Assessment of structural risks using the fuzzy weighted Euclidean FMEA and block diagram analysis
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Failure mode and effects analysis (FMEA) is a risk assessment method in products, processes, or systems for appropriate corrective actions. Although FMEA techniques are used in various industries, it has been criticized for several shortcomings. First, conventional FMEA entirely depends on qualitative evaluation. Second, traditional FMEA does not consider the functional influence between components of a system, meaning that it cannot be applied to systems-complicated influence relationships. Third, risk priority number (RPN) in traditional FMEA, which is evaluated in crisp values of severity (S), occurrence rate (O), and the probability of not detecting the failure (D), can lead to a RPN distortion problem in which contradictory interpretations of RPN result from, respectively, reasonable risk factors. In order to overcome these shortcomings, this paper proposes a new risk assessment method using importance risk priority number (IRPN). The IRPN, which is composed of structural and relational importance, is attained by taking a three-dimensional geometric approach to fuzzy weighted Euclidean (FWE) FMEA and risk block diagram analysis. The proposed risk assessment method is applied in the numerical example and empirical example of the thin film transistor liquid crystal display (TFT-LCD) products. Comparison results with previous FMEA methods show that the proposed method not only overcomes the shortcomings of previous FMEA methods, such as the RPN distortion, but is also useful for assessing the structural risks that involve functional influence between risks. In addition, a three-dimensional approach based on fuzzy logic is more analytical and applicable than previous methods.
KeywordsFailure mode and effect analysis Fuzzy weighted Euclidean Block diagram analysis Relational importance Structural importance
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This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No. NRF-2016R1A2B1008163).
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