Modelling and optimization of line efficiency for preventive maintenance of robot disassembly line

Abstract

Regular preventive maintenance of the robot is the key to ensure accurate and stable operation of the robot. It is also an important step to achieve long-term stability of the disassembly line. At present, there is a lack of joint research on preventive maintenance and conventional disassembly for robot disassembly line balancing problem. This study will integrate the joint optimization of the two for conventional disassembly scenario and preventive maintenance scenarios of robot disassembly line. A mixed integer linear programming model considering preventive maintenance of robot disassembly is established, which aims to optimize the disassembly efficiency of conventional disassembly scenario and preventive maintenance disassembly scenario, and optimize the conversion efficiency of the two scenarios. The fore-and-aft tool replacement of the robot in the proposed model is also considered to be closer to the actual disassembly scenario. This study will design a multi-objective improved genetic simulated annealing that matches the problem characteristics to efficiently solve large-scale problems. The performance of the proposed algorithm is verified by solving 21 benchmarks containing task sizes ranging from 7 to 145. Then the correctness of the proposed model and algorithm is verified bidirectionally by analyzing the exact results and the results of the proposed algorithm from a small-scale case. Finally, the performance of the algorithm is further tested through a laptop disassembly case, and the results are analyzed comprehensively to show the importance of the disassembly characteristics considered in the preventive maintenance of the robot.