Predictive Maintenance Programs

It is important for predictive maintenance programs using vibration analysis to have accurate, repeatable data. In addition to the type and quality of the transducer, three key parameters affect data quality the point of measurement, orientation, and transducer-mounting techniques. 

Another method used by some plants to acquire data is hand-held transducers. This approach is not recommended if it is possible to use any other method. Hand-held transducers do not provide the accuracy and repeatability required to gain maximum benefit from a predictive maintenance program. If this technique must be used, extreme care should be exercised to ensure that the same location, orientation, and compressive load are used for every measurement. Illustrates a hand-held device. 

The only useful function of broadband analysis is longterm trending of the gross overall condition of machinery. Typically, sets of alert/alarm limits are established to monitor the overall condition of the machine-trains in a predictive maintenance program. However, this approach has limited value and, when used exclusively, severely limits the ability to achieve the full benefit of a comprehensive program. 

Reference or baseline data sets should be acquired for each machine-train or process system to be included in a predictive maintenance program when the machine is installed or after the first scheduled maintenance once the program is established. These data sets can be used as a reference or comparison for all future measurements. However, such data sets must be representative of the normal operating condition of each machine-train. Three criteria are critical to the proper use of baseline comparisons reset after maintenance, proper identification, and process envelope. 

This limitation prohibits the use of most microprocessor-based vibration analyzers for complex machinery or machines with variable speeds. Single-channel data-acquisition technology assumes the vibration profile generated by a machine-train remains constant throughout the data-acquisition process. This is generally true in applications where machine speed remains relatively constant (i.e., within 5 to fO rpm). In this case, its use does not severely limit diagnostic accuracy and can be effectively used in a predictive-maintenance program. 

Most predictive-maintenance programs rely almost exclusively on frequency-domain vibration data. The microprocessor-based analyzers gather time-domain data and automatically convert it using Fast Fourier Transform (FFT) to frequency-domain data. A frequency-domain signature shows the machine s individual frequency components, or peaks. 

The following parameters are monitored in a typical predictive-maintenance program for fans aerodynamic instability, running speeds, and shaft mode shape, or shaft deflection. 

A process information sheet (PIS) should be developed for each machine-train and production process that is to be included in a predictive-maintenance program. These data sheets should include all process variables that affect the dynamics and vibration profiles of the monitored components. 

This change in vibration energy can be clearly observed in trend data acquired from machine-trains. A sawtooth trend is common to most predictive-maintenance programs, which can be directly attributed to variations in load. The only way to compensate for load variations is to track the actual load associated with each data set. 

Used properly, this feature greatly enhances a predictive-maintenance program. The real value of trending techniques is that they provide the capability of automatically scanning large amounts of data (both broadband and narrowband) and reporting any change in pre-selected values. 

A series of baseline or reference data sets should be taken for each machine-train included in a predictive-maintenance program. These data sets are necessary for future use as a reference point for trends, time traces, and FFT signatures that are collected over time. Such baseline data sets must be representative of the normal... 

Predictive maintenance was shown to reduce the actual time required to repair or rebuild plant equipment. The average improvement in mean-time-to-repair, MTTR, was a reduction of 60 per cent. To determine the average improvement, actual repair times before the predictive maintenance program were compared to the actual time... 

These techniques include (1) vibration monitoring (2) thermography, (3) tribology, (4) process parameters, (5) visual inspection and (5) other nondestructive testing techniques. This chapter will provide a description of each of the techniques that should be included in a full capabilities predictive maintenance program for typical plants. 

Most vibration-based predictive maintenance programs use some form of signature analysis in their program. However, the majority of these programs rely on comparative analysis rather than full root-cause techniques. This... 

The capital cost for implementing a vibration-based predictive maintenance program will range from about 8,000 to more than 50,000. Your costs will depend on the specific techniques desired. 

The chapters on establishing and maintaining a total plant predictive maintenance program will provide the practical knowledge required implementing a cost-effective vibration-based program that will provide maximum benefits. 

Infrared thermometers or spot radiometers are designed to provide the actual surface temperature at a single, relatively small point on a machine or surface. Within a predictive maintenance program, the point-of-use infrared thermometer can be used in conjunction with many of the microprocessor-based vibration instruments to monitor the temperature at critical points on plant machinery or equipment. This technique is typically used to monitor bearing cap temperatures, motor winding temperatures, spot checks of process piping temperatures and similar applications. It is limited in that the temperature represents a single point on the machine or structure. However when used in conjunction with vibration data, point-of-use infrared data can be a valuable tool. 

Inclusion of thermography into a predictive maintenance program will enable you to monitor the thermal efficiency of critical process systems that rely on heat transfer or retention electrical equipment and other parameters that will improve both the reliability and efficiency of plant systems. Infrared techniques can be used to detect problems in a variety of plant systems and equipment, including electrical switchgear, gearboxes, electrical substations, transmissions, circuit breaker panels, motors, building envelopes, bearings, steam lines, and process systems that rely on heat retention or transfer. 

Spectrographic analysis allows accurate, rapid measurements of many of the elements present in lubricating oil. These elements are generally classified as wear metals, contaminates, or additives. Some elements can be listed in more than one of these classifications. Standard lubricating oil analysis does not attempt to determine the specific failure modes of developing machine-train problems. Therefore, additional techniques must be used as part of a comprehensive predictive maintenance program. 

There are three major limitations with using tribology analysis in a predictive maintenance program equipment costs, acquiring accurate oil samples and interpretation of data. 

The capital cost of spectrographic analysis instrumentation is normally too high to justify in-plant testing. Typical cost for a microprocessor-based spectrographic system is between 30,000 and 60,000. Because of this, most predictive maintenance programs rely on third party analysis of oil samples. 

Many plants do not consider machine or systems efficiency as 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 can be operating at less than 50 per cent efficiency and the predictive maintenance program would not detect the problem. 

Regular visual inspection of the machinery and systems in a plant is a necessary part of any predictive maintenance program. In many cases, visual inspection will detect potential problems that will be missed using the other predictive maintenance techniques. 

Most of the vibration-based predictive maintenance systems include the capability of recording visual observations as part of the routine data acquisition process. Since the incremental costs of these visual observations are small, this technique should be incorporated in all predictive maintenance programs. 

All equipment and systems in the plant should be visually inspected on a regular basis. The additional information provided by visual inspection will augment the predictive maintenance program regardless of the primary techniques used. 

Numerous other nondestructive techniques can be used to identify incipient problems in plant equipment or systems. However, these techniques either do not provide a broad enough application or are too expensive to support a predictive maintenance program. Therefore, these techniques... 

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