An intuitionistic fuzzy linear mathematical model to determine the hybrid manufacturing system’s optimal operation condition

• Published in: Engineering applications of artificial intelligence 2023-09, Vol.124, p.106519, Article 106519
• Main Authors: Dinler, Esra, Atalay, Kumru Didem, Ic, Yusuf Tansel
• Format: Article
• Language: English
• Subjects: Intuitionistic fuzzy linear programming; Production planning; Recoverable systems; Remanufacturing; Uncertainty
• ISSN: 0952-1976; 1873-6769
• DOI: 10.1016/j.engappai.2023.106519

The recycling of the used products collected by the manufacturing companies for recycling from their customers and their inclusion in the production system for remanufacturing has become an essential topic regarding sustainable production systems. Using parts and equipment in the remanufacturing system, especially in electronic products and products in the automotive sector, is preferred because of the opportunities to reduce costs and increase energy and workforce efficiency. In this article, we analyzed the management of a hybrid production system that processes new or returned materials in the manufacturing system. An intuitionistic fuzzy linear mathematical model is developed to demonstrate financial benefit and make decisions about using used parts in remanufacturing systems. Our study contributes to the literature by first adapting the magnitude function to the hybrid manufacturing and remanufacturing process optimization problem. Also, the innovative scope of the paper is expanded by applying IVITFN to the remanufacturing process optimization problem for the first time using comparative analysis. We consider relevant costs, the uncertainty about the number of returned products, demand, unit costs and unit production times, and capacity limitation in determining the optimal operation condition. The proposed model results show smaller cost values against other models in the literature.