An optimization approach for predictive-reactive job shop scheduling of reconfigurable manufacturing systems

A. A. Abdul Rahman*, O. J. Adeboye, J. Y. Tan, M. R. Salleh, M. A. A. Rahman

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

The manufacturing industry is now moving forward rapidly towards reconfigurability and reliability to meet the hard-to predict global business market, especially job-shop production. However, even if there is a properly planned schedule for production, and there is also a technique for scheduling in Reconfigurable Manufacturing System (RMS) but job-shop production will always come out with errors and disruption due to complex and uncertainty happening during the production process, hence fail to fulfil the due-date requirements. This study proposes a generic control strategy for piloting the implementation of a complex scheduling challenge in an RMS. This study is aimed to formulate an optimization-based algorithm with a simulation tool to reduce the throughput time of complex RMS, which can comply with complex product allocations and flexible routings of the system. The predictive-reactive strategy was investigated, in which Genetic Algorithm (GA) and dispatching rules were used for predictive scheduling and reactivity controls. The results showed that the proposed optimization-based algorithm had successfully reduced the throughput time of the system. In this case, the effectiveness and reliability of RMS are increased by combining the simulation with the optimization algorithm.
Original languageEnglish
Pages (from-to)793-809
Number of pages17
JournalJordan Journal of Mechanical and Industrial Engineering
Volume16
Issue number5
Publication statusPublished - 01 Dec 2022

Keywords

  • Genetic algorithm
  • Optimization
  • Predictive-reactive
  • Reconfigurable manufacturing system
  • Scheduling
  • Simulation

ASJC Scopus subject areas

  • Mechanical Engineering
  • Industrial and Manufacturing Engineering

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