Scheduling optimization to minimize total weighted tardiness in environments with stochastic rework and reprocessing

This research proposes a mixed integer programming model for the electronics manufacturing industry with stochastic rework and reprocessing times. The complex assembly process in the electronics assembly poses several opportunities for defects resulting in rework to recover the cost and value added to the product. This leads to jobs spending more time in the manufacturing facility leading to increased job tardiness. Hence, the objective of this research is to optimize the job sequences in the manufacturing process considering the rework and reprocessing times. An optimal solver is used to solve the mathematical model to minimize the Total Weighted Tardiness (TWT). Also, a heuristic methodology considering the 'Total Estimated Processing Time' (TEPT), a linear combination of rework and reprocessing times, is developed to solve the NP-hard problem. A modified Genetic Algorithm to reroute defective jobs is also developed for this research problem. Numerical examples on single-machine and multi-machine setups indicate the superior performance of the developed methodologies compared to an optimal solver and different conventional dispatch rules.