Multi-AGV Flexible Manufacturing Cell Scheduling Considering Charging

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.

Implementation of Automated Guided Vehicles for the Automation of Selected Processes and Elimination of Collisions between Handling Equipment and Humans in the Warehouse

“…The maximum speed achieved with the load is 1.5 m/s. The device is a manipulator robot with a jacking mechanism, which is based on an operation using simultaneous localization and mapping (SLAM) lasers [33]. SLAM is the process of mapping an area while tracking the location of a device in that area.…”

“…Fast charging has a significant positive impact on the battery life, enabling it to operate continuously for a full 24 h. The lithium battery can be charged in auto-charging mode or manually and has a duration of 8 h on a full charge. A continuous connection of 3 h is required to fully charge the battery through either continuous charging or being connected to the charger [33]. The selected AGV model also has specified conditions when it cannot be deployed and used.…”

“…Automated guided vehicle systems are used for tasks that would normally be performed by forklifts, conveyor systems, or hand trucks, which move large volumes of material repeatedly [33].…”

“…From the perspective of the terrain, riding on uneven, obstructive, or stepped surfaces is prohibited [33].…”

Multi-AGV Scheduling under Limited Buffer Capacity and Battery Charging Using Simulation Techniques

“…Meanwhile, studies on the topic of AGV battery charging have also looked into issues like power management and energy efficiency. Li et al [22] developed a multiobjective nonlinear programming model based on a genetic algorithm to minimize the maximum completion time in a flexible manufacturing cell, considering the battery charging and waiting time of AGVs. Additionally, the influence of various loads on AGV power consumption was discussed.…”