Scheduling of Robotic Disassembly in Remanufacturing Using Bees Algorithms

Abstract

Traditional manufacturing pays much attention to profit without giving due regard to pollutant emission. Remanufacturing is being paid increasing attention due to resource saving and environment protection. Disassembly is an inevitable key step of remanufacturing and always carried out by manual labor, which incurs high cost and has low efficiency. Thus robotic disassembly is proposed to address these shortcomings. Scheduling of robotic disassembly, which mainly contains robotic disassembly sequence planning (RDSP) and robotic disassembly line balancing problem (RDLBP), realizes the disassembly efficiency improvement and the disassembly cost reduction. The Bees algorithm has shown great competitiveness compared with the other optimization algorithms and is seldom used in scheduling of robotic disassembly. In this chapter, RDSP and RDLBP are solved by Bees algorithms (BA). First, it is necessary to establish the disassembly model. Then, after considering the safe distance between the products and the end-effector, the end-effector's moving speed and the obstacle avoidance path length are utilized to obtain the end-effector's moving time. The optimization objectives of RDSP and RDLBP are also described. Next the optimal solutions of scheduling of robotic disassembly are obtained by BA. Finally, case studies of a gear pump are utilized to verify the proposed methods. Results show that the proposed methods are more applicable to solve RDSP and RDLBP than traditional methods. For RDSP, the enhanced discrete Bees algorithm (EDBA) performs better than genetic algorithm with precedence preserve crossover (GA-PPX) and self-adaptive simplified swarm optimization (SASSO) in terms of solution quality. For RDLBP, the improved multi-objective discrete Bees algorithm (IMODBA) performs better than the multi-objective genetic algorithm (MOGA) and multi-objective artificial bee colony with respect to hypervolume indicator (HI) and generational distance (GD).