Affiliations: Faculty of Industrial Engineering, Urmia University of Technology, Urmia, Iran
Correspondence:
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Corresponding author. Saeid Jafarzadeh Ghoushchi, Faculty of Industrial Engineering, Urmia University of Technology, Urmia, Iran. E-mails: [email protected]; [email protected].
Abstract: One of the most crucial components in risk management in an organization is detection of risk modes in a system, prioritization of them and making plans in order to enact corrective actions. And one of the common methods for prioritization of risks is the conventional Failure Mode Effects Analysis (FMEA). Although this approach is widely used in different industries, it suffers from some shortcomings, which can lead to failures in reaching reality-based results. This research study, therefore, proposed an approach in three phases for the compensation of the shortcomings of the FMEA method. In the first phase, the FMEA method was used to detect different risk modes and then assign values to the Risk Priority Number (RPN) determinant factors. In the second phase, the weights of the triple factors were calculated by means of Fuzzy Best-Worst Method (FBWM) and experts’ opinions. And finally, with respect to the outputs of previous phases, the risks were ranked by means of the proposed Z-WASPAS method. In addition to the assignment of different weights to the triple factors and considering the feature of uncertainty in these factors, the proposed approach paid attention to reliability in the risk modes via the Z-Numbers theory. The proposed approach was applied in the operation processes of Mes-e Sarcheshmeh molybdenum factory in Iran and the results indicated a full ranking of risks compared to other conventional methods such as FMEA and fuzzy WASPAS.
