Balancing, sequencing, and job rotation scheduling of a U-shaped lean cell with dynamic operator performance

Performance of a manufacturing cell is dependent on an efficient layout design, and optimal work schedules. However, the operator-dependent factors such as learning, forgetting, motivation, and boredom, can considerably impact the output of the system. In this study, we consider heterogeneous operators with dynamic performance metrics and integrate the job assignment, and job rotation scheduling problems, with the balancing and production sequencing in a U-shaped lean manufacturing cell. We present a novel multi-period nonlinear mixed-integer model to minimize the deviations from takt time, and the number of operators, in a finite planning horizon. An efficient meta-heuristic approach is developed to solve the problem and the results are compared to a static case where no human factor is included. Our computational results demonstrate that including the operator-dependent metrics can improve the performance of the cell design. We conduct a sensitivity analysis of the scheduling parameters including, rotation frequencies, takt time, cell size, and task types, and derive that the obtained solutions with the static settings, are not sufficient for an efficient lean cell design in the presence of dynamic human factors