TY - JOUR ID - 166221 TI - A two-objective setting for reducing costs and ergonomic risks of U-shaped assembly line balancing collaborated by robots and human workers JO - Journal of Industrial Engineering and Management Studies JA - JIEMS LA - en SN - 2476-308X AU - Mozaffari, Neda AU - Mehrmanesh, Hasan AU - Mohamadi, Mahmud AD - Faculty of Management, Islamic Azad University Central Tehran Branch, Tehran, Iran. Y1 - 2022 PY - 2022 VL - 9 IS - 2 SP - 113 EP - 128 KW - U-shaped assembly line KW - ergonomic risks KW - human and robot workers KW - Constraint Programming KW - Grasshopper Optimization Algorithm DO - 10.22116/jiems.2022.348827.1495 N2 - Balancing the production system’s resources like budget, equipment, and workers is one of the most important concerns of production managers. Managers seek to find an optimal way to balance their resources in production systems. By evaluating U-shaped assembly line papers, this investigation adds the literature on U-shaped assembly lines to the simultaneous examination of the balance ergonomic risks of human workers and current costs in the system when government offers tax benefits for using disabled workers. The mentioned outlook was not considered in previous papers. This study proposes a two-objective model to evaluate the effects of considering both robots and human workers in a U-shaped assembly line. The first objective is to minimize the system costs, and the second is to minimize the ergonomic risks. Human workers are divided into normal and disabled. The disabled workers are hired to enable tax benefits from the government. The constraint programming model for small and medium-sized problems and the grasshopper optimization algorithm (GOA) for big problems are developed to dissolve the problem. Numerical results show that two objective functions can also level system costs and ergonomic risks. The sensitivity analysis section analyzes three effective parameters (Production cycle time, Fatigue rate of human workers, and government tax benefit). It is shown that production cycle time directly affects using a robot or human workers (due to their mean time of speed), fatigue rate determines the allocation of tasks, and tax benefit helps to determine whether using disabled workers or not according objective functions. Also, it should be noticed the efficiency of GOA is shown by a comparison of several examples. Therefore, it is used for big-scale test problems. UR - https://jiems.icms.ac.ir/article_166221.html L1 - https://jiems.icms.ac.ir/article_166221_ef8f7bc58048841d01e73c4667c84661.pdf ER -