due both to wear and tear and lack of maintenance…).

To solve this problem, manufacturers need to identify the optimum balance between asset availability and utilization for any asset set at any given time, based on the current business strategy. Then, they need to use an integrated asset performance management approach to get Maintenance and Operations working together to achieve and maintain this balance.

New asset performance management models and algorithms are available to help manufacturers measure both asset utilization and availability in real time and identify the optimum balance that will best enable them to achieve current business objectives. With this understanding, a combination of advanced technologies, services and approaches (including RCM) can then be effectively applied by both Maintenance and Operations to drive utilization and availability to the desired states and thus maximize overall business performance.

Mike Caliel is president of Invensys Process Systems, a business unit of Invensys plc that includes the Avantis, Foxboro, SimSci-Esscor, and Triconex brands. Prior to joining Invensys in 1993, Caliel worked for both Honeywell and ABB.

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221

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December 1, 2005
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Maintenance/Asset Management Sales Presentations

In previous columns, we’ve highlighted why there is a need to speak the language of the CEO and CFO. Now, we need to discuss how to do it. Examining the major areas of financial impact for the maintenance/reliability functions in a plant or facility, we can see that they typically fall ito three major categories:

  • Cost reductions
  • Asset availability improvement
  • Asset efficiency improvement

This month, we’re going to look at the cost-reduction aspect. Cost reductions that can be achieved through maintenance improvements also basically fall into three major categories:

  • Maintenance labor
  • Maintenance materials
  • Energy savings

    As far as maintenance labor is concerned, the major savings is realized through increased labor productivityÐmeaning that the waste in maintenance labor deployment is reduced. This is one of the focuses of “Lean” maintenance initiatives, in which the focus is not on having technicians work harder, but smarter.

    For example, how often are the technicians at your plant waiting to work? In reactive plants, this can be as much as 70% to 80% of their time. That is the inverse of productive or “wrench” time, which will then be 20% to 30% of the technicians’ actual time on the job.

    Granted, the more proactive an organization is, the less waste that will be encountered. Conversely, if 50% or more of an organization’s resources are deployed on reactive work (work that is planned with less than one week’s notification), the more losses it is likely going to be encountering in this area.

    The key to increasing labor productivity, and, thus, decreasing this waste, lies in maintaining the organization’s assets to a point that they do not require short-term maintenance interventions. The primary maintenance strategy in accomplishing this is an effective preventive maintenance program. Maintenance activities that are planned and scheduled on a weekly basis cost 25% to 50% less than those that are performed in a reactive mode. Yet, while these are interesting statistics, do they really get the attention of the “C” level managers in your organization? Probably not. So, let’s consider the situation from another perspective.

    If you have 50 maintenance technicians in your organization, each working 2,000 hours per year (a low, but round number) and they are deployed with 25% “wrench” time, this amounts to 25,000 hours of actual work. If those technicians are paid $20. per hour, this equals $2,000,000 per year to accomplish 25,000 hours of work.

    On the other hand, if their “wrench” time were increased to 50%, those 50 maintenance technicians working 2,000 hours per year would accomplish 50,000 hours of actual work. Running these numbers, we can see that the technicians’ combined 25,000 hours of work actually could be accomplished for $1,000,000. Or, 50,000 hours of work could be accomplished for the $2,000,000.

    While a direct workforce reduction might seem logical based on the above scenario, you might want to simply consider a possible reduction in overtime (“best practice” is less than 5% overtime) or the economy of bringing outsourced work back in-house.

    If you were a “C” level executive, would the approach outlined here be something you would be interested in reviewing? Of course. This type of presentation helps the CEOs and CFOs truly understand the contribution of maintenance and reliability to profitability. Moreover, it’s the type of presentation you should be prepared to deliver every time.

    (Next month, we will consider a similar approach to spare parts savings.)

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    301

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    December 1, 2005
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    Building Successful Maintenance Skills Training Programs

    Look to ADDIE and her proven track record when it comes to developing and implementing effective training initiatives.

    Alarmingly. . .

     

    In certain skill-level assessments throughout the U.S. and Canada, 80% of those assessed scored less than 50% in the basic technical skills needed to perform their jobs. Additionally, assessments of maintenance department training programs indicated that the majority were not effective in resolving these skill problems. The primary causes of ineffective training included lack of targeting  within training programs and failure to use training-effectiveness metrics.

    Training can be a substantial investment, but it is an investment in your company, your people and the future. Effective training programs can improve equipment reliability and increase production levels. It also can support incorporation of new technologies, implementation of new procedures or the transfer of knowledge. Effective training programs can transform “on-paper” benefits into a real return on investment (ROI).

    To generate real skill-level improvements, employing a systematic approach to the development and implemention of the training program is essential. A proven effective approach is one based on the ADDIE Instructional Design Model. The success of this approach in improving skills and meeting industrial training requirements has been demonstrated in commercial manufacturing operations, as well as in nuclear power, aerospace, health and defense industries. It has gained acceptance in each of these fields by improveing training effectiveness.

    Through enhancement of the ADDIE model, greater successes in a shorter period of time, as well as increased responsiveness to changes, can be realized. The traditional model is a closed loop system with the evaluation results (the effectiveness metrics) used to update/upgrade the analysis, and so on. By creating a continuing analysis process, that is a process that continually considers and incorporates employee, equipment, facility, technology and similar changes, the entire ADDIE loop is renewed through both fresh perspectives and effectiveness improvents based on evaluation results. The results: better adaptiveness to change and quicker realization of skill requirements, which can very quickly impact equipment reliability and production capacity.

    Some characteristics of this internally looped, five-phase training program development process include:

    • It identifies the skills and skill levels that are required for your specific plant/operation.
    • It identifies the skills and skill levels that are available at your specific plant/operation.
    • It identifies what training should be provided for each position (based on analysis of the gap between required and available skills).
    • It provides continuous analysis of skill requirements, skill availability and gap- targeted training objectives.
    • It facilitates the design and development of training programs with explicit learning objectives and appropriate content.
    • It implements training presentation formats that are the most effective for achieving training objectives.
    • It ensures that employees master the learning objectives before they begin working in their assigned positions.
    • It measures training effectiveness and uses the results to maintain and improve training.

    The modified ADDIE training design/development process
    Analysis is the process of determining, and responding to changes in, personnel requirements, job performance problems and learning from industry experiences. It begins with fact-finding needed to make informed training development decisions. This ensures that apparent concerns are verified and can be resolved through training.

    Where the facts confirm/identify a specific training need, job task analysis uses existing job data and employee skills/experience to identify and rate job tasks/job skills gaps.

    Tasks rated difficult and important and lacking appropriate skills are selected for training. Their exact methods of correct performance and underlying competencies are determined through task analysis. When compete, this process reveals reliable information on effective and safe work practices. The knowledge, skills and attitudes identified provide a task-specific content reference for both new and existing programs.

    The Design process uses the task requirements and performance information collected during analysis to specify the knowledge, skills and attitudes that will be provided in the training. Skill requirements (knowledge and practical) are defined for each task. By defining how individual tasks are performed, they focus training development efforts and support task training and qualification.

    Learning objectives are developed for groups of task-related knowledge and skills. These types of written statements define exactly when, what and how well the employee must perform during training.

    Based on prior experience, lessons learned and instructional training, the most effective presentation methods are defined for the various sets of learning objectives (internal instructors, consultant and/or vendor instructors, community/technical colleges, employee self-paced, classroom, OJT, computer network, etc.). Tests are produced to ensure that these competencies are reliably evaluated. Together, these measures serve as the program design basis.

    Decisions on the training setting, employee entry qualifications and organization or learning objectives also are made. The design process concludes when all the tools for development of a training program are defined.

    Development organizes the instructional materials needed for employees to achieve the learning objectives. During the development phase, a review process by subject-matter experts that can include a table-top review, a written comment and revision cycle, and, if desired, a training pilot, is an important step. During the review process, critical input is essential to ensure that the training materials are clear, accurate and effective in addressing the desired objectives.

    Instructor and employee activities are defined based on presentation methods. These activities describe how the instructor and employees will perform during training to achieve the learning objectives. Existing, suitable training materials and lesson plans are selected and new ones produced as required. The resulting training materials are reviewed for technical accuracy, tried out with a group of employees and revised as necessary. Performance-based training materials are the products of this phase.

    Implementation is the process of putting training programs into operation. It begins by defining scheduling criteria and activating the training plan. Based on training delivery methods, instructors are selected and trained, and the availability of employees, facilities and resources is confirmed and used to create the training program schedule.

    Training is delivered as planned, and employee and instructor performance is evaluated. These evaluations serve two purposes:(1) to verify that employees have achieved the learning objectives; and (2) to identify and resolve any instructor performance and presentation method problems. Key records are maintained to support management information needs and to document the performance both of employees and instructors.

    Evaluation encompasses two distinct areas: (1) ensuring training’s continuing ability to produce qualified employees; and (2) measuring plant-related aspects, such as equipment reliability, production outages and production capacity. The latter area of evaluation is essential to monitor the effectiveness and the ROI in the training program.

    By monitoring such indicators as employee job performance, plant and procedure changes and production/operating experience, evaluation metrics help maintain and improve the training program. It is the dynamic process of assessing performance, identifying concerns and initiating corrective actions. The program feedback it yields enables training to respond adaptively to unforeseen problems or changing conditions. Completing the evaluation phase and incorporating its results produces the performance data and feedback vital to any training systemÕs continued effectiveness.

    Conclusion
    Training must on target. In other words, it must meet the expectation of both management and employees. The ADDIE process outlined here is not new. ItÕs been used successfully for many years. In light of its proven track record, even now, it continues to be taught in colleges and universities.

    Bob Call is a senior consultant with Life Cycle Engineering, in Charleston, SC. He has over 20 years experience in the maintenance and reliability field, specializing in project management, process improvement and supervisory skills training. Telephone: (843) 744-7110; e-mail: bcall@LCE.com; Internet: www.LCE.com

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    239

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    December 1, 2005
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    Do You Have The Right Foundation?

    Just because your company has a CMMS/EAM system doesn’t mean you’re using it properly. In fact, if you’re misusing any of the system modules, the information you’re generating may not be accurate.

    Data. . . information. . . facts. . . Whatever the term, “knowledge” is required to for good decision-making. The goal of a computerized maintenance management system (CMMS) or enterprise asset management system (EAM) is to produce quality data that helps a company make accurate decisions.

    Even as a company starts to implement CMMS/EAM, data collectio is beginning. Consider the various modules used in a comprehensive CMMS/EAM system:

    • Equipment
    • Inventory
    • Purchasing
    • Personnel
    • Preventive maintenance
    • Work-order (planning & scheduling)
    • Reporting

    Equipment module
    To use this module properly, each piece of equipment—or facility location—that requires tracking of costs and repairs must be identified. For example, the financial information will need to be stored in the equipment history when making repair/replacement and other life cycle cost decisions.

    Data provided by the other modules will be accumulated in the equipement module to provide accurate financial information.

    Inventory module
    Proper utilization of this module will require identifying the spare parts carried in each storeroom at the plant or facility. The necessary data includes, but is not limited to:

    • Part number
    • Part description (short & extended)
    • On-hand, reserved, on-order, etc.
    • Locations
    • Part-costing information
    • Historical use

    Information from the inventory module ensures the CMMS/EAMwill contain accurate material-costing information for each piece of equipment or facility location.

    Purchasing module
    This module is associated with the inventory module. It gives maintenance personnel a window into the ordering information.

    The purchasing module must include the following information:

    • Part number
    • Part description
    • Part-costing information
    • Delivery information, including date
    • Related vendor information
    • Ability to order non-stock materials

    The importance of the purchasing module becomes clear when planning a job and the delivery date for the required part is not available. It also is crucial for estimating job cost without knowledge of the new part cost.

    Personnel module
    This module allows a company to track specific information about each employee. Some of the required data includes:

    • Employee number
    • Name and personal information
    • Pay rate
    • Job skills
    • Training history
    • Safety history

    Information from the personnel module ensures that a facility will post accurate labor costs to work orders and equipment history.

    Preventive maintenance module
    The preventive maintenance (PM) module allows the tracking of all PM-specific costs. The costing information comes from the personnel and inventory databases. Some important data stored in this module includes:

    • PM type (lubrication, testing, etc)
    • Frequency required
    • Est. labor cost (via personnel module)
    • Est. parts cost (via inventory module)
    • Detailed task description

    The collection of this data ensures accurate service information and costing each time a technician performs a PM task. A CMMS/EAM also can project labor at material resource requirements for calendar-based PM tasks.

    Work-order module
    With this module, a user can initiate different types of work orders and track the work through completion. This module also requires the tracking of the costing and repair information to the correct piece of equipment or facility location. Using the work-order module requires information from all other modules of the system. Some the information required includes:

    • Identifying the equipment or facility location where the work is being performed
    • Identifying the labor requirements (personnel)
    • Identifying the parts requirements (inventory)
    • The priority of the work
    • The date the work must be finished
    • Contractor information
    • Detailed instructions

    To be effective, the work-order module requires information from all other modules. Without accurate information, this module cannot collect the required data. Furthermore, without accurate and complete data, it cannot post accurate information to the equipment history. Finally, without accurate data in the equipment history, maintenance/reliability personnel can’t make timely and cost effective decisions.

    Importance of data collection
    Just how important is data collection and analysis to a company? You can break it down into these management principles:

    • To manage, you must have controls.
    • To have control, you must have measurement.
    • To have measurement, you must have reporting.
    • To have reporting, you must collect data. The success of a CMMS/EAM system depends on the timeline and accuracy of collected data and the use of that data by the managers. If information is inaccurate and used incorrectly, the CMMS/EAM is considered to be a failure.

       

      The reporting relationship
      How effective is the overall utilization of any currently implemented CMMS/EAM systems? A recent survey showed that most companies scored just above 50% of the total possible score in that category. The figure reflects the comparison between a database of 200 companies (labeled University) and 800 companies (labeled RW).

      If Fig. 1 were reexamined, what modules in the diagram could be used and what ones could be eliminated? If only half of the information required by the CMMS/EAM system were utilized, what types of analysis could be performed? For example, if only work orders over a certain cost or duration were recorded in the CMMS/EAM, could accurate decisions be based on the equipment history information?

      Even before a facility implements a CMMS/EAM, the information it collects still will have some value. But, until the system is fully utilized, the data will not be accurate.

      For example, if only certain departments are on a CMMS/ EAM system (a typical pilot implementation problem), the data from these departments mayactually be quite accurate. However, in areas where a crossover or combination with another area or craft exists, the data may be incomplete or distorted.

      As highlighted earlier, a CMMS/EAM system should provide a completely integrated data collection system. Yet, even many mature users are not obtaining complete—and, thus, accurate—data from their CMMS/EAM systems. The previously mentioned benchmarking study pointed to the fact that just over 50% of the functionality was being utilized. Again, how can accurate and timely decisions be made with such incomplete data?

      When companies use corporate systems, the data might not be posted accurately in the equipment history. In fact, in most cases, the data is inaccurate or not posted at all. Consequently, the equipment history is incomplete or inaccurate.

      To put this into perspective, consider the following example:

      When you take your car in for repairs, the service manager gives you an estimate of the time and cost of the job (work-order planning). You accept the estimate, and the service shop begins the work. When the job is complete, you receive a shop order with a complete breakdown of each part used and its related cost. The bill (work order) also shows the number of hours the mechanic worked and his hourly rate. The total equals labor and parts.

      You expect this bill each time you go to the garage for any work. If your bill showed only the final price with no breakdown, you would not accept it.

      Now, apply this type of itemization to a CMMS/EAM system and consider whether this degree of reporting is detailed enough to provide accurate cost breakdowns for your plant’s equipment.

      Consider another example:

      When using CMMS/ EAM, if you do not supply the planner with closely integrated inventory information, that person cannot be sure the stores’ information is accurate. This is especially true if the information is updated only once a day or once a week.

      The situation repeats itself many times when other corporate systems are “interfaced” to a CMMS/EAM system.

      Technicians can waste time looking for a part that is supposed to be in the stores, when, in fact, another technician used that part the previous day or shift. This delay may seem inconsequential. However, when downtime can cost $1,000 or even $100,000 per hour, these types of delays may mean the difference between profit and loss for the entire company.

      When it comes time to consider replacing your car, do you look only at the labor charges you have made against it for its life? Do you look only at the parts used? No, you take the whole picture into account— labor, materials, present condition, etc. These same principles should carry over in the CMMS/EAM systems in companies. Unfortunately, though, companies have set CMMS/EAM information flow so the material or labor costs aren’t shown on the work order or equipment history. Therefore, decisions are really being based on inaccurate or incomplete dataÐand such decisions will be flawed.

      The financial implications of these flawed decisions can spell disaster foran organization. They can force a company into a condition where it cannot compete against other companies that make full use of their CMMS/EAM systems, thereby obtaining the subsequent cost benefits.

      If any part of the information detailed is not included during routine CMMS/EAM system usage, the system will eventually fail.

      The ultimate CMMS/EAM solution
      If a company is collecting data incorrectly, it is time to re-evaluate the CMMS/EAM system. A determination must be made as to whether data the company is collecting is accurate or if it is incomplete or missing. Moreover, a company should determine what parts of the system it is not utilizing correctlyÐor not using at all.

      By evaluating the answers and working to provide accurate data collection, the CMMS/EAM system will benefit the company’s bottom line. In today’s competitive marketplace, it is unacceptable to make guesses when data is available.

      The cost benefits gained by making correct decisions will help make a company more competitive. Wrong decisions actually can put a company out of business by placing it in a non-competitive position.

      What CMMS/EAM reports to use?
      Some systems are available with no reports, while others have hundreds of “canned” reports. The deciding factor is to use the reports required to manage the specific maintenance function.

      port does not support or verify a performance indicator utilized to manage maintenance, it is not beneficial. Reports that produce hundreds of pages of data that is never utilized will overload the maintenance and reliability departments.

      If a maintenance organization is managed by its estimated vs. actual budget and the CMMS/EAM system cannot produce a budget report, the system is not supporting the organization. With CMMS/EAM reports, too many are just as bad as too few.

      Give Fig. 2 another look. If the CMMS/EAM system score could be considered low, how about the reporting indicator? The two surveys were both under the 50% level, with one (marked “University”) in the 25% range. Realistically, how could one manage an organization where the reports are not properly utilized? Would this not, in truth, be managing by instinct or feelings? Since management requires measurement and measurement requires data, each company must use its CMMS/EAM system fully to obtain this data. Without such data, any decision that is made is just someone’s opinion.

      Discussions require factual data and when it is not available, arguments occur, which often is the case when emotions and opinions are involved. Consider whether employees at your company have discussions or arguments. The answer may mean the difference between being a world-class competitor and being a second-rate company.

      For additional information e-mail twireman@atpnetwork.com

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    474

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    Achieve Strategic Maintenance Through Metrics

    Looking at the big picture, if you ‘re not measuring it, you ‘re not really managing it.

    As manufacturing and production equipment often represent a company’s single largest capital investment, maintenance of these assets can significantly impact the bottom line. Many organizations face problems when they have not established a consistent method to measure the value of maintenance activities, which results in their underestimating the impact maintenance has on financial performance.

    Developing a methodology for measuring your processes provides guidance for needed maintenance activities and shows a continual impact on ROI. After you establish metrics for maintenance activities, you also can justify the value of current activities and support the case for new initiatives. This is especially true when initiating major changes in strategy, such as moving from a reactive operation to a proactive one. Without tangible evidence in the form of objective performance data, obtaining full buy-in support from management is more difficult to achieve.

    Determining what to measure
    The cornerstone for any successful Strategic Maintenance plan begins with clearly defining goals. Without adequately defining the desired performance—along with the reasons for it—companies often may generate a long list of metrics, yet overlook many that are vital to making critical performance-enhancing decisions.

    While most companies collect performance data, the challenge is to select information that has meaning to the bottom line. These types of powerful metrics directly measure the impact of maintenance efforts on the company ‘s Key Performance Indicators (KPI’s).

    Today, companies are turning to a variety of financial metrics, such as Return On Net Assets (RONA), which is commonly used by plant management. RONA calculates how well a company converts assets to sales, and, therefore, profits. Maintenance specifically impacts three main variables of the equation: Plant Revenue minus Costs divided by Net Assets.

    Other metrics used today are associated with plant productivity, such as Overall Equipment Effectiveness (OEE). Many times OEE is used in conjunction with RONA, as it is an extension of Plant Revenue. OEE is a statistical metric to determine how efficiently a machine is running. It is calculated by multiplying a machine ‘s Production Rate, Quality and Availability. The combination is the value a machine contributes to the production process.

    All companies have data and information, but many do not collect and analyze it to make informed decisions. Results from metrics can help companies lower inventory costs, reduce spares and boost availability and uptime. Maintenance impacts all of these features, but it is commonly used with downtime.

    Case in point
    A leading semiconductor manufacturer ‘s decision to migrate toward a more predictive maintenance strategy was directly tied to its business goals. In an industry where a few hours of downtime can result in millions of dollars in losses, success is measured by uptime.

    In semiconductor manufacturing, every part of the facility plays a critical role in the process. If any part of the facility fails, such as the power supply, HVAC or water-treatment system, production could come to a rapid—and costly—standstill. Using advanced condition-monitoring technology, the company designed and implemented a comprehensive predictive maintenance program that allows it to effectively monitor, analyze and track equipment performanceÐobserving operating conditions locally, as well as remotely, across multiple production sites.

    The reality is that replacing a fan or pump motor is a fraction of the cost of having a fabrication line down for any amount of time. If production is down for even one or two hours, the lost revenue would far exceed the cost of a replacement motor, or any other ancillary component.

    Since implementing its predictive maintenance program, the company has found countless minor vibration issues and identified several hundred major vibration problems, helping it avoid prolonged production shutdowns. More specifically, it has realized a five-to-one return on investment, and the program helped the company avoid estimated lost-production costs of more than $1.4 million in a single year.

    The big picture
    A complete review of maintenance operations and the physical asset management process can help identify equipment and operator performance issues and outline recommended corrective actions that can be implemented through maintenance initiatives. For example, in critical applications, companies may want to have a redundant or back-up piece of equipment in place to avoid production interruptions in the event the primary equipment needs to be shut down or replaced.

    This type of in-depth evaluation is important because it gives you a baseline as to your starting point for making improvements and for validating results. It also can help determine which activities will have the most impact on the company’s core business objectives and assist in identifying key areas of improvement, including what types of predictive strategies might be most effective.

    Once you’ve identified the most critical elements impacting your performance, you can begin to make a physical linkage between the maintenance activity and the improvement in results.

    Tapping the value of data
    In some cases, depending on the size of the plant, the type and volume of data needed to formulate the necessary metrics is not always available. In these instances, implementing the data collection or measurement technology can be an investment in itself.

    For example, you may need a software package to collect information to measure production rates, equipment availability or the amount of scrap coming off the line. You then can begin building your metrics off that data.

    In an industry where margins are low and parts are needed on a 24/7 basis, the correlation between equipment uptime and profitability is abundantly clear for the previously referenced semiconductor supplier. To maximize equipment reliability, the company established a comprehensive parts management program that has helped it improve parts availability, increase manufacturing efficiency, reduce downtime and minimize its inventory investment.

    In turn, the parts program has been instrumental in helping the company meet its aggressive production goals while minimizing costly downtime. Since putting the program in place, the company has reduced inventory by 25%, helping save approximately $250,000 in inventory expenses. Moreover, it credits the parts program for helping the facility boost its capacity by 250%—which helps the company significantly increase its return on net assets.

    Defining performance levels
    Any established metrics should focus on the level of improvement required to move from the current level of performance to the desired level. Defining this difference lets companies more effectively determine the specific actions, strategies and initiatives they need to undertake. To establish a successful measurement system, managers need to know:

    • The desired level of performance in quantifiable terms;
    • How the current performance levels are to be determined;
    • Specific actions that can be taken to close the gap between the current level and desired level.

    Performance measures should reflect how the maintenance department is providing value. For instance, in the power generation industry, downtime expense is calculated in cost-avoidance terms based on the profit from generating a megawatt-hour of electricity. Depending on the plant, the profit for a megawatt-hour varies drasticallyÐ ranging from $5 to $25 per hour. At one 560-MWpower plant in California, the cost-avoidance is calculated at $21 per megawatt hour. Therefore, downtime at this plant could cost upwards of $11,000 per hour (or $265,000 per day).

    By measuring the production value of the downtime for a department or unit, you can quickly grasp, with clear evidence, where to place your maintenance efforts. This allows you to more accurately focus the planning process by seeing what is costing the most money and knowing where to target your efforts. You then can record the cost of failures while directing efforts directly to those causes.

    Leveraging technology, improving techniques
    The emergence of advanced automation and control technology has made the effective use of maintenance metrics considerably easier. It can assist in nearly every area of maintenance. For example, maintenance software systems can track spare parts, compile time and costs, track metrics, schedule work and analyze equipment conditions.

    Wherever possible, build your collection of measures into the design of the automation system itself, so the metrics become an automatically generated product of normal usage. This can help reduce the burden of implementing and managing metrics.

    However, not all metrics are amendable to automated collection. So, in practice, you will need a mix of both “hard” and “soft” measures.

    Also, remember that automation systems and software can ‘t guarantee good maintenance performance or compensate for a lack of fundamental knowledge of what to measure and why.

    In some cases, companies can boost manufacturing efficiencies through improvements in operational processes, such as inventory tracking and equipment repair management. An effective inventory tracking system can help companies track overall repair rates and identify ways to build efficiencies into the process. For instance, if a pattern of repairs occurs on a particular machine over a period of time, storeroom managers can work with maintenance engineers to find and repair the root source of the equipment failure.

    Communicating results
    As previously mentioned, developing a methodology for measuring your processes provides guidance for needed maintenance activities and can justify the value of current activities and support the case for new initiatives. Justifying maintenance iniatives requires a significant investment in time and energy to not only establish accurate measurement parameters, but also to effectively communicate the value of maintenance and its relationship to the company ‘s underlying business goals. It involves shifting management ‘s attitude from one that sees maintenance as a necessary expense, to one that views it as a profit center.

    When using metrics to guide your project plans, it is important to stay objective, stick to the facts and understand the business trends that drive the need for improvements. For example, how does your parts management program help improve equipment uptime and reduce expenses related to lost production and scrap? More specifically, how does this impact on-time delivery—a key management goal?

    Bottom line
    If management does not fully understand the impact that maintenance activities can have on the organization, it is less likely they will support new initiatives or additional expenses.

    As for a management discipline, companies are still striving to realize the full potential and benefits of using performance metrics as a proactive tool to implement strategy throughout their organizations. When approached with a clear understanding of issues and goals, metrics can be a powerful way of setting targets, measuring success and identifying problems as they surface.

    Mike Laszkiewicz is the vice president, Customer Support and Maintenance business at Rockwell Automation. In his current role—and previously as vice president, Asset Management—he has been instrumental in developing Rockwell ‘s strategy for addressing the maintenance repair and operations (MRO) needs of manufacturers around the world. Laszkiewicz holds a Bachelor’s degree in Industrial Operations Management from the University of Wisconsin-Milwaukee. Telephone: (414) 382-3736; e-mail: mlaszkiewicz@ra.rockwell.com

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    254

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    December 1, 2005
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    The Wrong Maintenance Priorities Threaten Corporations

    According to this well-known veteran of the reliability trenches, one of the best ways to hone the survival skills industry needs today and into the future is to pay attention to the basics. Taking time—making time—to read is a great way to start.

    Many process plants assume that better maintenance strategies will lead to higher equipment reliability. Very often, the primary focus of these strategies is to avoid unnecessary oil changes or to optimize compressor overhauls and the pursuit of other preventive measures. Similarly, many of these strategies hope to help companies avoid equipment damage and costly production interruptions by doing appropriate maintenance “just-in-time.”

    While these are commendable goals, they do not address the constraints that are built into vast quantities of equipment that incorporate less-than-optimized components. Nor do such strategies remedy the numerous random failures that strain the maintenance budgets throughout industry today.

    Staffed by harried employees, shops frequently become adept only at replacing parts in kind. Likewise, relatively few companies position themselves to systematically implement maintenance avoidance measures. We know that, in existing plants and with few exceptions, failure avoidance would be far more profitable than implementing optimized maintenance timing on non-optimized equipment. In new equipment procurement situations, utilizing specifications that eliminate the very components that risk causing frequent maintenance and downtime would provide far greater returns on the incremental investment than fine-tuning an asset management or related program.

    Take, for example, the many operating plants today with literally hundreds of thousands of pumps that were purchased from the lowest bidders. It is wistful thinking to expect that all components in these lowest-cost machines represent best-available technology. In the age of downsizing, rightsizing and outsourcing, how realistic is it to assume that all of the various equipment manufacturers and vendors employ seasoned, well-versed, well-read subject matter experts?

    Suppose a manufacturer recently sold less-than-optimum equipment. Knowing that we live in a litigious environment, would we really expect this manufacturer to concede that he/she continues to make, sell or market non-optimized equipment or components? If the answer is no, then it is clear that the user/purchaser has to be the driver for identifying and implementing equipment upgrades.

    Trends that lead nowhere vs. trends for best-of-class performers
    At the risk of inviting irate responses from benchmarking companies, we contend that the trend towards increased benchmarking will, ultimately, add little value to many enterprises. A recently published article mentioned four so-called perspectives, labeling them Operations, Reliability, Work Management and Safety & Environmental. Goals were specified for each and 60 different key performance indicators (KPIs) were listed as useful for managing risk and improving profitability.

    At best, each one of those 60 benchmarks may give plants an indication of where they are in the game. Yet, not any of these listings specified even one of the many precise steps that really represent lasting improvement. What good is it to tell a facility it is re-working too many pumps, if nobody is able to explain the root cause reasons for this “excessive re-working” at that plant? While it’s nice to point out the fact that “there must be a problem somewhere,” far more value would be derived by adequately describing the root causes and solutions.

    Today, truly best-of-class performers use asset management and streamlined maintenance strategies as “icing on the cake.” They realize that these approaches add value only if the basics are in place and being practiced with consistency and forethought. As an example, best-of-class owner/purchasers are not likely to buy from the lowest bidder. They generally look at several competing offers and carefully examine which of them have “designed out” maintenance and failure risk. Best-of-class companies rarely, if ever, enter into lopsided alliances with suppliers. They will always use well-thought-out specifications that clearly describe and explain specific “upgraded” component materials, configurations, lubricant application methods, etc. Thus, the most important attribute of true best-in-class performers is their ability to provide authoritative answers to two questions:

    1. Can a component be upgraded to resist failure?
    2. If upgrading is feasible, is it also economically justified?

    These are primary. . . these are the basics. Everything else is of lesser importance. Best-of-class performers know this to be a fact and are organized accordingly. Moreover, they are staffed so as to have a person—a designated and responsible individual—who can answer these two questions quickly and with great accuracy.

    Why upgrading is often best
    Unfortunately, even now, buying from the lowest bidder remains the predominant procurement mode. Equally disappointing is the fact that those responsible for shortsighted decisions are often the ones that block access to systematic failure-avoidance measures. Consequently, even the otherwise desirable life cycle costing (LCC) methodology is an academic exercise unless the person doing the comparison is in a position to answer the two previously-asked questions.

    A facility which assumes that improvement initiatives spring forth from the original equipment manufacturer, or OEM, often will be disappointed. When, in 1986, a representative of a prominent pump manufacturer was asked why its designers didn’t engineer better pumps, the answer was that most customers selected pumps primarily based on cost and schedule. Accordingly, sales success was linked to cost and schedule, not long-term quality.

    More recently, at a symposium in Houston, another pump manufacturer claimed that general-purpose pumps were designed to be overhauled or repaired every 18 months. To keep costs low, two pump manufacturers said they couldn’t afford to upgrade their pumps.

    And, just last spring, at the 2005 NPRA Maintenance and Reliability Conference in New Orleans, several panel members touted key performance indicators that were largely based on not having production interruptions. To this day, a large number of managers and reliability engineers seem to be unconcerned if their pumps fail far more frequently than those at a competitor’s facility. The thought was even expressed that keeping pump failures at (relatively) high levels was one of the “safeguards” preventing upper-level managers from cutting the maintenance budget.

    At the same NPRA conference we met with a presenter of asset management strategies. We attempted to argue the monetary merit of failure reductions by selective upgrading. When the speaker suggested that his organization was very effective in identifying and recommending the various upgrade options, we challenged his claims. We have yet to find asset management consulting companies that identify the needed upgrade measures to the degree of detail urgently needed by industry.

    In support of our beliefs, we cited lube application in pumps as one of the many examples of industry not even being made aware of tangible reliability risks. This example deals with the use of oil rings in literally millions of equipment bearing housings, most of them in centrifugal pumps. Recall that the entire issue centers on our contention that industry is losing knowledge and application of the basics. Changing or fine-tuning management approaches will not bear the promised fruits unless the approaches are interwoven with systematic upgrade efforts. The following cases illustrate the type of dilemma with which industry is wrestling.

    Case #1: Lifting oil with bicycle chains
    While working with a client to determine the root causes of sludge in an oil sump and bearing failure in a pump, an experienced consultant (who was formerly employed as director of new pumping machinery development for two noted manufacturers) found a bicycle chain in the bearing housing. Its purpose, of course, was to feed lube oil to the bearings. Chances are that the bearing housing was simply too narrow to accommodate oil rings or similar means of lube application—a serious reliability risk.

    When the consultant questioned the appropriateness of using a bicycle chain in this manner, the pump manufacturer objected to the criticism and claimed “that’s the way we generally do it. . .we hear no complaints.” Basic science, or the most elementary application of engineering formulas, though, would show that the chain would have no chance of moving at the peripheral speed of the shaft at anything other than—for process pumps—unusually slow speeds.

    In most instances, the bicycle chain would slip relative to the shaft surface and, by virtue of the total downward-acting weight of the heavy chain, the side plates of the links would rub on the shaft. Wear-related oil contamination would almost certainly result, as was found and documented by the consultant. All of this begs the question: Would your asset management consultants have the basic knowledge to alert you to this? Or would your consultants limit their contribution to the rather obvious, i.e. telling you that you’re spending too much money on maintenance, and that you have “X% more” or “Y% less” shop backlog than the industry-recommended average? That would be nice to know, but where’s the real solution?

    Case #2: The limitations of oil rings
    Pump bearings in best-of-class U.S. oil refineries fail—on average—every 10 years. In certain other U.S. oil refineries, the failure rate is three times higher, with the average pump mean-time-between failures (MTBF) closer to three years. Let’s re-state our earlier point: To really add value, asset management consulting firms will have to authoritatively advise and advocate specific component upgrades. These firms must know, and must tell, the user-client, that oil rings (Fig. 1) impose a key limitation on the MTBF of many pumps.

    While perhaps representing one of the least expensive means of applying lube oil to bearings, oil rings are rarely a wise choice for the reliability-focused. From about 1840 until 1990, they were furnished in brass or bronze. More recently, and for reasons we wish to subsequently spell out, some manufacturers have experimented with plastic and aluminum rings. The results are mixed, at best. In any event, oil rings suffer from a number of limitations that are rarely recognized by equipment suppliers and users. Reliability-focused users avoid oil rings because these components represent an undue reliability risk. Here’s why:

    • Even some of the most advanced laser-optic shaft alignment systems will not have provisions ensuring that the shaft centerlines are absolutely horizontal. Visualize, therefore, how oil rings installed on shaft systems that are not totally parallel with the true horizon will run downhill. Doing so, an oil ring will make frictional contact with either a groove machined in the shaft, or some stationary surfaces associated with the bearing housing. The oil ring now tends to slow down, feeding less oil into the bearing. Many observers have also seen oil rings that showed clear evidence of edge wear and metal loss. Needless to say, the lost metal shavings end up contaminating the lubricant—not a desirable condition by any measure.
    • Oil-ring movement and circumferential speed are affected by the degree of immersion in the lubricant and by lubricant viscosity. Typical immersions are shown in Fig. 1, but recommendations may vary for different types of equipment. Clearly, a more deeply immersed oil ring or oil rings contacting an excessively viscous lubricant will not perform as intended. Also, for good tracking and to revolve with reasonable consistency, oil rings must be concentric within 0.002 inches (0.05 mm).
    • Oil-ring operation is affected by shaft surface velocity. As an experience-based rule, authoritative texts (Refs. 3 and 4) caution that shaft velocities as low as 2,000 fpm (~10.16 m/s) might represent the safe, or practical, field-installed (non-laboratory) limit for many oil rings. At 3,600 rpm, this limit infers a maximum shaft diameter of approximately 2.125 inches (~55 mm). It represents a “DN” value of 7,650, where DN is the product of shaft diameter (inches) and speed (rpm).
    • Reliability-focused users recommend flinger discs. Since flinger discs are secured to the shaft, they are not subject to the compounded influences of shaft horizontality, oil viscosity, depth of immersion and ring concentricity. They are a vast improvement over oil rings and are, in fact, available in many pump models presently marketed by U.S. and European suppliers. Ref. 1 contains an illustration from a 1960s-vintage catalog issued by a then prominent, major U.S. pump maker. The page shows the flinger discs furnished with this manufacturer’s pumps and states, rather pointedly, “anti-friction oil thrower (meaning flinger disc) ensures positive lubrication and eliminates the problems associated with oil rings.”

    Indeed, oil rings were problematic in the 1960s, and, more than 40 years later, they are still causing problems in many field installations. Retrofit flinger discs are available as cost-effective upgrade and retrofit options. Made to oversized dimensions, they can be easily trimmed to the required diameter. Their elastomer will fold into an umbrella shape during insertion through a narrow bearing-housing bore and will then snap back into its regular disc shape.

    In 2003 and 2004, thorough testing was done on a Viton¨ disc’sconfiguration at different speeds and with oils of different viscosities. Two results of this testing are shown in Fig. 3 and Fig. 4 for ISO Grade 32 and 68 lubricants at 3,600 rpm shaft speed.

    In each case, with flinger discs installed, the oil and bearing temperatures were compared against operation with the flinger disc removed and lube oil reaching the center of the lowermost bearing ball. From the graphs, it can be seen that, at higher pump speeds, lowering the oil level and using the trimmable flinger disc will reduce oil temperatures. Reduced oil temperatures will slow the rate of oil oxidation and tend to more closely maintain lubricant viscosity. Incidentally, with premium synthetic lubricants and operation at typical process pump speeds, the rate of oxidation is extremely slow. In that case, concern over oxidation issues on hermetically closed pump bearing housings are of very academic interest.

    Economic value explored
    Upon close examination, and with competent failure analysis, many observers have reached the conclusion that a large percentage of oil rings show signs of severe abrasion. It is undisputed and well known that the resulting lube oil contamination is reflected in premature bearing failures. Based on these observations, it has been estimated that at least 5% of the centrifugal pumps installed in the average petrochemical plant suffer from oil-ring deficiencies of sufficient magnitude to reduce bearing life from an assumed achievable six years to typically only three years. Other pumps may experience oil-ring degradation that reduces bearing life from five years to four years, and so forth. The issue is so intuitively evident that, to date, no one appears to have seen fit to spend research funds on scientific studies. Accordingly, empirical observations will have to suffice.

    In any event, expanding on this conservative estimate, we might be dealing with a plant comprising 600 pumps. Suppose that of these, 18 “suspect” pumps were being repaired every three years to the tune of $6,000 per incident. This would require an expenditure of $36,000 per year. If, using trimmable flinger discs, the MTBR (mean-time-between-repairs) could be extended to six years, this expenditure would drop to $18,000 per year for the affected 5% of the plant’s pump population. Needless to say, if one paid $50 per flinger disc, the 18 discs would have cost $900 and the investment would have had a payback of $18,000/$900 = 20:1. It is certainly no stretch to foresee greater savings and even more significant payback than demonstrated in this example after one or two years of operation.

    Belaboring the point
    The issue at hand is important enough to be highlighted again. Management often doesn’t seem to get it. Our view is simply that asset management and maintenance strategies are rather pointless if oil rings and flinger discs, the pitfalls of millions of inadequate old-style constant level lubricators and a veritable host of other basic issues are either not known or not addressed.

    Much money is lost when the basics are not understood. If each of 10 important or failure-prone components, practices, commissions or omissions in a pump were to reduce its reliability by 10%, raise 0.9 to the tenth power and convince yourself that you get less than 35% overall reliability. Staying with vulnerable components and not upgrading is a very poor choice indeed. Before looking for “high tech” and whatever else might be “icing on the cake,” a reliability-focused organization will learn to view every repair event as an opportunity to upgrade!

    Furthermore, if a manager is really serious about upgrading the knowledge base of a reliability workforce, he or she will cheerfully spend a few hundred dollars on solid textbooks that explain hundreds of these upgrade opportunities. He or she will know, or at least accept as fact, that implementing one or more of a number of highly cost-justified upgrade examples will definitely avoid failures. Since the average API pump failure event costs U.S. refineries in excess of $10,000 (Ref. 2), a single avoided failure represents a three-week payback for, say, a modest $600 spent on books.

    A good manager will probably insist that his/her reliability staffers read 200 textbook pages per yearÐthis adds up to a single page per work day. A good manager will not tolerate any excuses.

    Surely, a professional who has neither the time nor motivation to read a page a day will never help his employer move ahead.

    In the words of Mark Twain: “A man who chooses not to read is just as ignorant as a man who cannot read.” To which we might add that managers who choose not to make their people learn would serve their stakeholders better by going on permanent vacation.

    Before encouraging or allowing subordinates to simply “decorate the cake,” a good manager will see to it that the underlying foundation, that is, the cake itself, is edible. That implies that the basics are in place.

    References:

    1. Bloch, Heinz P.; “Slinger Rings Revisited,” Hydrocarbon Processing, August 2002
    2. Bloch, Heinz P. and Alan Budris; (2004) Pump User’s Handbook: Life Extension, The Fairmont Press, Inc., Lilburn, GA 30047, ISBN 0-88173-452-7
    3. Wilcock, Donald F., and Richard E. Booser, Bearing Design and Application, (1957), McGraw-Hill, New York, NY
    4. Bloch, Heinz P.; “Centrifugal Pump Cooling and Lubricant Application—A Technology Update,” International Pump User’s Symposium, Texas A&M University, Houston, TX, 2005
    5. Bloch, Heinz P., (1998) Improving Machinery Reliability, Third Edition, Gulf Publishing Company, Houston, TX, ISBN 0-88415-661-3

    Heinz P. Bloch is a professional engineer with over 43 years of experience in reliability engineering and maintenance cost reduction. He has written 14 comprehensive books on these subjects and continues to advise process plants worldwide on reliability im-provement and maintenance cost-reduction opportunities.

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    6:00 am
    December 1, 2005
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    Machinery Health Monitoring – Sense & Respond Logistics

    All eyes fixed on the future, the United States Navy looks to extend condition-based maintenance (CBM) technologies into the supply chain.

    The Vision

    In the year 2015, on some future naval platformÐperhaps USS BLUE SKYÐa machine will begin to falter in one of its pre-defined failure modes. This automatically will trigger a series of events to correct the failure and update the mission-readiness status of the platform in real-time. The “trigger” for some failure modes will, in fact, precede the actual functional failure, thus allowing for mitigating action to prevent an unplanned failure. This includes the pre-ordering of parts to complete necessary (and timely) maintenance without the inccurring of unnecessary logistics delays.

    The type of early warning outlined for the futuristic USS BLUE SKY also will allow a commander to assess the potential risk of the impending failure against the mission profile. That’s because a pre-validated, engineered work-order candidate, residing in a current or future database, will contain the required configuration data to identify the parts and tools necessary to accomplish the repair. In turn, the ship that work-order candidate is on will no longer be required to carry a large load of contingency spare parts, since the trigger mechanism will provide ample lead time for those parts to be put into the supply chain.

    Building blocks for the adjacent sidebar’s “BLUE SKY” vision of the future are in-place now—yet, much still remains to be done. Why should we do it?

    The answer lies in existing Chief of Naval Operations (CNO) policy and validated requirements for future naval platforms. Navy and and Department of Defense (DoD) initiatives, such as SHIPMAIN, CBM Plus, Engineering for Reduced Maintenance, Sense and Respond Logistics, Focused Logistics, and various Future Naval Capabilities provide vehicles and, in some cases, resources to achieve this future vision.

    The Navy’s Integrated Condition Assessment System (ICAS), as the program of record for shipboard machinery condition monitoring, provides the technology insertion opportunity to advance CBM and Sense and Respond capability. There is no silver bullet in any of the aforementioned efforts. Acquisition managers and technical warrant holders need to skillfully steer the work of these diverse, but related efforts, and harvest the offerings that support the requirements. There have been and will be successes to build upon, and there will be disappointments along the way. With no ready-made solutions available, there needs to be continued investment, engineering and trials, demonstrations and incremental fielding of advances via spiral development. The advances that are fielded will come largely from operating within the current framework of programs, organizations and policies.

    Background
    The case for condition-based maintenance (CBM) has been made. CNO effectively ended any debate in 1998 by issuing OPNAVINST 4790.16 (Condition Based Maintenance Policy). This instruction extended the more limited 1992 CBM directive (OPNAVINST 4700.7J) by mandating CBM application to all naval platforms.

    The intelligent application of sensing, processing and decision support technologies has a significant role in supporting Navy CBM policy. In the intervening years, there has been significant R&D investment in enabling technology, resulting in incremental improvement of fielded technologies and the associated maintenance and logistics applications, including, but not limited to, the previously referenced ICAS, the shipboard Preventive Maintenance System (PMS) Scheduler (SKED) and the Organizational Maintenance Management System—Next Generation (OMMS-NG). What has been missing is a tight integration between systems and linkage to supporting logistics and supply chain applications.

    Navy enterprise resource planning (ERP) implementation is on the horizon. However, as of this writing, (October 2005), there is no afloat ERP template.

    Application integration, to include available commercial off-the-shelf (COTS) products through development of software adapters, provides the vehicle to improve effectiveness and efficiency of today’s legacy applications onboard fielded platforms. Integration also will provide a stepping stone to the future of seamless information exchange among maintenance, logistics and operational readiness applications, both afloat and ashore.

    Development and acquisition of CBM-enabling technologies must follow the same reliability-centered maintenance (RCM) engineering principles of applicability and effectiveness as those used for development of maintenance requirements and tasks. A key concept is illustrated in Fig. 1, which plots resistance to failure versus operating age. In summary, a CBM enabling technology needs to be able to sufficiently detect the onset of a dominant failure mode (Potential Failure) in advance to prevent Functional Failure. In cases where this may not be possibleÐeither due to the nature of the failure and/or limitations of the technologyÐthere may still be value in automating the detection of a failure for automated generation of a pre-defined work-order candidate.

    Assuming, first, that RCM principles are employed for the identification of dominant failure modes to which enabling CBM technology can be applied, and second, that the technology being inserted is both applicable and effective, other issues need to be considered. Most significantly among these are information technology (IT) interface requirements and bandwidth limitations.

    The NAVSUP MHM – S&RL initiative
    As sponsored by the Naval Supply Systems Command (NAVSUP), the Machinery Health Monitoring, Sense and Respond Logistics (MHM – S&RL) system was de-signed to enable and demonstrate auto-nomous initiation of a technically validated, pre-formatted work-order candidate, populated with associated parts and related material. The work order trigger is based on the automated recognition and validation of a predefined failure mode on a machine of interest, resulting in actionable information being passed up-line to legacy maintenance and logistics systems.

    MHM-S&RL is focused on demonstrating this capability on the GSS 200 STAR Low Pressure Air Compressor (LPAC), a Navy design manufactured by both Dresser-Rand and Rix Industries. Failure modes are detected and processed using RLW Inc.’s S2NAP technology interfaced with legacy shipboard applications (ICAS, PMS SKED, and NTCSS suite). MIMOSA-based software adapter interfaces were developed under this project between S2NAP and ICAS, as well as between ICAS and PMS SKED.

    The team
    MHM – S&RL interfaces with multiple applications and networks. No single entity has all of the required expertise to develop the technology and interfaces. Under sponsorship of NAVSUP’s Command Science Advisor, the engineering group RLW assembled a multi-disciplinary team as shown in Table 1.

    Additionally, by way of acknowledgement, the Navy organizations listed in Table 2 also are involved in this initiative, either by lending support, defining requirements or providing data, technical reviews and comments in support of project objectives. Table 2 illustrates the imperative to involve the entire spectrum of fleet, maintenance and logistics organizations in development and demonstration projects such as MHM – S&RL.

    The system
    The MHM – S&RL System is a technology development and applications integration effort in support of Navy CBM. It is designed to automatically generate work-order candidates based on objective evidence of need for maintenance, as determined by intelligent machine monitoring.

    For a planned shipboard implementation, machine data for two individual LPACs in the same machinery space will be monitored by the S2NAP- embedded software device via both sensors and the LPACs’ control system. A health assessment is made based on this data, and if a predefined failure mode is recognized, an appropriate fault message is sent upstream, either using wireless 802.11b or wired Ethernet to ICAS. Raw sensor data also is passed to ICAS for display and trending. ICAS in turn, via an API, triggers a pre-formatted work-order candidate in OMMS NG, complete with required parts and the material (e.g., tools and consumables) necessary to effect the repair and cue the applicable work center via the SKED application utilizing the MIMOSA software adapter.

    The dominant, most-likely-to-occur, failure modes of the STAR LPAC identified by the MHM – S&RL System were determined through detailed analysis of 3-M History, a recent Type Commander Air Compressor Reliability Study and existing integrated class maintenance plan (ICMP) “Qualified” repair tasks (Q tasks). These failure modes were then validated through interviews with auxiliary-machinery work-center sailors aboard the USS BATAAN (LHD-5). The failure modes of interest are listed in Table 3.

    Each failure mode of interest (as listed in Table 3) is associated with current ICMP tasks and/or maintenance requirement cards (MRCs). Among the factors in their selection was consideration of the capability to realistically simulate occurrence of the failure in a demonstration environment. If a failure mode cannot be simulated, then there is little point in designing that failure into the demonstration system. This is a fact of life for development and demonstration of machinery health monitoring capabilities.

    System operation
    The MHM – S&RL System will communicate failure data from the S2NAP, integrated with the LPACs, to the ship’s Fiber Optic Data Multiplexing System (FODMS) Local Area Network (LAN), either via wired (Ethernet) or wireless (802.11b). Any wireless solution will incorporate the FIPS-140-2 security standard.

    The MHM – S&RL System also is applying the Machinery Information Management Open Systems Alliance (MIMOSA) standard as a software interface adapter to legacy applications onboard the ship for this demonstration. Specifically, the MIMOSA-based software adapter will enable interfacing between the S2NAP device and ICAS, as well as between the ICAS and SKED applications.

    The demonstration system is currently operational at the Land Based Engineering Site (LBES) in Philadelphia, PA. The initiative will conclude with a shipboard test in Spring of 2006, potentially associated with an ongoing Distance Support remote monitoring experimentation initiative. In order to demonstrate the system, additional hardware will be installed onboard ship, along with required software interfaces.

    In the Main Engine Room #2 (MER2), additional sensors (pressure sensors and accelerometers) and S2NAP devices will be installed on two LPACs (LPAC #2 and LPAC #3). The S2NAP will receive data directly from these added sensors, as well as from the LPACs’ Programmable Logic Controller (PLC). A network access device will be located in MER2 connected to the ship’s FODMS network to enable communications with ICAS. This network device will either be a wireless access point or an Ethernet switch, depending on the configuration allowed by the ship.

    A translator is used to pass data between the Linux-based S2NAP device and Windows-based shipboard applications. This device is being added to avoid software installations on other shipboard computers for this demonstration which would otherwise be required to facilitate communications; the translator allows for all of the software to reside on a single computer. This device can be located anywhere on the FODMS network. Its eventual location will be determined in consultation with the cognizant installation authority.

    The flow of data from the machine through legacy shipboard applications is shown in Fig. 2, which reflects the network architecture that will be implemented at the LBES in preparation for the shipboard demonstration.

    The SKED application currently resides on the IT21 network and is accessible via ICAS. This is the only bridge between the FODMS and the IT21 LANs.

    Antech Systems developed a demonstration release of SKED 3.1 to support this project. A pre-defined set of ‘U-Cards’ (standardized “Unscheduled Maintenance” cards emulating current MRCs) corresponding with the principal failure modes was developed by NAVSEALOGCEN (Norfolk Detachment). The U-Cards are integrated into the demonstration version of the SKED application. They will be triggered upon receipt of appropriate information from ICAS through the MIMOSA interface.

    The U-Cards also will identify parts and material (e.g., consumables and tools) required to complete each specific maintenance task. In addition to U-Cards, the system will trigger a pre-defined standardized work-order candidate (Form 4790-2K) for the applicable failure mode. This work-order candidate will then be routed to the Current Ships Maintenance Project (CSMP) through the OMMS-NG application.

    A MIMOSA interface to ICAS has been implemented in order to have failure modes that are already recognized by ICAS (i.e., clogged water injection filter – FM1, and fouled heat exchanger – FM10) passed by ICAS to SKED. Remaining failure modes (FM2-FM9) recognized by S2NAP then will be passed to ICAS for real-time display and for work -ordercandidate triggering in OMMS NG.

    Projected benefits
    There are many potential benefits to be obtained from the MHM – S&RL project. On the maintenance side, the time required for watch standers to take equipment readings will either be eliminated or substantially reduced by the application of sensors and remote monitoring. Additionally, some level of reduction is anticipated in the amount of scheduled (planned) maintenance required for the target equipment. There also will be some time savings from the automatic generation and management of 3-M documentation.

    On the supply side, the obvious benefit is that costly investment in large quantities of onboard spare parts can potentially be reduced. With planned maintenance reduced, the amount of parts and tools required to accomplish scheduled maintenance actions should also decrease.

    Finally, the amount of time required by shipboard maintenance and supply personnel to conduct technical research to identify required repair parts will diminish as this information is automatically provided on the U-Card associated with the pre-defined failure mode.

    To summarize
    At time of publication, this project is in the land-based demo phase. The associated Ship Change Documentation (SCD #558) is in the SHIPMAIN process for technical evaluation and the System Security Authorization Agreement (SSAA) process has been initiated. Additionally, the S2NAP platform has been evaluated for suitability to support the Distance Support initiative and is in the FIPS 140-2 validation process for wireless implementation.

    Future enhancements to this system planned for FY06 include: incorporating the evolving Ships’ Material Condition Model or “Corona Model”Ð Functional Index Numbers (FINs) and Equipment Operational Capability (EOC) values for equipments and failure modes; and follow-up fleet demonstration onboard an acquisition platform, most likely in the LPD-17 class. Furthermore, integration with ICAS’s Integrated Performance Analysis Reports (IPARs) will be explored.

    Ship configuration data matters. The capability described here is dependent on accurate configuration data from hull to hull. We know that the required level of accuracy does not exist, today. Perhaps this level of accuracy will become available through efforts such as Navy ERP and development of the Corona model.

    Network security is a big deal – and getting bigger. The Distance Support Innovation Lab at Naval Surface Warfare Center,, Crane Division, provided invaluable assistance in running a security vulnerability assessment on the S2NAP platform. The platform was subsequently tweaked, and it is now deemed suitable for shipboard network implementation. In general, advances made and lessons learned under projects like this will be made available to progressive programs such as the DDG Modernization Program, the ICAS Technology Refresh initiative, and acquisition (transformation) programs such as LPD-17, LCS, DD(X) and Navy ERP.

    Tightly coupling maintenance requirements and readiness imperatives with the supporting supply chain is a future state that is achievable through continued investment, experimentation, demonstration and fielding of enabling technologies. By employing and leveraging emerging technology, visions such as BLUE SKY can evolve into reality.

    Table 1. NAVSUP MHM – S&RL Team
    Company / Vendors/ Organizations Role
    RLW, Inc. Prime program mgmt., S2NAP developer, systems engineering, systems integration
    Uii Supply & logistics SME, program support
    Dresser-Rand GSS-200 STAR LPAC OEM – rebuild of LBES STAR LPAC
    Penn State University Applied Research Lab S2NAP Algorithm development
    DEI Group MIMOSA-based application adapter development, ICAS SME
    Antech Systems SKED application, PMS system SME
    Fortress Technologies FIPS 140-2 validated gateway vendor
    Value Point Networks Wireless access point vendor
    Naval Surface Warfare Center, Carderock Div., Philadelphia Detachment ICAS SME, application integration, Land Based Engineering Site support
    Table 2. Organizational Interfaces
    Organization Role
    NAVSEA (SEA 04RM) Access to Integrated Class Maintenance Plan (ICMP), Planned Maintenance System (PMS) data, functional architecture validation, SKED application
    NAVSEA (SEA 05Z53) POC for Ship Change Documentation (SCD) process, functional architecture validation
    Commander Naval Surface Forces
    (CNSF N43)
    Access to USS BATAAN for LPAC run data
    NAVSEALOGCEN Det Demonstration ‘U Card’ set development
    NAVSEA (PMS 400 FT) Ship Change Documentation review for DDG demo SPAWAR Codes 150/151 and MOA for Navy Tactical Command Support System (NTCSS) applications suite and SPAWARSYSCEN Norfolk software/test database installation
    NAVSEA (SEA 03) NTCSS suite MOA signatory Distance Support Office
    NAVSEA, Naval Surface Warfare Center, Crane Division – Distance Support Innovation Lab Security vulnerability assessment and Integration testing
    Navy Inventory Control Point (NAVICP) Allowance Parts List (APL) and Secondary Item support Mechanicsburg PA
    Table 3. STAR LPAC Failure Modes of Interest
    Number Failure Mode Description
    1 Clogged Water Injection Filter
    2 Clogged Muffler
    3 Relief Valve Actuation Failure (Tank)
    4 Clogged Air Inlet Filter
    5 Machinery Alignment – Coupling / Shaft
    6 Clogged Water Inlet Strainer
    7 Solenoid Valve Actuation Failure (Injection)
    8 Solenoid Valve Actuation Failure (Unloader)
    9 Compressor Bearings Worn
    10 Heat Exchanger Fouled

    References

    1. “Condition Based Maintenance for Shipboard Machinery,” G. William Nickerson. Proceedings of the 44th Meeting of the Machinery Failures Prevention Group, 1990.
    2. Condition Based Maintenance Policy, OPNAVINST 4790.16 (Washington DC: Department of the Navy, Office of the Chief of Naval Operations, 1998).
    3. “Applying RCM Principles in the Selection of CBM-Enabling Technologies,” Kenneth S. Jacobs. Proceedings of the Annual DoD Maintenance Symposium, 1999.
    4. “Planned Maintenance System: Development of Maintenance Requirements Cards,” Maintnance Index Pages and Associated Documentation, Mil-P-24534(Navy), 1985.
    5. “Taking the Integrated Condition Assessment System to the Year 2010, ” Michael DiUlio, Chris Savage, Brian Finley, Eric Schneider. Proceedings from Thirteenth International Ship Control Systems Symposium (SCSS) in Orlando, FL, April 2003.
    6. “Enterprise Remote Monitoring (ICAS & Distance Support), Tomorrow’s Vision Being Executed Every Day.” Christopher Savage, Michael DiUlio, Brian Finley, Ken Krooner, Pete Martinez, Pat Horton. Proceedings from 2005 ASNE Fleet Maintenance Symposium.

    Joe Gaines is currently the Office of Naval Research (ONR) Science Advisor to the Naval Supply Systems Command (NAVSUP). In this capacity, he is the senior representative of the Commander, RADM Daniel H. Stone, for all Science and Technology (S&T) issues. He also ia responsible for the Navy Logistics Productivity Program (a logistics R&D program) and the NAVSUP Small Business Innovation Research (SBIR) program. Gaines is the command’s representative to the Virtual SYSCOM Systems Engineering Steering Group and Technical Authority Board. He established the Logistics R&D Executive Steering Group at NAVSUP with senior leadership representation from across the NAVSUP enterprise. E-mail: joe.gaines@navy.mil

    Peter J. Sisa joined RLW, Inc., a small business specializing in embedded software solutions, in May 2004. Today, he manages the NAVSUP sponsored S2NAP Machinery Health Monitoring Sense & Respond Logistics initiative for RLW, in addition to the related “Smart Spaces” Small Business Innovative Research project. He recently has served as a representative on the Office of the Secretary of Defense’s CBM Plus working group – representing DD(X) as a Navy’s Ôselect’ platform for CBM capabilities. Prior to joining RLW, Sisa, held a number of positions with American Management System, in Fairfax VA, He retired from naval service in 1997, with extensive operational and staff experience, including duty on Chief of Naval Operations staff and with the Office of Naval Research. He holds a B.S. from the U.S. Naval Academy and an MPA from Troy State University. E-mail: PSisa@rlwinc.com

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    235

    6:00 am
    November 1, 2005
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    Make Sure Your Message Is Understood

    Bonjour! Bongiorno! Buenos dias! Salut! Hola! No matter what language you speak, it all translates to the same thing, right? Well, you might want to rethink that belief.

    A common challenge across many industries, when it comes to corporate growth, is how to successfully communicate a specific message in another language. While English is the accepted language of world finance and corporate operations, when your business takes you to another country, you must be willing and able to adapt. This is especially true in the case of manufacturing and maintenance, where a majority of employees are local men and women just trying to make a living.

    There is no question that everyone prefers to be trained, lectured, facilitated, coached and otherwise communicated with in his or her native tongue. We Americans are probably more demanding of this than any group of people.

    It is not unusual to see, for example, an American on business or vacation abroad who becomes indignant because a local shop owner doesn’t do business in English. Could it be that we simply don’t make the connection that over there WE are the foreigners!? The truth of the matter is that regardless of which country we may visit, it should be incumbent upon us to at least attempt the local language. This simple—sometimes embarrassing—act will allow you to garner an immense amount of respect with the local population. And, it will provide a great measure of credibility with your client in a foreign country.

    Remember that if your work takes you out of the United States, you generally can’t make the transition without some local help from within the country you are visiting. Presentations and training materials must be translated—and should be done by someone who “speaks the lingo” of your profession.

    Take a look at any English-to-“X” dictionary and see just how many engineering, maintenance or manufacturing-unique words it contains. Unfortunately, there are very few. Yet, it is utterly impossible to communicate any principles or theories to a plant, maintenance, materials, reliability or other professional without using these technical words.

    If you can’t find a dictionary of technical or engineering terms for your language requirements, you have no option but to find a local resource—or give up the client. It’s your choice.

    Most maintenance professionals in the U.S. understand the theory, process and application of the Responsibility, Accountability, Support and Information (RASI) model. In every process, each step requires someone who is “Responsible” for getting it done (the Doer) and someone who is ultimately “Accountable” for this step in the process (the Buck Stops Here). I was embarking on a coaching session at a client site in Quebec, in the beginning stages of RASI development, when several members of our client focus team noted (in French), “But there is no difference between Responsibility and Accountability.” As it turned out, they were correct. If you look up the word “accountable” in your French Quebec-American dictionary, you will find that the primary definition is, indeed, “responsible.”

    We were able to overcome this dilemma in Quebec by re-defining the “R”and the “A” in the classic RASI model. We decided that the “R” would represent the “Accountable” person and the “A” would represent the “Actor” (the Doer), or “Responsible” person in the model. In this way, we were able to retain the RASI title for the model while still accurately representing each of the letters in the acronym. This same approach should work well with many other languages as a company may continue expanding its business into the global market.

    Many language scholars would agree that, while most Americans struggle with any foreign language, English—and American English, in particular—is, in fact the hardest language to master. We have many words that are spelled the same, but which have several different meanings, as well as many different words with the same root meaning.

    The message here is that if you have designs on expanding your business or service outside of the U.S., don’t get caught with your Funk & Wagnalls down!

    Bob Call is a Senior Consultant with Life Cycle Engineering. He has over 20 years experience in maintenance and reliability, specializing in project management, process improvement and supervisory skills training. E-mail bcall@LCE.com4360

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