A novel resilient supplier and order allocation model with pythagorean fuzzy sets based on Industry 4.0 initiatives

Abstract

When disruptions or failures occur for any actor connected with global supply chain networks, it can affect all actors including suppliers, manufacturers, contractors, or freight forwarders. Supplier interruptions can impose crucial losses on the entire supply chain by halting supply flows, akin to a domino effect. Resilient supplier selection is at the heart of current supply chain management thinking and guides the correct understanding of this concept by quickly responding to and eliminating disruptions. Industry 4.0 (I4.0) and related enablers are emerging as important drivers of the supplier selection process. Motivated by these issues, this study discusses a fuzzy multi-objective linear programming (FMOLP) model in the context of I4.0 enablers and resilience strategies to trade-off between resilience, I4.0, and operations cost. For the supplier selection process, four resilient, three I4.0, and three traditional criteria have been considered. For the order allocation process, the evaluation of suppliers is evaluated by Pythagorean fuzzy numbers, and a FMOLP model is developed for resilient supplier selection and order allocation problem. The model’s objectives are the minimization of purchasing and operations costs, maximization of resilience value, and maximization of suppliers’ assessment against I4.0 enablers. The pythagorean fuzzy analytic hierarchy process is used to acquire the importance levels of these objectives. A case study from Turkey’s machinery manufacturing industry is used to demonstrate the applicability of the proposed framework. The proposed model assists decision-makers in allocating the optimum order quantities under various strategies, as it simultaneously considers I4.0 enablers and resilience strategies. It is observed that the manufacturers are willing to incorporate I4.0 enablers and resilience strategies into supplier selection.