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HSE risk prioritization using robust DEA-FMEA approach with undesirable outputs

HSE risk prioritization using robust DEA-FMEA approach with undesirable outputs: A study of automotive parts industry in Iran Nowadays, manufacturers realize that enhancing attention in health, safety and environment (HSE) management system…

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HSE risk prioritization using robust DEA-FMEA approach with undesirable outputs

HSE risk prioritization using robust DEA-FMEA approach with undesirable outputs: A study of automotive parts industry in Iran Nowadays, manufacturers realize that enhancing attention in health, safety and environment (HSE) management system leads to significant success in their activities. In order to accomplish HSE integrated management, the first step is identification and assessment of potential risks to control them, which may increase the protection level of employee and efficiency of work environment. Failure modes and effect analysis (FMEA) is one the most used methods in risk assessment. However, conventional FMEA disadvantages such as using risk priority number (RPN) to prioritize risks make this method inefficient in industries. The aim of this study is to present an integrated robust data envelopment analysis (RDEA)-FMEA approach to evaluate and prioritize HSE risks in various industries and to cover disadvantages of traditional scoring system of RPN in FMEA method. In fact, in the present study, prioritization of HSE risks are carried out by considering two extra parameters including cost and duration of treatment (as outputs) in addition to three parameters of severity, occurrence, and detection (as inputs). Additionally, uncertainty and undesirability of mentioned parameters are considered simultaneously. The proposed approach was implemented in a company active in manufacturing spare parts of automotive and then results were compared to conventional DEA model and RPN scores. The results indicate that, ranking risks according to this extension compared to traditional FMEA, leads to a more reliable and convincing prioritization.