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A multi-objective joint optimisation method for simultaneous part family formation and configuration design in delayed reconfigurable manufacturing system (D-RMS)

Huang, S ; Sharif University of Technology | 2024

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  1. Type of Document: Article
  2. DOI: 10.1080/00207543.2023.2223725
  3. Publisher: 2024
  4. Abstract:
  5. In the era of Industry 4.0, the demand fluctuation has become fiercer due to the characteristics of diversification, customisation, and uncertainty. Reconfigurability of manufacturing systems has been proven to be a useful and necessary feature when it comes to handling demand uncertainty. This feature can be achieved through the implementation of reconfigurable manufacturing system (RMS) and delayed reconfigurable manufacturing system (D-RMS). D-RMS is a subclass of RMS that focuses primarily on improving the convertibility of the manufacturing system. The two main phases involved in implementing D-RMS are part family formation and configuration design. Therefore, we proposed a multi-objective joint optimisation method of part family formation and configuration design according to the philosophy of D-RMS. Firstly, we develop a multi-objective joint optimisation model that takes into account investment cost, reconfiguration cost, similarity coefficient, and delayed reconfiguration to optimise the part family and configuration of D-RMS simultaneously. Three types of machine tools namely dedicated machine tools, flexible machine tools, and reconfigurable machine tools are considered in the optimisation model. Secondly, the non-dominated sorting genetic algorithm-III (NSGA-III) is adopted to solve the proposed multi-objective integer programming problem. Finally, numerical experiments are presented to demonstrate the effectiveness of the proposed multi-objective joint optimisation method. © 2023 Informa UK Limited, trading as Taylor & Francis Group
  6. Keywords:
  7. Delayed reconfigurable manufacturing system(D-RMS) ; Industry 4.0 ; Multi-objective joint optimisation ; NSGA-III ; Computer aided manufacturing ; Genetic algorithms ; Integer programming ; Machine tools ; Multiobjective optimization ; Numerical methods ; Configuration designs ; Joint optimization ; Multi objective ; Non-dominated sorting genetic algorithm-III ; Optimization method ; Part family formation ; Reconfigurable manufacturing system
  8. Source: International Journal of Production Research ; Volume 62, Issue 1-2 , 2024 , Pages 92-109 ; 00207543 (ISSN)
  9. URL: https://www.tandfonline.com/doi/full/10.1080/00207543.2023.2223725