Modelling worker fatigue and recovery in dual-resource constrained systems

The operational benefits that dual-resource constrained (DRC) job shop systems bring have captured the attention of researchers for some time. Although several studies that investigate DRCs are available in the literature, none has investigated a DRC system for the effects of human fatigue and recovery, which poses important parameters to avoiding overload and injury to employees. The purpose of this paper is to address this limitation by presenting a mixed-integer linear programming (MILP) model that describes fatigue and recovery in a DRC system with one worker performing n tasks (flexibility level) within m cycles. Later, the complexity of the MILP problem was reduced to four practical cases. These cases were investigated to evaluate several research questions. The results obtained from the MILP model and the four practical cases suggest that short rest breaks after each task, short cycle times and faster recovery rates improve the system’s performance and that reduced force levels in the work tasks will reduce recovery needs and further increase performance. Further research is still needed to identify or to develop better models of physiological and mental fatigue that can be integrated to the modelling framework presented here.