Guide to Predictive Maintenance--Establishing a Predictive Maintenance Program [part 1]

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The decision to establish a predictive maintenance program is the first step toward controlling maintenance costs and improving process efficiency in your plant. Now what do you do? Numerous predictive maintenance programs can serve as models for implementing a successful predictive maintenance program. Unfortunately, many programs were aborted within the first three years because a clear set of goals and objectives were not established before the program was implemented. Implementing a total-plant predictive maintenance program is expensive. After the initial capital cost of instrumentation and systems, a substantial annual labor cost is required to maintain the program.

To be successful, a predictive maintenance program must be able to quantify the cost-benefit generated by the program. This goal can be achieved if the program is properly established, uses the proper predictive maintenance techniques, and has measurable benefits. The amount of effort expended to initially establish the program is directly proportional to its success or failure.

GOALS, OBJECTIVES, AND BENEFITS

Constructive actions issue from a well-established purpose. It’s important that the goals and objectives of a predictive maintenance program be fully developed and adopted by the personnel who perform the program and upper management of the plant.

A predictive maintenance program is not an excuse to buy sophisticated, expensive equipment. Neither is the purpose of the program to keep people busy measuring and reviewing data from the various machines, equipment, and systems within the plant.

The purpose of predictive maintenance is to minimize unscheduled equipment failures, maintenance costs, and lost production. It’s also intended to improve the production efficiency and product quality in the plant. This is accomplished by regular monitoring of the mechanical condition, machine and process efficiencies, and other parameters that define the operating condition of the plant. Using the data acquired from critical plant equipment, incipient problems are identified and corrective actions taken to improve the reliability, availability, and productivity of the plant.

Specific goals and objectives will vary from plant to plant; however, we will provide an example that illustrates the process. Before goals and objectives can be developed for your plant, you must determine the existing maintenance costs and other parameters that will establish a reference or baseline data set. Because most plants don’t track the true cost of maintenance, this may be the most difficult part of establishing a predictive maintenance program.

At a minimum, your baseline data set should include the staffing, overhead, overtime premiums, and other payroll costs of the maintenance department. It should also include all maintenance-related contract services, excluding janitorial, and the total costs of spare parts inventories. The baseline should also include the percentage of unscheduled versus scheduled maintenance repairs, actual repair costs on critical plant equipment, and the annual availability of the plant.

This baseline should include the incremental costs of production created by catastrophic machine failures and other parameters. If they are available or can be obtained, they will help greatly in establishing a valid baseline. The long-term objectives of a predictive maintenance program are to:

  • Eliminate unnecessary maintenance.
  • Reduce lost production caused by failures.
  • Reduce repair parts inventory.
  • Increase process efficiency.
  • Improve product quality.
  • Extend the operating life of plant systems.
  • Increase production capacity.
  • Reduce overall maintenance costs.
  • Increase overall profits.

Just stating these objectives, however, won’t make them happen or provide the means of measuring the program's success. Establish specific objectives (e.g., reduce unscheduled maintenance by 20 percent or increase production capacity by 15 percent). In addition to quantifying the expected goals, define the methods that will be used to accomplish each objective and the means that can be used to measure the actual results.

FUNCTIONAL REQUIREMENTS

Functional requirements will vary with the size and complexity of the plant, company, or corporation; however, minimal requirements must be met regardless of the variables. These requirements are management support, dedicated and accountable personnel, efficient data collection and analysis procedures, and a viable database.

Management Support

Implementing a predictive maintenance program will require an investment in both capital equipment and labor. If a program is to get started and survive to accomplish its intended goals, management must be willing to commit the necessary resources.

Management must also insist on the adoption of vital record-keeping and information exchange procedures that are critical to program success and are outside the control of the maintenance department. In most aborted programs, management committed to the initial investment for capital equipment but did not invest the resources required for training, consulting support, and in-house staffing that are essential to success.

Several programs have been aborted during the time between 18 and 24 months after implementation. They were not aborted because the program failed to achieve the desired results, but rather they failed because upper management did not clearly under stand how the program worked.

During the first 12 months, most predictive maintenance programs identify numerous problems in plant machinery and systems. Therefore, the reports and recommendations for corrective actions generated by the predictive maintenance group are highly visible.

After the initial 12 to 18 months, most of the serious plant problems have been resolved and the reports begin to show little need for corrective actions. Without a clear under standing of this normal cycle and the means of quantifying the achievements of the predictive maintenance program, upper management often concludes that the program is not providing sufficient benefits to justify the continued investment in staffing.

Dedicated and Accountable Personnel

All successful programs are built around a full-time predictive maintenance team.

Some of these teams may cover multiple plants and some monitor only one; however, every successful program has a dedicated team that can concentrate its full attention on achieving the objectives established for the program. Even though a few successful programs have been structured around part-time personnel, this approach is not recommended. All too often, part-time personnel won’t or cannot maintain the monitoring and analysis frequency that is critical to success.

The accountability expected of the predictive maintenance group is another critical factor to program effectiveness. If measures of program effectiveness are not established, neither management nor program personnel can determine if the program's potential is being achieved.

Efficient Data Collection and Analysis Procedures

Efficient procedures can be established if adequate instrumentation is available and the monitoring tasks are structured to emphasize program goals. A well-planned program should not be structured so that all machines and equipment in the plant receive the same scrutiny. Typical predictive maintenance programs monitor from 50 to 500 machine-trains in a given plant.

Some of the machine-trains are more critical to the continued, efficient operation of the plant than others. The predictive maintenance program should be set up to concentrate the program's efforts in the areas that will provide maximum results. The use of microprocessor- and PC-based predictive maintenance systems greatly improves the data collection and data management functions required for a successful program.

These systems can also provide efficient data analysis; however, procedures that define the methods, schedule, and other parameter of data acquisition, analysis, and report generation must also be included in the program definition.

Viable Database

The methods and systems that you choose for your program and the initial program development will largely determine the success or failure of predictive maintenance in your plant. Proper implementation of a predictive maintenance program is not easy. It will require a great deal of thought and-perhaps for the first time-a complete understanding of the operation of the various systems and machinery in your plant.

The initial database development required to successfully implement a predictive maintenance program will require several staffing months of effort. The result of the extensive labor required to properly establish a predictive database often results in either a poor or incomplete database. In some cases, the program is discontinued because of staff limitations. If the extensive labor required to establish a database is not available in-house, consultants can provide the knowledge and labor required to accomplish this task.

The ideal situation would be to have the predictive systems vendor establish a viable database as part of the initial capital equipment purchase. This service is offered by a few of the systems vendors. Unfortunately, many predictive maintenance programs have failed because these important first critical steps were omitted or ignored. There are a variety of beneficial technologies and predictive maintenance systems. How do you decide which method and system to use? A vibration-based predictive maintenance program is the most difficult to properly establish and requires much more effort than any of the other techniques. It will also provide the most return on investment. Too many of the vibration-based programs fail to use the full capability of the predictive maintenance tool. They ignore the automatic diagnostic power that is built into most of the microprocessor-based systems and rely instead on manual interpretation of all data.

The first step is to determine the types of plant equipment and systems that are to be included in your program. A plant survey of your process equipment should list every critical component within the plant and its impact on both production capacity and maintenance costs. A plant process layout is invaluable during this phase of program development. It’s easy to omit critical machines or components during the audit; therefore, care should be taken to ensure that all components that can limit production capacity are included in your list.

The listing of plant equipment should be ordered into the following classes depending on the equipment's impact on production capacity or maintenance cost: Class I, essential; Class II, critical; Class III, serious; and Class IV, others.

Class I, or essential, machinery or equipment must be online for continued plant operation. Loss of any one of these components will result in a plant outage and total loss of production. Plant equipment that has excessive repair costs or repair parts lead-time should also be included in the essential classification.

Class II, or critical, machinery would severely limit production capacity. As a rule of thumb, loss of critical machinery would reduce production capacity by 30 percent or more. Also included in the critical classification are machines or systems with chronic maintenance histories or that have high repair or replacement costs.

Class III, or serious, machinery includes major plant equipment that does not have a dramatic impact on production but that contributes to maintenance costs. An example of the serious classification would be a redundant system.

Because the inline spare could maintain production, loss of one component would not affect production; however, the failure would have a direct impact on maintenance cost.

Class IV machinery includes other plant equipment that has a proven history of impacting either production or maintenance costs. All equipment in this classification must be evaluated to determine whether routine monitoring is cost effective. In some cases, replacement costs are lower than the annual costs required to monitor machinery in this classification.

The completed list should include every machine, system, or other plant equipment that has or could have a serious impact on the availability and process efficiency of your plant. The next step is to determine the best method or technique for cost effectively monitoring the operating condition of each item on the list. To select the best methods for regular monitoring, you should consider the dynamics of operation and normal failure modes of each machine or system to be included in the program.

A clear understanding of the operating characteristics and failure modes will provide the answer to which predictive maintenance method should be used.

Most predictive maintenance programs use vibration monitoring as the principal technique. Visual inspection, process parameters, ultrasonics, and limited thermographic techniques should also be added to the in-house program. The initial cost of systems and advanced training required by full thermographic and tribology techniques prohibits their inclusion into in-house programs. Plants that require these techniques normally rely on outside contractors to provide the instrumentation and expertise required.

Because of the almost unlimited numbers and types of machinery and systems used in industry, it’s impossible to cover every one in this book; however, Section 7 pro vides a cross-section that illustrates the process used to identify the monitoring parameters for plant equipment.

SELLING PREDICTIVE MAINTENANCE PROGRAMS

Justification of a predictive maintenance program to corporate management is difficult, but convincing the entire workforce to embrace improvement is almost impossible. Because few companies can afford to invest the financial resources and staffing required to improve the effectiveness of their plants, corporate management has a built-in resistance to change. Couple this resistance with the natural aversion to change that dominates most workforces, and selling improvement becomes very difficult.

How do you convince corporate management and the workforce to invest in predictive maintenance improvement?

Six Keys to Success:

There are six keys to successful justification and implementation of a continuous improvement program: (1) formulating a detailed program plan, (2) knowing your audience, (3) creating an implementation plan, (4) doing your homework, (5) taking a holistic view, and (6) getting absolute buy-in.

Formulating a Detailed Program Plan:

Don’t shortcut the program plan. It must be a concise, detailed document that pro vides clear direction for the program. Remember that the plan should be a living document. It should be upgraded or modified as the program matures.

Concise Goals and Objectives. Your justification package must include a clear, concise game plan. Corporate and plant management expect you to understand the problems that reduce plant effectiveness and to offer a well-defined plan to correct these problems.

The first step in reaching this understanding is conducting a comprehensive evaluation of your facility. Evaluation of your plant will be the most difficult part of your preparation. Cost-accounting and performance tracking systems are not set up to track all of the indices that define performance. At best, there will be some data for yield, unscheduled delays, and traditional costs, such as maintenance, labor, and material, but in most cases, the data will be extremely limited and may not provide a true picture.

Typically, the reports generated by these tracking programs are compartmentalized and will only disclose part of the true picture. For example, delays will be contained in several reports. Maintenance delays will be divided into at least two reports: unscheduled and planned downtime. Operating delays will be in another report or reports, and material control in yet another. To get a true picture of downtime, you must consolidate all nonproduction time into one report. The same is true of yield or product quality. At one client's facility, we found 57 different yield reports, none of which agreed. As you can imagine, developing a true picture of the yield for this plant was extremely difficult.

Don’t use artificial limits; normalize data to the physical limits that bound plant performance. For example, a plant that operates continuously has a physical limit of 8,760 production hours in a calendar year. Capacity, availability, and all other performance indices should be based on this physical limit, not an arbitrary number of hours that are the common industry practice. Data should also be normalized to remove other variables, such as selling price and sales volume.

Self-evaluation is extremely difficult. Each of us has built-in perceptions that influence how we interpret data. These perceptions are deep-rooted and may prevent you from developing an honest evaluation of plant effectiveness. One of my favorite examples is maintenance planning. Most of my clients state absolutely that they plan at least 80 percent of their maintenance activities. Few, if any, actually plan 10 percent.

At best, 80 percent of their maintenance tasks may be listed on a written schedule, but few are effectively planned.

How do you get around these perceptions? There is no easy answer. You must either make a commitment to honestly evaluate the effectiveness of each function and area within your plant or hire a qualified consultant to conduct the evaluation for you.

Accurate Cost Estimates. Many programs fail simply because costs, such as training, infrastructure, and required staffing, are underestimated. Make every effort to identify and quantify these costs as part of your justification.

Realistic Return-on-Investment Milestones. A clear set of project milestones will help ensure continuation of your program. If corporate executives can see measurable improvements, the probability of continuation and long-term success is greatly improved.

Tracking and Evaluation Plan. Selling the program is not finished when the justification package is approved. You must continue to sell the program for its entire life.

A well-defined tracking and evaluation plan, coupled with clearly defined milestones, will greatly improve your chance of success. Remember: Never stop selling the program. Newsletters, video presentations, periodic reports, and personal contacts are essential to the continuation and success of your program.

Knowing Your Audience:

There are at least five levels of selling that must be accomplished for a successful program: (1) corporate management, (2) plant management, (3) division management, (4) line supervision, and (5) the hourly workforce. Your justification package must address all five levels of approval. Benefits must address the unique concerns of each of these five groups.

Corporate Management. Corporate management must make the first commitment.

Most improvement programs are expensive and will require corporate-level approval.

Therefore, your initial justification package must be prepared for this critical audience.

A successful justification package must be couched in terms that these individuals will understand and accept. Remember that corporate managers are driven by one and only one thing-the bottom line. Your company's president is evaluated by the stockholders and board of directors based solely on the overall profitability of the corporation. Your justification package must presents the means to improve profitability.

Improvements in terms of staffing per unit produced, increased yields, and reduced overall costs are the key phrases that must be used to gain approval. Corporate-level executives are looking for ways to improve their perceived value. You must supply these means as part of your plan.

Plant Management. To a lesser degree, plant executives are driven by the same stimuli as those at corporate level. Although they tend to have a broader view of plant operations, plant-level managers want to see justification couched in terms of total plant.

One other factor is critical to success at this level. Most plant executives don’t have a maintenance background. In fact, most have a built-in prejudice against the maintenance organization. Many are convinced that maintenance is the root-cause of the plant's poor performance. If your justification package and program plan are defined in maintenance terms or you limit improvements to traditional maintenance issues, your chances for approval will be severely limited.

Division Management. Total, absolute support of division managers is crucial. In most plants, the division manager controls all of the resources required to implement change. Regardless of the organizational structure, this level of management has control of the operating and maintenance budget as well as allocation of the work force. Without this support, your program cannot succeed. If you can gain this support, you are well on your way to success.

Line Supervision. In many plants, first-line supervisors are the most resistant to change. In some cases, this resistance is driven by insecurity. Generally, this segment of the workforce is the first to be cut during reengineering or downsizing. As a result, their natural tendency is to resist any new program that is touted as a plant improvement program.

In other plants, supervisors have been conditioned by a long history of failed attempts to correct plant problems. The myriad "programs of the month," which have become the norm in our domestic plants, have resulted in widespread frustration throughout the workforce. This frustration is especially true of first-line supervisors.

Regardless of the reason for their resistance, first-line supervisors must be convinced to provide absolute, unconditional support. Your program plan must include the motivation and rationale that will convince this critical part of the workforce to get involved and to become a positive force that will ensure success.

Hourly Workforce. Most programs fail to address the final audience-the hourly workforce. This mistake is absolutely fatal. Without the total support and assistance of the hourly workers, nothing can change. Your program plan must include specific means of winning both initial and long-term support from the workers.

The best way to accomplish this key milestone is to include their representatives in the program development phase and continue their involvement throughout the program. Think like your audience. Include specific information and data that will be understood by your audience. Corporate executives will relate to staffing per ton, working ratios, and bottom-line profit. Hourly workers will relate to improved working conditions and higher incentives that result from improved yields. Think like your audience and your potential for approval will be improved.

Creating an Implementation Plan:

A concise, detailed program plan is the most important part of your program. Without a good plan, most programs fail within the first year. The plan must include well defined goals and objectives. Use extreme caution to ensure that goals are achievable within the prescribed timeline.

Few plants can afford to lay out major capital investments that are required by improvement programs. Therefore, your program should use a phased approach.

Specific tasks should be defined in a logical sequence that minimizes investment and maximizes returns. Return on investment must be the driving force behind your timeline and implementation approach.

Make sure that all tasks required to accomplish your program are included in the program plan. Each task should include a clear definition, including a deliverable; assign responsibility to a specific individual; and indicate a start and end date. In addition, each task description should include all tools, skills, and support required.

Return on Investment. A viable continuous improvement program must be designed to pay for itself. Don’t be misled; this is not an arbitrary management view. Your profit and loss statement clearly shows that the financial resources required to support an improvement program are simply not available. Every decision made must be driven by this single factor-return on investment. Unless your program can definitely pay for itself, it should not be implemented.

Frankly, most maintenance improvement programs won’t pay for themselves. Traditional applications of predictive maintenance, reliability-centered maintenance, total productive maintenance, and a myriad of others are not capable of generating enough return to justify implementation. The only proven means of generating a positive return is to include the total plant in your program.

Do Not Overstate Benefits. The natural tendency is to define outlandish benefits that will be generated by the program. In some instances, these projections are based on data provided by consultants or vendors of improvement systems, like predictive maintenance, and are simply not valid. In other cases, you may overstate expected return-on-investment numbers to ensure approval. This is perhaps the greatest mistake that can be made. Remember that your justification will establish expectations that you must meet. If you overstate benefits, you will be expected to deliver. In conclusion, make sure that you prepare your justification and plan to assure success.

Doing Your Homework:

An honest, in-depth evaluation of your plant is an absolute requirement. This evaluation provides two essential data sets: (1) it defines the specific areas that need to be improved, and (2) it provides a baseline or benchmark that can be used to measure the success of your program.

Taking a Holistic View:

Don’t limit your plant evaluation to a single plant function or deficiency. If you really want to improve the performance of your plant, look at every function or variable that has a direct or indirect impact on performance. Your evaluation should include these critical plant functions: sales, purchasing, engineering, production, maintenance, human resources, and management. Unless you take a holistic view, your program and its benefits will be limited.

Getting Absolute Buy-In:

The total, absolute support of all employees within your plant is essential to success.

You must gain their support or the program will fail. This task must be ongoing for the duration of your program. You must constantly reinforce this commitment or some portion of the workforce will lose interest and you will lose their support.

SELECTING A PREDICTIVE MAINTENANCE SYSTEM

After developing the requirements for a comprehensive predictive maintenance program, the next step is to select the hardware and software system that will most cost-effectively support your program. Because most plants will require a combination of techniques (e.g., vibration, thermography, tribology), the system should be able to provide support for all of the required techniques. Because a single system that will support all of the predictive maintenance is not available, you must decide on the specific techniques that must be used to support your program. Some of the techniques may have to be eliminated to enable the use of a single predictive maintenance system.

In most cases, though, two independent systems will be required to support the monitoring requirements in your plant.

Most plants can be cost-effectively monitored using a microprocessor-based system designed to use vibration, process parameters, visual inspection, and limited infrared temperature monitoring. Plants with large populations of heat transfer systems and electrical equipment will need to add a full thermal imaging system in order to meet the total-plant requirements for a full predictive maintenance program. Plants with fewer systems that require full infrared imaging may elect to contract this portion of the predictive maintenance program. This option will eliminate the need for an additional system. A typical microprocessor-based system will consist of four main components: a meter or data logger, a host computer, transducers, and a software program.

Each component is important, but the total capability must be evaluated to achieve a system that will support a successful program.

Fundamental System Requirements

The first step in selecting the predictive maintenance system that will be used in your plant is to develop a list of the specific features or capabilities the system must have to support your program. At a minimum, the total system must have the following capabilities:

  • User-friendly software and hardware
  • Automated data acquisition
  • Automated data management and trending
  • Flexibility
  • Reliability
  • Accuracy
  • Training and technical support

User-Friendly Software and Hardware:

The premise of predictive maintenance is that existing plant staff must be able to understand the operation of both the data logger and the software program. Because plant staff normally has little, if any, computer or microprocessor background, the system must use simple, straightforward operation of both the data acquisition instrument and software. Complex systems, even if they provide advanced diagnostic capabilities, may not be accepted by plant staff and therefore won’t provide the basis for a long-term predictive maintenance program.

Automated Data Acquisition:

The object of using microprocessor-based systems is to remove any potential for human error, reduce staffing, and automate as much as possible the acquisition of vibration, process, and other data that will provide a viable predictive maintenance database. Therefore, the system must be able to automatically select and set monitoring parameters without user input. The ideal system would limit user input to a single operation, but this is not totally possible with today's technology.

Automated Data Management and Trending:

The amount of data required to support a total-plant predictive maintenance program is massive and will continue to increase over the life of the program. The system must be able to store, trend, and recall the data in multiple formats that will enable the user to monitor, trend, and analyze the condition of all plant equipment included in the program. The system should be able to provide long-term trend data for the life of the program. Some of the microprocessor-based systems limit trends to a maximum of 26 data sets and will severely limit the decision-making capabilities of the predictive maintenance staff. Limiting trend data to a finite number of data sets eliminated the ability to determine the most cost-effective point to replace a machine rather than let it continue in operation.

Flexibility:

Not all machines or plant equipment are the same, and neither are the best methods of monitoring their condition equal. Therefore, the selected system must be able to support as many of the different techniques as possible. At a minimum, the system should be capable of obtaining, storing, and presenting data acquired from all vibration and process transducers and provide an accurate interpretation of the measured values in user-friendly terms. The minimum requirement for vibration-monitoring systems must include the ability to acquire filter broadband, select narrowband, time traces, and high-resolution signature data using any commercially available transducer. Systems that are limited to broadband monitoring or to a single type of transducer cannot support the minimum requirements of a predictive maintenance program.

The added capability of calculating unknown values based on measured inputs will greatly enhance the system's capabilities. For example, neither fouling factor nor efficiency of a heat exchanger can be directly measured. A predictive maintenance system that can automatically calculate these values based on the measured flow, pressure, and temperature data would enable the program to automatically trend, log, and alarm deviations in these unknown, critical parameters.

Reliability:

The selected hardware and software must be proven in actual field use to ensure their reliability. The introduction of microprocessor-based predictive maintenance systems is still relatively new, and it’s important that you evaluate the field history of a system before purchase. Ask for a list of users and talk to the people who are already using the systems. This is a sure way to evaluate the strengths and weaknesses of a particular system before you make a capital investment.

Accuracy:

Decisions on machine-train or plant system condition will be made based on the data acquired and reported by the predictive maintenance system. It must be accurate and repeatable. Errors can be input by the microprocessor and software as well as by the operators. The accuracy of commercially available predictive maintenance systems varies. Although most will provide at least minimum acceptable accuracy, some are well below the acceptable level.

It’s extremely difficult for the typical plant user to determine the level of accuracy of the various instruments that are available for predictive maintenance. Vendor literature and salespeople will attempt to assure the potential user that their system is the best, most accurate, and so on. The best way to separate fact from fiction is to compare the various systems in your plant. Most vendors will provide a system on consignment for up to 30 days. This will provide sufficient time for your staff to evaluate each of the potential systems before purchase. Next>>

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