Balancing parallel assembly lines with human-robot collaboration: problem definition, mathematical model and tabu search approach
Zhaofang Mao, Jiaxin Zhang, Yiting Sun, Kan Fang, Dian Huang
Abstract
Human-robot collaboration (HRC), as an emerging production mode, has garnered significant attention in the context of the growing smart manufacturing. This study aims to investigate the application of human-robot collaboration in parallel assembly lines and explore its potential for improving productivity, resource utilisation and flexibility. To the best of our knowledge, this is one of the first attempts to consider the combination of parallel assembly line balancing problem (PALBP) and human-robot collaboration. In this study, the parallel assembly line balancing problem with human-robot collaboration (PALBP-HRC) is introduced and characterised. The collaboration mode allows human workers and robots to execute tasks both in parallel and in collaboration. A mixed-integer programming model (MIP) that minimises the cycle time is formulated and a lower bound is proposed. Due to the NP-hardness, we develop an adapted tabu search (TS) algorithm specifically tailored for problem characterisation. Experimental results indicate that the proposed TS algorithm achieves competing performance compared to the MIP and other algorithms, including genetic algorithm (GA) and simulated annealing (SA) algorithm. The comparison between PALBP and PALBP-HRC demonstrates that the integration of human-robot collaboration to parallel assembly line can achieve significant improvements in efficiency and flexibility.