Risk Assessment by a New FMEA Model based on an Extended AHP Method under a Fuzzy Environment

Document Type : Research Article


1 Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

2 North Kargar Street, School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran

3 Department of Industrial Management, Vali-e-Asr University of Rafsanjan, Rafsanjan, Iran

4 Department of Industrial Engineering, KHATAM University, Tehran, Iran



Risk assessment has an essential role in managing different risks and their effects. A failure mode and effects analysis (FMEA), as one of the most famous risk assessment tools, has frequently been used in a wide range of industries and organizations. In this study, a new fuzzy analytic hierarchy process (AHP)-based FMEA model is introduced for evaluating the risks of various failure modes more precisely. In this model, fuzzy weighted aggregated risk priority numbers (FWARPNs) are taken into consideration instead of risk priority numbers (RPNs) for the failure modes. Moreover, considering that an economic criterion is added to the three main risk factors, the FWARPNs are calculated by utilizing four risk factors of occurrence (O), severity (S), detection (D), and cost (C). The new criterion (C) denotes the required cost for eliminating the effects of failure occurred. Also, the weights of these four risk factors are computed by an extended fuzzy AHP method. For enhancing the efficiency of the proposed model, a novel fuzzy numbers ranking method is also applied in both suggested fuzzy FMEA and AHP methods. This new ranking method is based on creating different horizontal α-cuts in fuzzy numbers. Finally, to indicate the practicability and effectiveness of the proposed model, Kerman Ghete Gostar Casting Plant is considered as a case study in which the risks of toxic gas release are assessed by the suggested fuzzy FMEA model. The obtained results show that the proposed model is a practicable and advantageous risk assessment method in the real world.