Digital twin-driven dynamic scheduling of a hybrid flow shop

Khalil Tliba (), Thierno M. L. Diallo, Olivia Penas, Romdhane Ben Khalifa, Noureddine Ben Yahia and Jean-Yves Choley
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Khalil Tliba: ISAE-SUPMECA
Thierno M. L. Diallo: ISAE-SUPMECA
Olivia Penas: ISAE-SUPMECA
Romdhane Ben Khalifa: Université de Tunis - ENSIT
Noureddine Ben Yahia: Université de Tunis - ENSIT
Jean-Yves Choley: ISAE-SUPMECA

Journal of Intelligent Manufacturing, 2023, vol. 34, issue 5, No 12, 2306 pages

Abstract: Abstract Industries require, nowadays, to be more adaptable to unforeseen real-time events as well as to the rapid evolution of their market (e.g. multiplication of customers, increasingly personalized and unpredictable demand, etc.). To meet these challenges, manufacturers need new solutions to update their production plan when a change in the production system or its environment occurs. In this context, our research work deals with a dynamic scheduling problem of a real Hybrid Flow Shop considering the specific constraints of a perfume manufacturing company. This paper proposes a Digital Twin-driven dynamic scheduling approach based on the combination of both optimization and simulation. For the optimization, we have developed a mixed integer linear programming (MILP) scheduling model taking into account the main specific scheduling requirements of our case study. Regarding the simulation approach, a 3D shop floor model has been developed including the additional stochastic aspects and constraints which are difficult or impossible to model with a MILP approach. These two models are connected with the real shop floor to create a digital twin (DT). The developed DT allows the re-scheduling of production according to internal and external events. Finally, validation scenarios on a perfume case study have been designed and implemented in order to demonstrate the feasibility and the relevance of the proposed digital twin-driven dynamic scheduling approach.

Keywords: Dynamic scheduling; Predictive-reactive; Hybrid flow-shop; Digital twin; Flexibility; MILP (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10845-022-01922-3

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