Designing a Dynamic and Sustainable Cellular Manufacturing System by Considering the Amount of Energy Consumption and Manpower in Production Planning

The design and planning of cellular Manufacturing systems in most classical models is based on minimizing production costs or increasing producers' profits. With the expansion of production systems and the increase in demand for products, concerns about environmental issues and excessive consumption of non-renewable resources have increased. On the other hand, paying attention to workers and the safety of the work environment has been introduced as a vital issue in creating a sustainable Manufacturing system. In this article, a new multi-objective mathematical model for creating a sustainable cellular Manufacturing system is presented according to the mentioned items in order to minimize the production costs in the system in addition to optimizing the environmental effects of the Manufacturing system. In the following, the model was solved using the epsilon constraint method and various solutions were presented in the form of a Pareto front for decision making. Due to the NP-hardness of the proposed model and the inability of the GAMS software to find optimal solutions for large-scale problems, a non-dominant sorting genetic algorithm (NSGA-II) is presented to solve it. The results showed that the meta-heuristic method has reduced the solution time by at least three times compared to the epsilon constraint method; Also, reducing the level of environmental risks has led to an increase in production costs. Finally, the applicability of the proposed model in an agricultural equipment production workshop has been investigated as a case study.