Considering physical workload and workforce diversity in a Collaborative Assembly Line Balancing (C-ALB) optimization model

In comparison to the traditional usage of robots, Cobotization (Human-Robot collaboration) can be considered as an effective way to increase the productivity of assembly lines while ensuring job security and flexibility. However, successful implementation of human-robot collaboration scenarios requires adapted decision support tools. Workforce diversity can be mentioned as one of the factors that should be included to study its impact on both the performance of the production system and on ergonomics. Accordingly, in this research, a new bi-objective optimization model for the collaborative assembly line with Cobots is proposed to simultaneously minimize the cycle time and the physical workload of human operators. The workforce diversity of human operators is modeled through experience level and physical ability. To analyze the benefits of the developed model, a comparison between the different solutions from the Pareto front is conducted. The results show that the utilization of Cobots can reduce both cycle time and physical workload in the assembly line. Copyright (C) 2022 The Authors.

Automated summary

In comparison to traditional robot usage, Human-Robot collaboration (Cobotization) is an effective way to increase assembly line productivity while ensuring job security and flexibility. This research proposes a new bi-objective optimization model for collaborative assembly lines with Cobots, which successfully reduces both cycle time and physical workload, as validated through a comparison of different solutions.