An industrial human-robot collaboration case study for workers’ well-being

Abstract

This work showcases an innovative application case of human-robot collaboration in an industrial environment, a scenario less commonly observed than in research settings. The focus is on a collaborative work cell implemented in a manufacturing context, where assembly and screwdriving tasks on a heavy and large part are conducted under the pace determinant of an injection moulding process. The work cell combines the synergistic tasks of an operator, a cobot, an ergonomic workbench and an AI system responsible for decision-making. The AI system balances the trade-off between process needs and operator well-being by considering buffer levels, workers’ perceived physical fatigue and hand preferences. The results show a reduction between 17% and 32% in the total cycle time, a better workload balance, increased job satisfaction and reduced perceived fatigue.