Minimizing human fatigue and make-span in a dual resource constrained job shop scheduling problem

Even if the implementation of Industry 4.0 solutions is gaining importance in many companies, workers still have a crucial role in various manufacturing environments. Some tasks cannot be executed only by automatic machines, robots, or other technological solutions due to the knowledge and the approach required to work that only humans can have or for investment reasons. Therefore, in some sectors, such as the assembly lines of large and complex products, workers still represent one of the most important drivers that affect efficiency and productivity. However, human physical capabilities are limited and if they are exceeded fatigue arises, in particular for ageing workers. Physical fatigue has negative consequences both for workers and companies since it impacts the employees’ well-being, product quality and productivity. During the last decade, several models have been proposed to quantify the time required to recover fatigue spent by executing tasks. However, only a few works integrate such models in operational procedures for scheduling tasks for workers to minimize workers’ fatigue and makespan. Moreover, in the scheduling process, idle times occur due to the presence of precedence constraints that cannot be violated. They represent no-value added activities for companies, but they could represent a benefit for workers since they could be used as a rest. Considering dual-resource constrained systems, this work proposes a heuristic approach for job shop scheduling problems. Workers’ fatigue and related recovery time are evaluated according to the workers’ age. Finally, numerical tests are used to compare different scenarios and quantify benefits in terms of productivity and efficiency.