Risk Assessment Framework for Reverse Logistics in Waste Plastic Recycle Industry: A Hybrid Approach Incorporating FMEA Decision Model with AHP-LOPCOW- ARAS Under Trapezoidal Fuzzy Set

Detcharat Sumrit; Jirawat Keeratibhubordee

doi:10.31181/dmame812025984

Authors

Detcharat Sumrit The Cluster of Logistics and Rail Engineering, Faculty of Engineering, Mahidol University, Phuttamonthon, Thailand https://orcid.org/0000-0003-3157-6697
Jirawat Keeratibhubordee The Cluster of Logistics and Rail Engineering, Faculty of Engineering, Mahidol University, Phuttamonthon, Thailand https://orcid.org/0009-0005-0143-8762

DOI:

https://doi.org/10.31181/dmame812025984

Keywords:

Failure Mode Effect Analysis (FMEA),, Analytic Hierarchy Process (AHP), LOgarithmic Percentage Change-driven Objective Weighting (LOPCOW), Additive Ratio Analysis (ARAS), Trapezoidal fuzzy set (TrFS)

Abstract

In this study, a novel risk assessment framework designed for evaluating the challenges of plastic packaging waste management in the context of reverse logistics is introduced. The framework leverages Failure Mode Effect Analysis (FMEA) to address decision-making in a fuzzy environment. To augment the traditional FMEA risk criteria, encompassing severity (S), occurrence (O), and detection (D), three additional essential risk criteria are introduced: cost of failure (C), complexity of failure resolution (H), and impact on business (I). These newly incorporated criteria significantly enhance the capacity to convey the multifaceted risks inherent in reverse logistics for the plastic recycling sector. Furthermore, a comprehensive literature review and expert validation are conducted to identify ten distinct failure modes. To subjectively and objectively determine the risk criteria weightings, a combination of Analytic Hierarchy Process (AHP) and LOgarithmic Percentage Change-driven Objective Weighting (LOPCOW) is employed. Finally, the Additive Ratio Assessment (ARAS) approach is applied to prioritize such failure modes. Recognizing the inherent imprecision and uncertainty associated with human decision-making, the trapezoidal fuzzy set (TrFS) is adopted throughout all decision-making processes. To showcase the proposed framework effectiveness, the framework is applied as a case study to a waste plastic recycling manufacturer in Thailand.

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