Assembly line rebalancing problem with human-robot collaboration and a hyper-matheuristic solution approach

Abstract

In the context of the Industry 5.0 vision, which emphasises the importance of human-centred industries, assembly lines wherein humans and robots work together have emerged as innovative systems that allow the advantages of both to be combined. Accordingly, industrial managers are attempting to implement collaborative systems that will benefit from the consistency of robots and their capacity to work in hazardous environments, as well as the insight and adaptability of humans. Nevertheless, the process of eliminating an existing system and building another one from scratch is both costly and time-consuming. Rather than constructing an entirely new system, it is possible to reconfigure the line based on the new situation, thus enabling the system to adapt to changes. To the best of our knowledge, studies in the literature on collaborative assembly lines have focused on the initial installation phase, while the researchers who have dealt with the rebalancing process have not taken into account the change in the workforce structure as a reason for rebalancing. This study introduces the Assembly Line Rebalancing Problem with Human-Robot Collaboration as a means of filling the perceived gap in the literature. The considered problem addresses the need for line rebalancing to integrate traditional and collaborative robots as operators in existing manual assembly lines. In order to tackle this problem, a mathematical modelling approach and an artificial bee colony algorithm-based hyper-matheuristic algorithm are presented with the objective of optimising cycle time. The results of the computational tests on benchmark problems adapted from the literature demonstrate that the proposed algorithm outperforms the mathematical modelling approach and basic artificial bee colony algorithm.