Life Cost Based FMEA Manual: A Step by Step Guide to Carrying Out a Cost-based Failure Modes and Effects Analysis
Failure occurs when one or more of the intended functions of a product are no longer fulfilled to the customer's satisfaction. The most critical product failures are those that escape design reviews and in-house quality inspection and are found by the customer. The product may work for a while until its performance degrades to an unacceptable level or it may have not worked even before customer took possession of the product. The end results of failures which may lead to unsafe conditions or major losses of the main function are rated high in severity. Failure Modes and Effects Analysis (FMEA) is a tool widely used in the automotive, aerospace, and electronics industries to identify, prioritize, and eliminate known potential failures, problems, and errors from systems under design, before the product is released (Stamatis, 1997). Several industrial FMEA standards such as those published by the Society of Automotive Engineers, US Department of Defense, and the Automotive Industry Action Group employ the Risk Priority Number (RPN) to measure risk and severity of failures. The Risk Priority Number (RPN) is a product of 3 indices: Occurrence (O), Severity (S), and Detection (D). In a traditional FMEA process design engineers typically analyze the 'root cause' and 'end-effects' of potential failures in a sub-system or component and assign penalty points through the O, S, D values to each failure. The analysis is organized around categories called failure modes, which link the causes and effects of failures. A few actions are taken upon completing the FMEA worksheet. The RPN column generally will identify the high-risk areas. The idea of performing FMEA is to eliminate or reduce known and potential failures before they reach the customers. Thus, a plan of action must be in place for the next task. Not all failures can be resolved during the product development cycle, thus prioritization of actions must be made within the design group. One definition of detection difficulty (D) is how well the organization controls the development process. Another definition relates to the detectability of a particular failure in the product when it is in the hands of the customer. The former asks 'What is the chance of catching the problem before we give it to the customer'? The latter asks 'What is the chance of the customer catching the problem before the problem results in a catastrophic failure?' (Palady, 1995) These differing definitions confuse the FMEA users when one tries to determine detection difficulty. Are we trying to measure how easy it is to detect where a failure has occurred or when it has occurred? Or are we trying to measure how easy or difficult it is to prevent failures? Ordinal scale variables are used to rank-order industries such as, hotels, restaurants, and movies (Note that a 4 star hotel is not necessarily twice as good as a 2 star hotel). Ordinal values preserve rank in a group of items, but the distance between the values cannot be measured since a distance function does not exist. Thus, the product or sum of ordinal variables loses its rank since each parameter has different scales. The RPN is a product of 3 independent ordinal variables, it can indicate that some failure types are 'worse' than others, but give no quantitative indication of their relative effects. To resolve the ambiguity of measuring detection difficulty and the irrational logic of multiplying 3 ordinal indices, a new methodology was created to overcome these shortcomings, Life Cost-Based FMEA. Life Cost-Based FMEA measures failure/risk in terms of monetary cost. Cost is a universal parameter that can be easily related to severity by engineers and others. Thus, failure cost can be estimated using the following simplest form: Expected Failure Cost = {sup n}{Sigma}{sub i=1}p{sub i}c{sub i}, p: Probability of a particular failure occurring; c: Monetary cost associated with that particular failure; and n: Total number of failure scenarios. FMEA is most effective when there are inputs into it from all concerned disciplines of the product development team. However, FMEA is a long process and can become tedious and won't be effective if too many people participate. An ideal team should have 3 to 4 people from: design, manufacturing, and service departments if possible. Depending on how complex the system is, the entire process can take anywhere from one to four weeks working full time. Thus, it is important to agree to the time commitment before starting the analysis else, anxious managers might stop the procedure before it is completed.
- Research Organization:
- SLAC National Accelerator Lab., Menlo Park, CA (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC02-76SF00515
- OSTI ID:
- 946447
- Report Number(s):
- SLAC-TN-09-001; TRN: US200903%%906
- Country of Publication:
- United States
- Language:
- English
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