A novel FMEA model based on fuzzy multiple-criteria decision-making methods for risk assessment

A developed gained and lost dominance score method for risk prioritization in FMEA with Fermatean fuzzy information

Failure mode and effect analysis (FMEA) is one of the most effective means for potential systematic risk assessment in a real work environment. Nevertheless, the traditional FMEA approach has been extensively criticized for many deficiencies in coping with risk evaluation and prioritization problems under inter-uncertain environments. To overcome the limitations, in this paper, a synthesized risk priority calculation framework is proposed for FMEA by combining the gained and lost dominance score (GLDS) method, the combination ordered weighted averaging (C-OWA) operator, and Fermatean fuzzy set (FFS). Firstly, we use FFS to express the experts’ uncertain risk evaluation information which can depict the fuzziness and ambiguity of the information. Secondly, the C-OWA operator combined with FFS is introduced to build the group risk matrix which can provide a more reasonable risk analysis result. Then, the developed GLDS method with FFS is presented to calculate the risk priority of each failure mode which takes both individual and group risk attitudes into consideration. Finally, a medical device risk analysis case is introduced to demonstrate the proposed FMEA framework. We also perform comparison analyses to confirm the effectiveness and rationality of the hybrid risk prioritization framework for FMEA under a complex and uncertain situation.

Supply chain sustainability risk assessment model using integration of the preference selection index (PSI) and the Shannon entropy

Purpose

This study proposes a new model for assessing supply chain sustainability risk integrating subjectivity and objectivity of decision-maker. Research has shown the vacancy of study in dealing with the above issue. To fill this research gap, a new decision support model considering the subjectivity and objectivity of decision-makers in assigning the weight of the supply chain risk reprioritization criteria is presented and demonstrated using a case example.

Design/methodology/approach

This study adopts a new decision support model for assessing supply chain sustainability risk based on additional failure mode and effect analysis (FMEA) parameters and its integration with preference selection index (PSI) methodology and the Shannon entropy. A case example of the supply chain small and medium enterprise (SME) producing handy crafts has been used in this study.

Findings

The result of the study reveals critical sustainability risk dimensions and their risk elements demanding management attention to support realization to a more sustainable business operation.

Research limitations/implications

The use of a single case study is often associated as a limitation in the research studies, and this study is based on findings from SMEs in the handy craft sector in a developing country. Nonetheless, future studies may focus on replicating this study using more samples. This preliminary study provides academics and practitioners with an exemplar of supply chain sustainability risk assessment from the SME in a developing country.

Practical implications

The result of this study is beneficial for practitioners, particularly owner-managers of SMEs who can use this study as guidance on how to identify and select the critical sustainability risks and plan mitigating strategies accordingly.

Originality/value

Scientific effort on appraising criticality of supply chain sustainability risks considering subjectivity and objectivity of decision-maker simultaneously is missing in earlier studies. To the best of the author’s knowledge, this is the first paper applying the PSI and Shannon entropy method and using it for evaluating the impact of supply chain risk based on five sustainability pillars. The findings and suggestions for future research initiatives will provide new insights for scholars and practitioners in managing SME supply chain sustainability risks.

Risk management in occupational safety: A systematic mapping

BACKGROUND

Occupational safety risk management is a systemic process capable of promoting technical engineering solutions, considering a wide range of predictable, unexpected and subjective factors related to accident occurrences. In Brazil, the behavior of managers in relation to risk management tends to be reactive, and facilitates access to information for crucial practical and academic purposes when it comes to changing the attitude of managers, so that their actions become increasingly more proactive.

OBJECTIVE

To identify, classify, analyze, and discuss the existing literature related to the topic, produced from 2008 to 2020, besides contributing to a broader understanding of risk management in occupational safety.

METHODS

We did a systematic literature mapping. The research process was documented starting by the planning stage. Afterwards, the focus was on research conduction and information synthesis.

RESULTS

Knowledge systematization and stratification about OHS risk management through various perspectives to identify, analyze and manage risks in the workplace. Were identified 37 tools for identifying and analyzing risks, management-related practices and future research trends.

CONCLUSIONS

The set of tools and management practices identified can be used as a support for decision making in the selection process of tools and practices to reduce risks and improve occupational safety. Also, the results can help target future research.

A Novel Hybrid Approach for Risk Evaluation of Vehicle Failure Modes

This paper addresses the problem of evaluating vehicle failure modes efficiently during the driving process. Generally, the most critical factors for preventing risk in potential failure modes are identified by the experience of experts through the widely used failure mode and effect analysis (FMEA). However, it has previously been difficult to evaluate the vehicle failure mode with crisp values. In this paper, we propose a novel hybrid scheme based on a cost-based FMEA, fuzzy analytic hierarchy process (FAHP), and extended fuzzy multi-objective optimization by ratio analysis plus full multiplicative form (EFMULTIMOORA) to evaluate vehicle failure modes efficiently. Specifically, vehicle failure modes are first screened out by cost-based FMEA according to maintenance information, and then the weights of the three criteria of maintenance time (T), maintenance cost (C), and maintenance benefit (B) are calculated using FAHP and the rankings of failure modes are determined by EFMULTIMOORA. Different from existing schemes, the EFMULTIMOORA in our proposed hybrid scheme calculates the ranking of vehicle failure modes based on three new risk factors (T, C, and B) through fuzzy linguistic terms for order preference. Furthermore, the applicability of the proposed hybrid scheme is presented by conducting a case study involving vehicle failure modes of one common vehicle type (Hyundai), and a sensitivity analysis and comparisons are conducted to validate the effectiveness of the obtained results. In summary, our numerical analyses indicate that the proposed method can effectively help enterprises and researchers in the risk evaluation and the identification of critical vehicle failure modes.