Abstract
Abstract Process Failure Modes and Effects Analysis (PFMEA) concept, has been developed based on the success of Failure Modes and Effects Analysis (FMEA) to include a broader analysis team for the realization of a comprehensive analysis in a short time. The most common use of the PFMEA involves manufacturing processes as they are required to be closely examined against any unnatural deviation in the state of the process for producing products with consistent quality. In a typical FMEA, for each failure modes, three risk factors; severity (S), occurrence (O), and detectability (D) are evaluated and their multiplication derives the risk priority number (RPN). However there are many shortcomings of this classical crisp RPN calculation. This study introduces a fuzzy hybrid approach that allows experts to use linguistic variables for determining S, O, and D for PFMEA by applying fuzzy ‘technique for order preference by similarity to ideal solution’ (TOPSIS) and fuzzy ‘analytical hierarchy process’ (AHP). An ap...
Highlights
There exists a continuously increasing demand for quality products in industry and manufacturing systems need to be closely monitored for any unnatural deviation in the state of the process in order to produce products with consistent quality[1]
The potential failures are ranked according to their global weight scores
Later the closeness coefficients are multiplied by the weights of the process functions for finding the global weight scores
Summary
There exists a continuously increasing demand for quality products in industry and manufacturing systems need to be closely monitored for any unnatural deviation in the state of the process in order to produce products with consistent quality[1]. FMEA was first used in NASA in 1963 as a formal design methodology and later Ford Motor adopted and promoted the technique in 1977 due to its obvious reliability requirements[5] After this time, FMEA has become a powerful tool extensively employed for safety and reliability analysis of products and processes in a wide range of industries in aerospace, nuclear and automotive industries[6]. Conventional PFMEA evaluation includes these factors each of which is assigned a value between 1 and 10 (with 1 being the best and 10 being the worst case) and the values of severity (S), occurrence (O), and detectability (D) are multiplied to produce risk priority number (RPN) as RPN = SxOxD.
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