Balancing U-type assembly lines with human–robot collaboration

Abstract

In this work, we consider a U-type assembly line balancing problem with human–robot collaboration (UALBP-HRC), in which the collaborative robot (cobot) can either parallelly process different tasks or collaboratively process the same task with workers. A mixed-integer programming (MIP) model is formulated and the objective is to minimize the cycle time for a given number of stations. We further propose an enhanced MIP (EMIP) model by incorporating enhancement strategies, including tight lower bound, upper bound and initial solution. To the best of our knowledge, this study is among the first attempts to address the UALBP-HRC in which both parallel and collaborative tasks are allowed. Due to the NP-hardness of the problem, a simulated annealing algorithm with enhanced search procedure (ESA) is developed to effectively solve the problem. The model functionalities and algorithm effectiveness are evaluated by adapted standard datasets and real case studies. The experimental results show that EMIP outperforms MIP and ESA finds promising solutions compared to MIP, EMIP, simulated annealing algorithm (SA) and genetic algorithm (GA). The comparisons between UALBP-HRC and straight assembly line balancing problem with human–robot collaboration (ALBP-HRC) are also conducted and the managerial insights are concluded.