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Like preventive maintenance, predictive maintenance has many definitions. To some, predictive maintenance is monitoring the vibration of rotating machinery in an attempt to detect incipient problems and prevent catastrophic failure.

To others, it is monitoring the infrared image of electrical switchgear, motors, and other electrical equipment to detect developing problems.

The common premise of predictive maintenance is that regular monitoring of the actual crafts condition, operating efficiency, and other indicators of operating condition of machine trains and process systems provides the data required to ensure the maximum interval between repairs and minimize the number and cost of unscheduled outages created by machine train failures.

Predictive maintenance is much more. It is the means of improving productivity, product quality, and overall effectiveness of manufacturing and production plants.
Predictive maintenance is not vibration monitoring, thermal imaging, lubricating oil analysis, or any of the other nondestructive testing techniques being marketed as predictive maintenance tools.

“Predictive maintenance, simply stated, is a philosophy or attitude of using the actual operating condition of plant equipment and systems to optimize total plant operation”

A comprehensive predictive maintenance management program utilizes a combination of the most cost effective tools, that is, vibration monitoring, thermography, tribology, and the like, to obtain the actual operating condition of critical plant systems and, based on this actual data, schedules all maintenance activities on an “as needed” basis.

Including predictive maintenance in a comprehensive maintenance management program allows optimizing the availability of process machinery and greatly reduces the cost of maintenance. It also provides the means to improve product quality, productivity, and profitability in manufacturing and production plants.

Predictive maintenance is a condition-driven preventive maintenance program. Instead of relying on industrial or in-plant average life statistics (i.e., mean time to failure) to schedule maintenance activities, predictive maintenance uses direct monitoring of the crafts condition, system efficiency, and other indicators to determine the actual mean time to failure or loss of efficiency for each machine train and system in the plant. At best, traditional time-driven methods provide a guideline to “normal” machine train life spans.

In preventive or run-to-failure programs, the final decision on repair or rebuild schedules must be made on the basis of intuition and the personal experience of the maintenance manager. The addition of a comprehensive predictive maintenance program provides factual data on the actual crafts condition of each machine train and process system that the maintenance manager can use for scheduling maintenance activities.

A predictive maintenance program minimizes unscheduled breakdowns of all crafts equipment in the plant and ensures that repaired equipment is in acceptable condition. The program also identifies machine train problems before they become serious. Most equipment problems can be minimized if Predictive maintenance utilizing vibration signature analysis is predicated on two basic facts:

  1. All common failure modes have distinct vibration frequency components that can be isolated and identified
  2. The amplitude of each distinct vibration component remains constant unless there is a change in the operating dynamics of the machine train.

These facts, their impact on machinery, and the methods that identify detected and repaired early. And quantify the root cause of failure modes are developed in more detail in later chapters.

Predictive maintenance utilizing process efficiency, heat loss, or other nondestructive techniques can quantify the operating efficiency of plant equipment or systems. These techniques used in conjunction with vibration analysis can provide the maintenance manager or plant engineer information for achieving optimum reliability and availability from the plant.

A wide variety of predictive techniques and technologies may provide benefit to a facility or plant. In most cases, more than one is needed for complete coverage of all critical assets and to gain maximum benefits from their use. Several nondestructive techniques normally are used for predictive maintenance management: vibration monitoring, process parameter monitoring, thermography, tribology, and visual inspection. Each technique has a unique data set to assist in determining the actual need for maintenance. Some typical technologies successfully utilized by facilities and plants are included in the Table below.

Most comprehensive predictive maintenance programs use vibration analysis as the primary tool. Since the majority of normal plant equipment is rotating, vibration monitoring provides the best tool for routine monitoring and identification of incipient problems however remember “It is all about the Failure Modes”. These facts, impact on machinery, and the methods that identify and quantify the root cause of failure modes are developed. However, vibration analysis does not provide the data required on electrical equipment, areas of heat loss, condition of lubricating oil, and other parameters that should be included in the program.

Predictive maintenance utilizing process efficiency, heat loss, or other nondestructive techniques can quantify the operating efficiency of plant equipment or systems. These techniques used in conjunction with vibration analysis can provide the maintenance manager or plant engineer information for achieving optimum reliability and availability from the plant.

A wide variety of predictive techniques and technologies may provide benefit to a facility or plant. In most cases, more than one is needed for complete coverage of all critical assets and to gain maximum benefits from their use.

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