Scheduling in Flexible Flow Shop Environments with Re-Entrant Jobs and Heterogeneous Workers

Abstract

In many industries, manufacturing is organized as a flexible flow shop (FFS), which has gotten the researchers' attention. The scheduling studies, particularly those on FFS scheduling, are concerned with homogeneous workers with the same skill set or heterogeneous workers who can only perform one specific type of operation on the production lines. Moreover, jobs are mainly assumed to go through an operation once. Yet, in real-life production, workers might have different skill sets with varying processing times. Furthermore, certain jobs may require revisiting the same machine multiple times, i.e., re-entrant jobs. We study an FFS environment with re-entrant jobs, considering worker flexibility. We propose a mixed integer linear programming model to find the optimal sequences of jobs to be processed by the multiskilled workers assigned to the production system, ensuring each re-entrant job waits for a predefined time window before reprocessing on the same operation. The objective of the model is to minimize makespan. We tested the proposed model on a dataset taken from a real production system of a PVC windows and doors production facility