Assessment and Prioritize Risk Factors of Financial Measurement of Management Control System for Production Companies Using a Hybrid Z-SWARA and Z-WASPAS with FMEA Method: A Meta-Analysis

A hybrid generalized TODIM based risk prioritization method for failure mode and effect analysis with linguistic Z-numbers

The traditional failure mode and effect analysis (FMEA), as an effective risk analysis technique, has several limitations in the uncertainty modeling and the weights determination of the risk indicators. This paper aims to propose a hybrid risk prioritization method simultaneously considering the characteristics of the reliability associated with the FMEA team members’ evaluation information and their psychological behavior to enhance the performance of the traditional FMEA model. The hybrid risk prioritization method is developed based on the generalized TODIM method and the weighted entropy measure with the linguistic Z-numbers (LZNs). First, the LZNs are adopted to depict the FMEA team members’ cognition information and the reliability of these information. Second, a weighted entropy measure based on the fuzzy entropy and the LZNs is developed to obtain the risk indicators’ weights. Finally, the generalized TODIM method with the LZNs is constructed to obtain the risk priority orders of failure modes, which can effectively simulate the FMEA team members’ psychological character. The applicability and effectiveness of the proposed risk prioritization method is validated through an illustrative example of an integrated steel plant. The results of sensitivity analysis and comparative analysis indicate that the proposed hybrid risk prioritization method is effective and valid, and can get more accurate and practical risk ranking results to help enterprises formulate accurate risk prevention and control plans.

Road safety assessment and risks prioritization using an integrated SWARA and MARCOS approach under spherical fuzzy environment

There are a lot of elements that make road safety assessment situations unpredictable and hard to understand. This could put people's lives in danger, hurt the mental health of a society, and cause permanent financial and human losses. Due to the ambiguity and uncertainty of the risk assessment process, a multi-criteria decision-making technique for dealing with complex systems that involves choosing one of many options is an important strategy of assessing road safety. In this study, an integrated stepwise weight assessment ratio analysis (SWARA) with measurement of alternatives and ranking according to compromise solution (MARCOS) approach under a spherical fuzzy (SF) set was considered. Then, the proposed methodology was applied to develop the approach of failure mode and effect analysis (FMEA) for rural roads in Cosenza, southern Italy. Also, the results of modified FMEA by SF-SWARA-MARCOS were compared with the results of conventional FMEA. The risk score results demonstrated that the source of risk (human) plays a significant role in crashes compared to other sources of risk. The two risks, including landslides and floods, had the lowest values among the factors affecting rural road safety in Calabria, respectively. The correlation between scenario outcomes and main ranking orders in weight values was also investigated. This study was done in line with the goals of sustainable development and the goal of sustainable mobility, which was to find risks and lower the number of accidents on the road. As a result, it is thus essential to reconsider laws and measures necessary to reduce human risks on the regional road network of Calabria to improve road safety.