Digital Twin-Driven Dynamic Scheduling of Flexible Manufacturing System in the Context of Smart Factory Producing Brass Accessories.

  • Published In: Journal of Industrial Integration & Management, 2025, v. 10, n. 1. P. 67 1 of 3

  • Database: Business Source Ultimate 2 of 3

  • Authored By: Chakroun, Ayoub; Hani, Yasmina; Elmhamedi, Abderrahmane; Masmoudi, Faouzi 3 of 3

Abstract

This study aims to deal with a dynamic scheduling problem of a real Flow Shop follow-up of an assembly process considering the specific constraints and requirements of a brass accessories manufacturing (BAM) company. We basically set up a Digital Twin-driven dynamic scheduling approach for Industry 4.0 by addressing uncertainties of machine availability. In fact, the setup of this Digital Twin (DT) is the outcome of the combination of both optimization and simulation. For the first step, we have elaborated a Mixed Integer Linear Programming (MILP) scheduling model by taking into account the dedicated requisites of our case study. Concerning simulation, a 3D simulation platform of a workshop producing brass accessories controlled by a Cyber-Physical Production System (CPPS) has been developed, in our previous work, including constraints and stochastic aspects. The simulation constraints are difficult or impossible to be modeled in the MILP model. These designs are integrated with the real workshop to construct the Digital Twin. The proposed tool enables the rescheduling of production orders based on machine disturbances and unpredictability. Validation scenarios have been designed and conducted to highlight the efficacy of the Digital Twin approach utilizing the brass accessories case study. We are confident that this represents the initial endeavor addressing the optimization of production rescheduling in a flow shop follow-up of a mixed assembly system. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Journal of Industrial Integration & Management. 2025/03, Vol. 10, Issue 1, p67
  • Document Type:Article
  • Subject Area:Business and Management
  • Publication Date:2025
  • ISSN:2424-8622
  • DOI:10.1142/S2424862224500155
  • Accession Number:186630095
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