Modeling and Scheduling of Multi-Stage and Multi-Processor Flow Shop

Abstract

This paper addresses a multi-stage and multi-processor flow shop scheduling problem while minimizing the over utilization of machines. Fuzzy Inference System has been used to determine the job priority, considering factors such as completion times, processing complexity, critical ratio, profit over time, cost over time and level of inventory, while incorporating their uncertainties. In a similar manner, machine priority has been deduced, taking into account the mean time between failure, mean time to repair, mean time between shutdown, mean time between maintenance, failure rate and set up time. The grouping and sequencing of jobs in every stage are determined by an algorithm in such a way that the problem becomes multiobjective with objectives like minimizing the lead time, set up time, level of inventory, while maximizing machine and labor utilization along with profit over time.