Development and analysis of scheduling decision rules for a dynamic flexible job shop production system: a simulation study

Abstract

The present paper focuses on a simulation-based experimental study of scheduling decision rules for scheduling a typical dynamic flexible job shop production system. The case of partial flexibility is considered wherein an operation can be performed on three different machines. Each operation can be performed efficiently on the primary machine. The other two alternative machines are also capable of performing the same operation, though less efficiently. This is modelled as a percentage increase in the processing time when an operation is performed on an alternate machine. A discrete event simulation model of the job shop system is used as a test bed for experimentation. Three scheduling rules from the literature are used for machine selection decision. A total of 15 scheduling rules from the literature are incorporated in the simulation model for job scheduling decisions. Six new scheduling rules for job scheduling are also developed and investigated. The performance measures evaluated are the mean flow time, standard deviation of flow time, mean tardiness, standard deviation of tardiness and percentage of tardy jobs. The analysis of simulation results reveal that the proposed scheduling rules provide better overall performance for the various measures when compared with the existing scheduling rules.