Due to a perception that RCM was a very time consuming and labor intensive activity, a number of shortened versions of RCM have been devised in an attempt to speed up the analysis or increase the overall value of the time committed to analysis. Many of these methods have used the acronym, RCM to describe the process but do not conform to the works of Nolan and Heap (1978) nor the SAE Standard for RCM. These streamlined approaches are known as streamlined RCM techniques.

Statistical Methods

There are three main types of statistical maintenance analysis programs known to the author.

1. One of these is based on MILSTD 2173 and works from the premise that no inspection task is 100% effective. The algorithms adjust the interval of “on condition” tasks to account for less than perfect inspection methods.

2. Another is based on the notion that the more frequent the inspection the higher the cost of maintenance but the lower the chances of failure. The objective of maintenance under this algorithm is to determine the lowest overall cost of maintenance. This algorithm is flawed if inspection is near 100% reliable or is fail safe¹ as, providing the inspection is inside the PF² interval, more inspections only add to the cost of maintenance but not reduce the chances of failure.

3. The third statistical method has uses to Weibull analysis as a basis. This method suffers mostly from poor data integrity.

The overwhelming problem with statistical methods in the vast majority of industrial plant is that the failure history data is so unreliable and incomplete that any statistical inferences drawn from such data are wildly inaccurate and lack any worthwhile statistical confidence. The algorithms are also reliant on accounting inputs such as the cost of PM, repair and failure. All of these inputs are subject to the vagaries of the accounting systems deployed.

The second large problem is that statistical methods tend to be used by engineers or contractors who are not sufficiently familiar with the equipment an the manner that it is used on site. Often the result is a misguided program which is totally discredited by the tradesmen and operators because of its low quality and secondly because they were not sufficiently involved in its derivation.

Some explanation of the first two methods is contained at Part 3 (UNDERSTANDING STATISTICAL METHODS OF MAINTENANCE ANALYSIS) of this paper that will be published next.  

Experience, Trial and Error

In many cases, capital acquisition programs fail to recognize the need to define the maintenance program prior to the “Operation” stage of the equipment life cycle. Often, the plant is installed and operated without a formal maintenance program. Over time, the operations and maintenance staff begin to conduct inspections and perform various maintenance activities largely at their own initiative. Failures occur and the maintenance program has tasks added to it. In some organizations, the work is formalized by generating electronic or paper based maintenance schedules. In other organizations, the work continues to be done in a completely informal manner. Even though some managers may believe that there is no preventive maintenance done within their plant, this situation is highly unlikely. The confusion is often that the preventive maintenance is not appreciated, as there is no documentation.

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¹ Any incorrect sample will suggest there is a failure when in fact there is not.  Oil analysis or vibration analysis are examples where most of the problems are fail-safe.

² The period between the point at which a fault can be first detected and the point where it is considered to have functionally failed.