Modeling and performance analysis of a closed-loop supply chain using first-order hybrid Petri nets

Abstract

Green or closed-loop supply chain had been the focus of many manufacturers during the last decade. The application of closed-loop supply chain in today’s manufacturing is not only due to growing environmental concerns and the recognition of its benefits in reducing greenhouse gas emissions, energy consumption, and meeting a more strict environmental regulations but it also offers economic competitive advantages if appropriately managed. First-order hybrid Petri nets represent a powerful graphical and mathematical formalism to map and analyze the dynamics of complex systems such as closed-loop supply chain networks. This article aims at illustrating the use of first-order hybrid Petri nets to model a closed-loop supply chain network and evaluate its operational, financial, and environmental performance measures under different management policies. Actual data from auto manufacturer in the United States are used to validate network’s performance under both tactical and strategic decision-making, namely, (1) tactical decision—production policies: increase of recovered versus new components and (2) strategic decision—closed-loop supply chain network structure: manufacturer internal recovery process or recovery process done by a third-party collection and recovery center. The work presented in this article is an extension of the use of first-order hybrid Petri nets as a modeling and performance analysis tool from supply chain to closed-loop supply chain. The modularity property of first-order hybrid Petri nets has been used in the modeling process, and the simulation and analysis of the modeled network are done in MATLAB® environment. The results of the experiments depict that first-order hybrid Petri nets are a powerful modeling and analysis formalism for closed-loop supply chain networks and can be further used as an efficient decision-making tool at both tactical and strategic levels. Unlike other researches on modeling supply chain networks that focus on evaluating individually cost, operational, or environmental aspects, the research here shows how first-order hybrid Petri nets can be extended to assess simultaneously operational, financial, and environmental network’s performance measures at different managerial decision-making levels. The results particularly are compelling for researchers and industrial practitioners who can use the same methodology in evaluating their network’s performance and making educated management decisions based on the performance results and the impact of their selected supply chain and manufacturing strategies.