A Hybrid Fuzzy FMEA Framework for Sustainable Supply Chain Risk Prioritization
Keywords:
Sustainable supply chain , risk management , fuzzy AHP , fuzzy EDAS , FMEA , food supply chainAbstract
Sustainable supply chain management (SSCM) focuses on managing economic, environmental, and social impacts across supply chain activities. In recent years, identifying and managing sustainable supply chain risks has become increasingly important for companies aiming to build resilient and responsible supply chains.
This study aims to identify and prioritize sustainable supply chain risk factors by proposing a decision-support framework based on a hybrid Failure Mode and Effects Analysis (FMEA) approach. The proposed methodology integrates traditional FMEA with a multi-criteria decision-making (MCDM) framework combining the Fuzzy Analytic Hierarchy Process (Fuzzy AHP) and the Fuzzy Evaluation based on Distance from Average Solution (Fuzzy EDAS). Fuzzy AHP is used to determine the weights of risk criteria (occurrence, severity, and detection), while Fuzzy EDAS is applied to rank sustainable supply chain risks.
The proposed framework is applied in a global confectionary company through a survey conducted with ten decision makers. The results reveal that management policy failure is the most critical risk factor.In addition, social sustainability risks such as child labor/forced labor and unfair wages were identified as significant risk factors affecting sustainable supply chains. These findings are consistent with the characteristics of chocolate supply chains, which rely heavily on labor-intensive agricultural raw materials and therefore may be more vulnerable to social sustainability risks.
The proposed framework provides a systematic and practical tool for decision makers to identify and prioritize sustainable supply chain risks and supports the development of more sustainable and resilient supply chain strategies.
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