The fuzzy human-robot collaboration assembly line balancing problem

Abstract

Consideration is given to the assembly line balancing problem (ALBP) in production lines employed collaborative robots. Human–robot collaboration promises high advantages in manufacturing regarding automation, productivity, accuracy as well as flexibility in production. This technology is really challenging but requires redesigning of assembly lines to effectively involve the available human- and robot-resources. As robots can collaborate with humans sharing the assembly tasks in the same workstation, production managers experience an increasingly complex ALBP setting. Moreover, a crucial issue raised within this context is the variance and uncertainty in processing times for manual (human) work. Processing times for human work are subject to the nature and skills of the human worker. We explore the heuristic solution of this NP-hard problem using a problem-specific metaheuristic. Our aim is to investigate the effects of utilizing collaborate robots in manual assembly lines with respect to both production rate and workload smoothing. Simulation experiments on a real-life case study borrowed from the literature show how to tackle the problem under uncertainty (fuzziness) in task processing times.