A Digital Twin Modular Framework for Reconfigurable Manufacturing Systems - Advances in Production Management Systems. Towards Smart and Digital Manufacturing Access content directly
Conference Papers Year : 2020

A Digital Twin Modular Framework for Reconfigurable Manufacturing Systems

Abstract

The emergence of Industry 4.0 and its related technologies transformed modern manufacturing environment by making them more intelligent. This is associated with the fast evolution of data acquisition technologies and the enormous amount of generated data. Among these modern manufacturing environment, Reconfigurable Manufacturing System (RMS) is a concept able to cope with the current market conditions, characterized by an increasingly personalized and volatile demand. At the same time, Digital Twin (DT) emerged as a new concept. DT represents a new data-driven vision that combines real time data analytics, optimization and simulation. When managing modern and complex manufacturing systems, DT provides new insights and potentials in decision-making process support. In this context, this paper is an attempt to present an integrated RMS digital twin (RMS-DT) modular framework. RMS-DT is a model that can represent the system state at any moment in time while allowing a holistic system visibility to improve its performances and enable flexible decision-making. The paper is concluded with a discussion, future challenges and perspectives in order to enhance the proposed RMS digital twin framework.
Fichier principal
Vignette du fichier
504014_1_En_57_Chapter.pdf (683.53 Ko) Télécharger le fichier
Origin : Explicit agreement for this submission
licence : CC BY - Attribution

Dates and versions

hal-02923302 , version 1 (22-06-2023)

Licence

Attribution

Identifiers

Cite

Hichem Haddou Benderbal, Alexandre Dolgui, Abdel Karim Yelles-Chaouche. A Digital Twin Modular Framework for Reconfigurable Manufacturing Systems. APMS 2020: Advances in Production Management Systems. Towards Smart and Digital Manufacturing, Aug 2020, Novi Sad, Serbia. pp.493-500, ⟨10.1007/978-3-030-57997-5_57⟩. ⟨hal-02923302⟩
98 View
35 Download

Altmetric

Share

Gmail Facebook X LinkedIn More