Predictive Maintenance: Promises & Pitfalls Key Roles, Techniques and Benefits of Predictive Maintenance Program

Predictive Maintenance: Promises & Pitfalls

Predictive maintenance is often misunderstood and misused program. Most users define it as a means to prevent catastrophic failure of critical rotating machinery while its role is to be a part of an integrated, total plant performance management program. As such, it can provide the means to improve the production capacity, product quality, and overall effectiveness of our manufacturing and production plants.

Or to be exact in definition, Predictive maintenance is a management technique that uses regular evaluation of the actual operating condition of plant equipment, production systems, and plant management functions to optimize total plant operation.

The output of a predictive maintenance program is data. Until action is taken to resolve the deviations or problems revealed by the program, plant performance cannot be improved. Therefore, a management philosophy that is committed to plant improvement must exist before any meaningful benefit can be derived. Without the absolute commitment and support of senior management and the full cooperation of all plant functions, a predictive maintenance program cannot provide the means to resolve poor plant performance.

Properly used, predictive maintenance can identify most, if not all, factors that limit effectiveness and efficiency of the total plant.

What can be achieved with Predictive maintenance program?

  • It can minimize unscheduled breakdowns of all mechanical equipment in the plant and ensure that repaired equipment is in acceptable mechanical condition.
  • It can also identify machine-train problems before they become serious.
  • Most problems can be minimized if they are detected and repaired early.
  • Normal mechanical failure modes degrade at a speed directly proportional to their severity. If the problem is detected early, major repairs, in most instances, can be prevented.

To achieve these goals, the predictive maintenance program must correctly identify the root cause of incipient problems. Many of the established programs do not meet this fundamental requirement. Precipitated by the claims of predictive maintenance system vendors, many programs are established on simplistic monitoring methods that identify the symptom rather than the real cause of problems. In these instances, the derived benefits that are achieved are greatly diminished. In fact, many of these programs fail because maintenance managers lose confidence in the program’s ability to accurately detect incipient problems.

Key roles of predictive maintenance

Production management

Predictive maintenance can be an invaluable production management tool. The data derived from a comprehensive program can provide the information needed to increase production capacity, product quality, and the overall effectiveness of the production function.
Production efficiency is directly dependent on a number of machine-related factors.

Predictive maintenance can provide the data needed to achieve optimum, consistent reliability, capacity, and efficiency from critical production systems.

Product quality and total production costs is another area where predictive maintenance can benefit production management. Regular evaluation of critical production systems can anticipate potential problems that would result in reduced product quality and an increase in overall production costs. While the only output of the predictive maintenance program is data, this information can be used to correct production problems that directly affect the effectiveness and efficiency of the production department.

Quality Improvement

Most product quality problems are the direct result of

  • production systems with inherent problems,
  • poor operating procedures,
  • improper maintenance, or
  • defective raw materials.

Predictive maintenance can isolate this type of problem and provide the data required to correct many of the problems that result in reduced product quality.
A comprehensive program will use a combination of data, such as vibration, thermography, tribology process parameters, and operating dynamics, to anticipate deviations from optimum operating condition of critical plant systems before they can affect product quality, production capacity, or total production costs.

Predictive Maintenance Techniques

There are a variety of technologies that can and should be used as part of a comprehensive predictive maintenance program. Since mechanical systems or machines account for the majority of plant equipment, vibration monitoring is generally the key component of most predictive maintenance programs. However, vibration monitoring cannot provide all of the information that will be required for a successful predictive maintenance program.

Hence, as previously noted, it must be iterated that a comprehensive predictive maintenance program must include other monitoring and diagnostic techniques. These techniques include:

  • vibration monitoring - Vibration analysis is the dominant technique used for predictive maintenance management. Since the greatest population of typical plant equipment is mechanical, this technique has the widest application and benefits in a total plant program. This technique uses the noise or vibration created by mechanical equipment and in some cases by plant systems to determine their actual condition.
  • thermography - It uses instrumentation designed to monitor the emission of infrared energy, i.e., temperature, to determine their operating condition. By detecting thermal anomalies, i.e., areas that are hotter or colder than they should be, an experienced surveyor can locate and define incipient problems within the plant.
  • tribology - it is the general term that refers to design and operating dynamics of the lubrication .
  • process parameters,
  • visual inspection, and
  • other nondestructive testing techniques.

Process parameters and Predictive maintenance

Many plants do not consider machine or systems efficiency to be part of the maintenance responsibility. However, machinery that is not operating within acceptable efficiency parameters severely limits the productivity of many plants. Therefore, a comprehensive predictive maintenance program should include routine monitoring of process parameters. As an example of the importance of process parameters monitoring, consider a process pump that may be critical to plant operation.

Vibration-based predictive maintenance will provide the mechanical condition of the pump and
infrared imaging will provide the condition of the electric motor and bearings. Neither provides any indication of the operating efficiency of the pump. Therefore, the pump could be operating at less than 50 percent efficiency and the predictive maintenance program would not detect the problem. Process inefficiencies, like the example cited, are often the most serious limiting factor in a plant.

Their negative impact on plant productivity and profitability is often greater than the total cost of the maintenance operation. However, without regular monitoring of process parameters, many plants do not recognize this unfortunate fact. If your program included monitoring of the suction and discharge pressures and ampere load of the pump, you could determine the operating efficiency. 

The brakehorsepower could be used to calculate operating efficiency of any pump in the program. By measuring the suction and discharge pressure, the total dynamic head (TDH) can be determined. A flow curve, used in conjunction with the actual total dynamic head, would define the actual flow (gpm) and an ammeter reading would define the horsepower. With these measured data, the efficiency can be calculated.

Process parameters monitoring should include all machinery and systems in the plant process that can affect its production capacity. Typical systems include heat exchangers, pumps, filtration, boilers, fans, blowers, and other critical systems.

Inclusion of process parameters in predictive maintenance can be accomplished in two ways: manual or microprocessor-based systems. However, both methods will normally require installing instrumentation to measure the parameters that indicate the actual operating condition of plant systems. Even though most plants have installed pressure gages, thermometers, and other instruments that should provide the information required for this type of program, many of them are no longer functioning. Therefore, including process parameters in your program will require an initial capital cost to install calibrated instrumentation. Data from the installed instrumentation can be periodically recorded using either manual logging or a microprocessor-based data logger. If the latter is selected, many vibration-based microprocessor systems can also provide the means of acquiring process data. 

Benefits of Predictive Maintenance

Properly implemented predictive maintenance can do much more than just schedule maintenance tasks. Typical results of predictive maintenance, based on operating dynamics, can be substantial. Using the four major loss classifications, first-year results from a maintenance improvement program based on a comprehensive predictive maintenance program include the following:

  • Breakdown losses
  • Quality improvement
  • Capacity improvement


L. R. Higgins, R. K. Mobley, R. Smith: Maintenance Engineering Handbook