A Fuzzy Supply Chain Model Evaluating Energy Management Systems under Imperfect Production and Uncertain Costs

Abstract

To assess the impact of energy management systems in supply chain with varying cost parameters along with carbon emissions enhancing sustainability, minimizing expenses while ensuring operational efficiency. In this study, a non-linear sustainable supply chain model is developed by incorporating an energy management system and considering a varying cost parameter to reflect real-world complexities. In practical production environments, systems often fail to produce perfectly flawless items due to various unpredictable factors. To address such uncertainties, single-valued trapezoidal neutrosophic fuzzy parameters are employed in the model. Furthermore, recognizing the significant impact of carbon emissions on global warming, the model integrates the cost of carbon emissions across different processes. Finally, the Lagrangian method is applied to derive the optimal solution for the formulated problem. The proposed model has been solved using the prescribed optimization method, yielding a total cost of 398,181 for the manufacturing firm with investment in energy management systems, compared to a total cost of 461,634 for the firm without such investment. This significant reduction in total cost clearly demonstrates that the implementation of energy management systems enhances the overall performance and cost-efficiency of the manufacturing process. The efficiency of energy management systems considering varying cost parameters and carbon emissions under single-valued trapezoidal neutrosophic fuzzy environments has not yet been thoroughly investigated in the existing literature.