Multi-AGV Flexible Manufacturing Cell Scheduling Considering Charging

Jianxun Li, Wenjie Cheng, Kin Keung Lai () and Bhagwat Ram
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Jianxun Li: School of Economics and Management, Xi’an University of Technology, Xi’an 710048, China
Wenjie Cheng: School of Economics and Management, Xi’an University of Technology, Xi’an 710048, China
Kin Keung Lai: International Business School, Shaanxi Normal University, Xi’an 710048, China
Bhagwat Ram: Centre for Digital Transformation, Indian Institute of Management Ahmedabad, Vastrapur 380015, India

Mathematics, 2022, vol. 10, issue 19, 1-15

Abstract: Because of their flexibility, controllability and convenience, Automated Guided Vehicles (AGV) have gradually gained popularity in intelligent manufacturing because to their adaptability, controllability, and simplicity. We examine the relationship between AGV scheduling tasks, charging thresholds, and power consumption, in order to address the issue of how AGV charging affects the scheduling of flexible manufacturing units with multiple AGVs. Aiming to promote AGVs load balance and reduce AGV charging times while meeting customer demands, we establish a scheduling model with the objective of minimizing the maximum completion time based on process sequence limitations, processing time restrictions, and workpiece transportation constraints. In accordance with the model’s characteristics, we code the machine, workpiece, and AGV independently, solve the model using a genetic algorithm, adjust the crossover mutation operator, and incorporate an elite retention strategy to the population initialization process to improve genetic diversity. Calculation examples are used to examine the marginal utility of the number of AGVs and electricity and validate the efficiency and viability of the scheduling model. The results show that the AVGs are effectively scheduled to complete transportation tasks and reduce the charging wait time. The multi-AGV flexible manufacturing cell scheduling can also help decision makers to seek AGVs load balance by simulation, reduce the charging times, and decrease the final completion time of manufacturing unit. In addition, AGV utilization can be maximized when the fleet size of AGV is 20%-40% of the number of workpieces.

Keywords: AGV scheduling; flexible manufacturing cell; AGV charging; genetic algorithm (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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