Maintenance Management

CORRECTIVE MAINTENANCE

There are three types of maintenance tasks: reactive, corrective, and preventive. The principal difference in these occurs at the point when the repair or maintenance task is implemented. In breakdown maintenance, repairs do not occur until the machine fails to function. Preventive maintenance tasks are implemented before a problem is evident and corrective tasks are scheduled to correct specific problems that have been identified in plant systems.

A comprehensive maintenance program should use a combination of all three. However, most domestic plants rely almost exclusively on breakdown maintenance to maintain their critical plant production systems.

Reactive Maintenance. In these programs, less concern is given to the operating condition of critical plant machinery, equipment, or systems. Since most of the maintenance tasks are reactive to breakdowns or production interruptions, the only focus of these tasks is how quickly the machine or system can be returned to service. As long as the machine will function at a minimum acceptable level, maintenance is judged to be effective. This approach to maintenance management is both ineffective and extremely expensive. Breakdown maintenance has two factors that are the primary contributors to high maintenance costs: poor planning and incomplete repair.

The first limitation of breakdown maintenance is that most repairs are poorly planned because of the time constraints imposed by production and plant management. As a result, manpower utilization and effective use of maintenance resources are minimal. Typically, breakdown or reactive maintenance will cost three to four times more than the same repair when it is well planned. The second limitation of breakdown maintenance is that it concentrates repair on obvious symptoms of the failure, not the root cause. For example, a bearing failure may cause a critical machine to seize and stop production. In breakdown maintenance, the bearing is replaced as quickly as possible and the machine is returned to service. No attempt is made to determine the root cause of the bearing failure or to prevent a recurrence of the failure. As a result, the reliability of the machine or system is severely reduced. This normal result of breakdown maintenance is an increase in the frequency of repairs and a marked increase in maintenance costs.

Preventive Maintenance. The concept of preventive maintenance has a multitude of meanings. A literal interpretation of the term is a maintenance program that is committed to the elimination or prevention of corrective and breakdown maintenance tasks. A comprehensive preventive maintenance program will utilize regular evaluation of critical plant equipment, machinery, and systems to detect potential problems and immediately schedule maintenance tasks that will prevent any degradation in operating condition.

In most plants, preventive maintenance is limited to periodic lubrication, adjustments, and other time-driven maintenance tasks. These programs are not true preventive programs. In fact, most continue to rely on breakdowns as the principal motivation for maintenance activities.

A comprehensive preventive maintenance program will include predictive maintenance, time-driven maintenance tasks, and corrective maintenance to provide comprehensive support for all plant production or manufacturing systems.

Corrective Maintenance. The primary difference between corrective and preventive maintenance is that a problem must exist before corrective actions are taken. Preventive tasks are intended to prevent the occurrence of a problem. Corrective tasks correct existing problems.

Corrective maintenance, unlike breakdown maintenance, is focused on regular, planned tasks that will maintain all critical plant machinery and systems in optimum operating conditions. Maintenance effectiveness is judged on the life-cycle costs of critical plant machinery, equipment, and systems, not on how fast a broken machine can be returned to service.

Corrective maintenance, as a subset of a comprehensive preventive maintenance program, is a proactive approach toward maintenance management. The fundamental objective of this approach is to eliminate breakdowns, deviations from optimum operating condition, and unnecessary repairs and to optimize the effectiveness of all critical plant systems.

The principal concept of corrective maintenance is that proper, complete repairs of all incipient problems are made on an as-needed basis. All repairs are well planned, implemented by properly trained craftsmen, and verified before the machine or system is returned to service. Incipient problems are not restricted to electrical or mechanical problems. Instead, all deviations from optimum operating condition, that is, efficiency, production capacity and product quality, are corrected when detected.

All corrective repairs or maintenance must be well planned and scheduled to minimize both cost and interruption of the production schedule. Adequate time must be allowed to permit complete repair of the root cause and resultant damage caused by each of the identified incipient problems.

Repairs must be complete and properly implemented. In many cases, poor maintenance or repair practices result in more damage to critical plant machinery than the observed failure mode.

A fundamental requirement of corrective maintenance is proper, complete repair of each incipient problem. To meet this requirement, all repairs must be made by craftsmen who have the necessary skills, repair parts, and tools required to return the machine or system to as-new condition.

One of the reasons that most plants rely on breakdown maintenance is that tight production schedules and management constraints limit the time available for maintenance. The only way to reduce the number and frequency of breakdown repairs is to allow sufficient time for proper maintenance.

Plant management must permit adequate maintenance time for all critical plant systems before either preventive or corrective maintenance can be effective. In the long term, the radical change in management philosophy will result in a dramatic reduction in the downtime required to maintain critical production and manufacturing equipment. Machinery that is maintained in as-new condition and not permitted to degrade to a point that breakdown or serious problems can occur will require less maintenance than machinery maintained in a breakdown mode.

Corrective maintenance will remain a critical part of a comprehensive plant maintenance program. However, the objective of a viable preventive program is to eliminate all breakdown maintenance and severely reduce the number and frequency of corrective maintenance actions.

The ultimate objective of any maintenance program should be the elimination of machine, equipment, and system problems that require corrective actions.

PREVENTIVE MAINTENANCE

Preventive maintenance, as its name implies, are specific tasks that are designed to prevent the need for corrective or breakdown maintenance, as well as prolong the useful life of capital assets and auxiliary equipment. Most preventive maintenance programs are a loose conglomeration of inspections, cleaning, adjustment, lubrication, and similar tasks that do little, if anything, to preserve the reliability of critical production assets. Statistically, between 33 percent and 42 percent of so-called preventive maintenance tasks add no value, in terms of reliability or maintenance prevention. [XX]

Preventive maintenance replaces these no-value tasks with specific maintenance activities that both prevents failures and prolong the useful life of plant assets. Development of a preventive maintenance program follows logic diagrams shown in Fig. 1.1. and the task selection criteria, illustrated in Table 1.1., which are its principal tools.

The logic diagrams are the basis of an evaluation technique applied to each functionally significant item (FSI) using all available technical data, as well as the “native knowledge” of plant personnel. Principally, the evaluations are based on the item’s functional failures and failure causes. The development of a preventive maintenance program is based on the following:

Identification of FSI’s

Identification of applicable and effective preventive maintenance tasks using the decision tree logic.

Information Collection. Equipment information provides the basis for the evaluation and should be assembled prior to the start of the analysis and supplemented as the need arises. The following should be included:

Requirements for equipment and its associated systems, including regulatory requirements

Design and maintenance documentation

Performance feedback, including maintenance and failure data

Also, in order to guarantee completeness and avoid duplication, the evaluation should be based on an appropriate and logical breakdown of the equipment.

Figure 2.1. Development tasks of a reliability-based preventive maintenance program

System Analysis. Information collection define the procedure for the identification of the functionally significant items and the subsequent maintenance task selection and implementation. It should be noted that the tasks can be tailored to meet the requirements of particular industries and the emphasis placed on each task will depend on the nature of that industry.

Identification of Systems. The objective of this task is to partition the equipment into systems, grouping the components contributing to achievement of well-identified functions and identifying the system boundaries. Sometimes it is necessary to perform further partitioning into the subsystems, which perform functions critical to system performance. The system boundaries may not be limited by the physical boundaries of the systems, which may overlap.

Frequently, the equipment is already partitioned into systems through industry specific partitioning schemes. This partitioning should be reviewed and adjusted where necessary to ensure that it is functionally oriented. The results of equipment partitioning should be documented in a master system index that identifies systems, components, and boundaries.

Identification of System Functions. The objective of this task is to determine the main and auxiliary functions performed by the systems and subsystems. The use of functional block diagrams will assist in the identification of system functions. The function definition describes the actions or requirements which the system or subsystem should accomplish, sometimes in terms of performance capabilities within the specified limits. The functions should be identified for all modes of equipment operation.

Reviewing design specifications, design descriptions, and operating procedures, including safety, abnormal operations, and emergency instructions, may determine the main and auxiliary functions. Functions such as testing or preparations for maintenance, if not considered important, may be omitted. The reason for omissions must be given. The product of this task is a listing of system functions.

Selection of Systems. The objective of this task is to select and prioritize systems, which will be included in the Reliability Centered Maintenance (RCM) program because of their significance to equipment safety, availability, or economics. The methods used to select and prioritize the systems can be divided into:

Qualitative methods based on past history and collective engineering judgment

Quantitative methods, based on quantitative criteria, such as criticality rating, safety factors, probability of failure, failure rate, life cycle cost, and the like, used to evaluate the importance of system degradation/failure on equipment safety, performance, and costs. Implementation of this approach is facilitated when appropriate models and data banks exist

Combination of qualitative and quantitative methods

The product of this task is a listing of systems ranked by criticality. The systems, together with the methods, the criteria used and the results, should be documented.

System Functional Failures and Criticality Ranking. The objective of this task is to identify system functional degradation/failures and prioritize them. The functional degradation/failures of a system for each function should be identified, ranked by criticality and documented.

Since each system functional failure may have different impacts on safety, availability, or maintenance cost, it is necessary to rank and prioritize them. The ranking takes into account probability of occurrence and consequences of failure. Qualitative methods based on collective engineering judgment and based on the analysis of operating experience can be used. Quantitative methods of Simplified Failure Modes and Effects Analysis (SFMEA) or risk analysis can also be used.

The ranking represents one of the most important tasks in RCM analysis. Too conservative a ranking may lead to an excessive preventive maintenance program, and conversely a lower ranking may result in excessive failures and a potential safety impact. In both cases, a non-optimized maintenance program will result. The outputs of this task are the following:

Listing of system functional degradation/failures and their characteristics

Ranking list of system functional degradation/failures

PREDICTIVE MAINTENANCE

As a maintenance management tool, predictive maintenance can provide the data required to schedule both preventive and corrective maintenance tasks on an as-needed basis. Instead of relying on industrial average-life statistics, such as mean-time-to-failure (MTTF), to schedule maintenance activities, predictive maintenance uses direct monitoring of the operating condition, system efficiency, and other indicators to determine the actual mean-time-to-failure or loss of efficiency for each machine train and system within the plant.

At best, traditional time-driven methods provide a guideline to normal machine-train life spans. The final decision, in preventive or run-to-failure programs, on when to repair or rebuild a machine must be made on the basis of intuition and the personal experience of the maintenance manager. The addition of a comprehensive predictive maintenance program can and will provide factual data that define the actual mechanical condition of each machine train and operating efficiency of each process system. These data provide the maintenance manager with factual data that can be used to schedule maintenance activities.

A predictive maintenance program can minimize unscheduled breakdowns of all mechanical equipment in the plant and ensure that repaired equipment is in acceptable mechanical condition. The program 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.

Predictive maintenance cannot function in a void. To be an effective maintenance management tool, it must be combined with a viable maintenance planning function that will use the data to plan and schedule appropriate repairs. In addition, it is dependent on the skill and knowledge of maintenance craftsmen. Unless proper repairs or corrective actions are made, the data provided by the predictive maintenance program cannot be effective. Both ineffective planning and improper repairs will severely restrict the benefits of predictive maintenance.

Predictive maintenance utilizing vibration signature analysis is predicated on two basic facts: all common failure modes have distinct vibration frequency components that can be isolated and identified, and the amplitude of each distinct vibration component will remain constant unless there is a change in the operating dynamics of the machine train. Predictive maintenance utilizing process efficiency, heat loss, or other nondestructive techniques can quantify the operating efficiency of non-mechanical plant equipment or systems. These techniques used in conjunction with vibration analysis can provide the maintenance manager or plant engineer with factual information that will enable them to achieve optimum reliability and availability from their plant.

PREDICTIVE MAINTENANCE TECHNIQUES

A variety of technologies can, and should be, used as part of a comprehensive predictive maintenance program. Because mechanical systems or machines account for most plant equipment, vibration monitoring is generally the key component of most predictive maintenance programs; however, vibration monitoring cannot provide all of the information required for a successful predictive maintenance program. This technique is limited to monitoring the mechanical condition and no other critical parameters required to maintain reliability and efficiency of machinery. It is a very limited tool for monitoring critical process and machinery efficiencies and other parameters that can severely limit productivity and product quality.

Therefore, a comprehensive predictive maintenance program must include other monitoring and diagnostic techniques. These techniques include vibration monitoring, thermography, tribology, process parameters, visual inspection, ultrasonic, and other nondestructive testing techniques. This chapter provides a brief description of each of the techniques that should be included in a full-capabilities predictive maintenance program for typical plants. Subsequent chapters provide a more detailed description of these techniques and how they should be used as part of an effective maintenance management tool.

VIBRATION MONITORING

Vibration monitoring and analysis are two of the most useful tools for predicting incipient mechanical, electrical, and process-related problems within plant equipment, machinery, and continuous process systems. Therefore, they are the most often used predictive maintenance technologies. Used in conjunction with other process-related measurements, such as flow, pressure, and temperature measurements, vibration analysis can provide the means to first schedule maintenance and ultimately to eliminate the need for corrective maintenance tasks.

Vibration monitoring and analysis can be used to evaluate all mechanical and most continuous process equipment within a manufacturing or production plant. They are not limited to simple rotating machines. Until recently, slow-speed machinery, especially complex, continuous-process lines, were excluded from the useful range of vibration analysis. Recent technology developments have removed this limitation and now permit the use of vibration analysis techniques for machinery with primary speeds as low as 6 rpm.

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Causes of Machine Vibration. All machines vibrate. These vibrations are caused by the tolerances which the machine designer has allowed so that the machine can be built, since some dimensional variations are inherent in any machine’s manufacture. These tolerances give a new machine a characteristic vibration “signature” and provide a base line against which future measurements can be compared. Similar machines in good operating condition will have similar vibration signatures which differ from each other only by their manufacturing and installation tolerances.

A change from the base line of the vibration of a machine, assuming it is operating under normal conditions, indicates that an incipient defect is starting to change the mechanical condition of the machine. Different defects cause the vibration signature to change in different ways, thus providing a means of determining the source of the problem as well as warning of the problem itself.

Characteristics of Vibration. Vibration is a natural product of the mechanical and dynamic forces within machinery, plant equipment, and process systems. All mechanical equipment and most dynamic plant systems, such as heat exchangers, filters, mixing tanks, and chemical reaction vessels, will generate some level of vibration as part of their normal operation. A clear understanding of machine dynamics and how these forces create unique vibrational frequency components is the key to using vibration data as a diagnostic tool.

Machinery vibration is the result of a series of individual vibration components that are generated by the movement or generated forces of mechanical or process components within the machine or its corresponding system. Each of these individual vibration components has a well-defined periodic motion. That is, the motion will repeat itself in all its particulars after a specific interval of time. The interval or time period T in which the vibration repeats itself is usually measured in seconds. Its reciprocal is the frequency of the vibration and is normally measured in terms of cycles per second (cps), or hertz (Hz).

Machinery Dynamics. All mechanical plant equipment can be broken down into four classifications: constant-speed, constant-load, constant-speed, variable-load, variable-speed, constant-load, and variable-speed, variable-load. The vibration monitoring system that you select must be able to effectively handle all these combinations of machine operation. Why is this important? Both speed and load will affect the location and amplitude of the unique vibration components generated by the mechanical forces or motion within the machine train.

The location or frequency of individual vibration components will maintain a fixed relationship to the actual running speed of the specific shaft that generated the force. As the shaft speed changes, so will the location or frequency of the individual vibration components generated by that shaft. For example, the gear-meshing-frequency component of a gear with 10 teeth mounted on a shaft turning at 20 Hz will be located at 200 Hz. If the shaft speed changes to 40 Hz, the gear meshing frequency also will move to 400 Hz.

Load changes will not cause the location of individual vibration frequency components to change but will affect the amplitude or energy of each component. Change in machine load will either amplify or dampen the energy of individual vibration components. The variation in vibration energy at 100 percent load cannot be compared directly with that of the same machine operating at 50 percent load. Therefore, your vibration-based predictive maintenance program must compensate for load variations.

To establish and utilize vibration-based predictive maintenance, a complete knowledge of each machine component and how they interact within the machine train is absolutely necessary. Every phase, from implementation through root-cause failure analysis, of a predictive maintenance program is driven by the dynamics and resulting vibration characteristics of each machine train. All rotating, reciprocating, and continuous-process machines have common components, characteristics, and failure modes. Each machine also has totally unique operating dynamics and failure modes.

Common Failure Modes:

Imbalance. Imbalance is probably the most common failure mode in mechanical equipment. The assumption that actual mechanical imbalance must exist to create an imbalanced condition within the machine is incorrect. Aerodynamic or hydraulic instability also can create massive imbalance in a machine. In fact, all failure modes will create some form of imbalance in a machine. When all failures are considered, the number of machine problems that are the result of actual mechanical imbalance of the rotating element is relatively small. Imbalance will take many forms in the vibration signature. In almost every case the fundamental or running-speed component will be excited and is the dominant amplitude. However, this condition also can excite multiple harmonics or multiples of running speed. The number of harmonics and their amplitude have a direct correlation with the number of planes of mechanical imbalance and their phase relationship.

Misalignment. This condition is virtually always present in machine trains. Generally, we assume that misalignment exists between two shafts connected by a coupling, V-belts, or other intermediate drives. Misalignment also can exist between the bearings of a solid shaft and at other points within the machine. The presentation of misalignment in the vibration signature will depend on the type of misalignment. There are two major classifications of misalignment: parallel and angular.

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THERMOGRAPHY

Thermography is a predictive maintenance technique that can be used to monitor the condition of plant machinery, structures, and systems, not just electrical equipment. It uses instrumentation designed to monitor the emission of infrared energy (i.e., surface temperature) to determine operating condition. By detecting thermal anomalies (i.e., areas that are hotter or colder than they should be), an experienced technician can locate and define a multitude of incipient problems within the plant.

Infrared technology is predicated on the fact that all objects having a temperature above absolute zero emit energy or radiation. Infrared radiation is one form of this emitted energy. Infrared emissions, or below red, are the shortest wavelengths of all radiated energy and are invisible without special instrumentation. The intensity of infrared radiation from an object is a function of its surface temperature; however, temperature measurement using infrared methods is complicated because three sources of thermal energy can be detected from any object: energy emitted from the object itself, energy reflected from the object, and energy transmitted by the object. Only the emitted energy is important in a predictive maintenance program. Reflected and transmitted energies will distort raw infrared data. Therefore, the reflected and transmitted energies must be filtered out of acquired data before a meaningful analysis can be completed.

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Variations in surface condition, paint or other protective coatings, and many other variables can affect the actual emissivity factor for plant equipment. In addition to reflected and transmitted energy, the user of thermographic techniques must also consider the atmosphere between the object and the measurement instrument. Water vapor and other gases absorb infrared radiation. Airborne dust, some lighting, and other variables in the surrounding atmosphere can distort measured infrared radiation. Because the atmospheric environment is constantly changing, using thermographic techniques requires extreme care each time infrared data is acquired.

Most infrared-monitoring systems or instruments provide filters that can be used to avoid the negative effects of atmospheric attenuation of infrared data; however, the plant user must recognize the specific factors that affect the accuracy of the infrared data and apply the correct filters or other signal conditioning required to negate that specific attenuating factor or factors.

Collecting optics, radiation detectors, and some form of indicator are the basic elements of an industrial infrared instrument. The optical system collects radiant energy and focuses it on a detector, which converts it into an electrical signal. The instrument’s electronics amplifies the output signal and processes it into a form that can be displayed.

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TRIBOLOGY

Tribology is the general term that refers to design and operating dynamics of the bearing-lubrication-rotor support structure of machinery. Two primary techniques are being used for predictive maintenance: lubricating oil analysis and wear particle analysis.

Lube Oil Analysis. Lubricating oil analysis, as the name implies, is an analysis technique that determines the condition of lubricating oils used in mechanical and electrical equipment. It is not a tool for determining the operating condition of machinery or detecting potential failure modes. Too many plants are attempting to accomplish the latter and are disappointed in the benefits that are derived. Simply stated, lube oil analysis should be limited to a proactive program to conserve and extend the useful life of lubricants. Although some forms of lubricating oil analysis may provide an accurate quantitative breakdown of individual chemical elements – both oil additive and contaminants contained in the oil – the technology cannot be used to identify the specific failure mode or root-cause of incipient problems within the machines serviced by the lube oil system.

The primary applications for lubricating oil analysis are quality control, reduction of lubricating oil inventories, and determination of the most cost-effective interval for oil change. Lubricating, hydraulic, and dielectric oils can be periodically analyzed using these techniques to determine their condition. The results of this analysis can be used to determine if the oil meets the lubricating requirements of the machine or application. Based on the results of the analysis, lubricants can be changed or upgraded to meet the specific operating requirements.

In addition, detailed analysis of the chemical and physical properties of different oils used in the plant can, in some cases, allow consolidation or reduction of the number and types of lubricants required to maintain plant equipment. Elimination of unnecessary duplication can reduce required inventory levels and therefore maintenance costs.

As a predictive maintenance tool, lubricating oil analysis can be used to schedule oil change intervals based on the actual condition of the oil. In midsize to large plants, a reduction in the number of oil changes can amount to a considerable annual reduction in maintenance costs. Relatively inexpensive sampling and testing can show when the oil in a machine has reached a point that warrants change.

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Wear Particle Analysis. Wear particle analysis is related to oil analysis only in that the particles to be studied are collected by drawing a sample of lubricating oil. Whereas lubricating oil analysis determines the actual condition of the oil sample, wear particle analysis provides direct information about the wearing condition of the machine-train. Particles in the lubricant of a machine can provide significant information about the machine’s condition. This information is derived from the study of particle shape, composition, size, and quantity.

Two methods are used to prepare samples of wear particles. The first method, called spectroscopy or spectrographic analysis, uses graduated filters to separate solids into sizes. Normal spectrographic analysis is limited to particulate contamination with a size of 10 microns or less. Larger contaminants are ignored. This fact can limit the benefits that can be derived from the technique. The second method, called ferro-graphic analysis, separates wear particles using a magnet. Obviously, the limitation to this approach is that only magnetic particles are removed for analysis. Nonmagnetic materials, such as copper, aluminum, and so on that make up many of the wear materials in typical machinery are therefore excluded from the sample.

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Wear particle analysis is an excellent failure analysis tool and can be used to understand the root-cause of catastrophic failures. The unique wear patterns observed on failed parts, as well as those contained in the oil reservoir, provide a positive means of isolating the failure mode.

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ULTRASONICS

Ultrasonics, like vibration analysis, is a subset of noise analysis. The only difference in the two techniques is the frequency band they monitor. In the case of vibration analysis, the monitored range is between 1 Hertz (Hz) and 30,000 Hz; ultrasonic monitors noise frequencies above 30,000 Hz. These higher frequencies are useful for select applications, such as detecting leaks that generally create high-frequency noise caused by the expansion or compression of air, gases, or liquids as they flow through the orifice, or a leak in either pressure or vacuum vessels. These higher frequencies are also useful in measuring the ambient noise levels in various areas of the plant.

As it is being applied as part of a predictive maintenance program, many companies are attempting to replace what is perceived as an expensive tool (i.e., vibration analysis) with ultrasonics. For example, many plants are using ultrasonic meters to monitor the health of rolling-element bearings in the belief that this technology will provide accurate results. Unfortunately, this perception is invalid. Because this technology is limited to a broadband (i.e., 30 kHz to 1 MHz), ultrasonics does not provide the ability to diagnosis incipient bearing or machine problems. It certainly cannot define the root cause of abnormal noise levels generated by either bearings or other machine-train components.

As part of a comprehensive predictive maintenance program, ultrasonics should be limited to the detection of abnormally high ambient noise levels and leaks. Attempting to replace vibration monitoring with ultrasonics simply will not work.

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ELECTRICAL TESTING – MEGGER TEST

In order to measure high resistances, a device known as a mega-ohmmeter can be used. This instrument differs from a normal ohmmeter in that instead of measuring current to determine resistance, it measures voltage. This mode of testing involves applying relatively high voltage (500 to 2,500 volts, depending on the unit) to the circuit and verifying that no breakdown is present. Generally, this is considered a non-destructive test, depending on the applied voltage and the rating of the insulation. This method of testing is used primarily to test the integrity of insulation. It will not detect shorts between windings, but it can detect higher-voltage–related problems with respect to ground.

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RELIABILITY CENTERED MAINTENANCE

Description. Reliability centered maintenance (RCM) is a technique initially developed by the airline industry that focuses on preventing failures whose consequences are most likely to be serious. RCM was developed in the late 1960s when wide-body jets were being introduced into service. Because of the increased size and complexity of these aircraft, airlines were concerned that the continuing use of traditional maintenance methods would make the new aircraft uneconomical.

Previously, preventive maintenance was primarily time-based (e.g., overhauling equipment after a certain number of hours of flying time). In contrast RCM is condition-based, with maintenance intervals based on actual equipment criticality and performance data. After adopting this approach, airlines found that maintenance costs remained about constant, but that the availability and reliability of their aircraft improved because effort was spent on maintenance of equipment most likely to cause serious problems. As a result, RCM is now used by most of the world's airlines.

Reliability centered maintenance (RCM) analysis is a systematic evaluation approach for developing or optimizing a maintenance program. RCM utilizes a decision logic tree to identify the maintenance requirements of equipment according to the safety and operational consequences of each failure and the degradation mechanism responsible for the failures.

Maintenance and Reliability Centered Maintenance (RCM). The relationship between RCM and traditional maintenance practices can best be summarized as follows: “Plant and equipment are installed and employed to do what the users want them to do. Maintenance is undertaken in a variety of forms, to ensure that the plant and equipment continues to do what the users want it to do. Reliability Centered Maintenance determines what maintenance needs to be performed and what testing and inspection needs to be performed to support the maintenance strategy”.

The outcomes of an RCM analysis can result in changes to existing preventive maintenance tasks, the use of condition monitoring, inspections and functional testing, or the addition or elimination of such tasks. Figure 1 shows the structure of maintenance.

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When used effectively it can result in the enhancement of safety and reliability of plant and equipment and the optimization of operations and maintenance activities.

RCM is not a process, which will result in short term benefits, so those adopting it should be prepared for a 5 to 10-year payback term.

RCM is a decision making tool. Operations and maintenance programs can benefit both the processes involved in the decision-making, soft benefits and the outcomes, that result in the changes to maintenance and operations programs. The following are some examples:

The act of performing the RCM decision-making process provides a benefit in promoting better co-operation among all of those involved in the process.

The process demands that all established tasks are challenged with the objective of justifying continued use or removing/replacing them with other tasks, in doing so it promotes a healthy questioning attitude.

The process raises awareness of the functions of the systems involved, the consequences of failure of those functions and the economics of operating and maintaining them.

The clear aims of RCM are to improve reliability and optimize the cost effectiveness of maintenance activities. When performed effectively it will result in the elimination of unnecessary maintenance tasks and the introduction of measures to address omissions and deficiencies in maintenance programs.

The Principles of RCM. The RCM analysis process centers on the functions of plant and equipment, the consequences of failure and measures to prevent or cope with functional failure. The process must establish answers to the following questions and an effective response to them:

What are the functions and performance standards of the plant?

In what ways does it fail to fulfil its functions?

What causes each functional failure?

What happens when each failure occurs?

In what way does each failure matter?

What can be done to predict or prevent each failure?

What should be done if a suitable proactive task cannot be found?

The RCM Process – Basic Steps. RCM is not a stand-alone process, it must be an integral part of the Operations and Maintenance programs. The introduction of the RCM process will involve changes to established working processes. For the successful introduction of such changes it will be important that management demonstrate their commitment to the changes, possibly in the form of a policy statement and personal involvement and that measures are taken to establish the engagement of those who will be involved or affected by the changes. RCM works best when employed as a bottom up process, involving those working directly in the operation and maintenance of the plant and equipment.

Preparation. The preparatory phase has a number of steps which basically involve the selection of the systems to be analyzed, gathering the necessary data for the analysis. In addition, the ground rules or criteria to be used in the selection and analysis process must be established. For example; Key Assumptions, Critical Evaluation Criteria, Non Critical Evaluation Criteria and Establishment of a review process. The stages can be summarized as follows:

System Selection

Definition of the system boundaries

Acquisition of Documentation and Materials

Interviews with Plant Personnel

Analysis. Once the systems have been selected for analysis and the preparations have been completed the analysis can commence. Experience in the analysis process is important for effective decision-making. Such experience may exist in the utility or it may be bought in from specialist service providers in this area.

The data contained in formal systems is usually very comprehensive but knowledge management is not so well developed in NPPs that all experience is captured in data basis. For this reason, it is important that personnel with local experience in the operation and maintenance of the plant are involved in the analysis process.

The first stage of the analysis process therefore is the assembly of a team with a suitable range of qualifications and experience for the task. The analysis involves the following stages:

Identification of System Functions

System Functional Failure Analysis

Equipment Identification

Reliability and Performance Data Collection

Identification of Failure Modes

Identification of Failure Effects

Determination of Component Criticality

Task Selection. When the analysis has been completed the next part of the process is to allocate suitable maintenance tasks to the systems and equipment identified in the analysis process, in accordance with the significance ascribed to them, be they critical or non-critical. This part of the process will seek to establish the most cost effective means of delivering the maintenance strategy in respect of achieving safety, reliability, environmental and economic goals.

The task selection process uses various forms of logical decision making to arrive at conclusions in a systematic manner. The outcomes can include:

Preventive Maintenance

Condition Monitoring

Inspection and Functional Testing

Run to Failure