Integrating Human-Centricity, Sustainability, and Resilience in Digital Twin Models for Industry 5.0 : A Multi-Objective Optimization Approach

Madani Bezoui (1, 2) , Ilhem Slama (3) , Ahcene Bounceur (4) , Saeed Mian Qaisar , Mohammad Hammoudeh , Abdulaziz Turki Almaktoom

1 LINEACT - Laboratoire d'Innovation Numérique pour les Entreprises et les Apprentissages au service de la Compétitivité des Territoires
2 CESI - CESI : groupe d’Enseignement Supérieur et de Formation Professionnelle
3 UTT - Université de Technologie de Troyes
4 KFUPM - King Fahd University of Petroleum and Minerals

This paper presents the InduDesc framework, an innovative digital twin model within the CupCarbon software, designed for the advanced needs of Industry 5.0. It integrates human-centred ergonomics, sustainability and resilience into the Flexible Job Shop Scheduling Problem (FJSP), traditionally an NP-hard challenge. By minimising operating times and balancing machine utilisation with ergonomic and sustainability considerations, the framework provides a dynamic workload management tool based on real-time 'fatigue' metrics. Using a tabu search algorithm, InduDesc generates a Pareto frontier to help decision makers identify strategies that efficiently align with the integrated goals of Industry 5.0.

Mots clés: Multi-Objective Optimization Ergonomics Digital Twin Industry 5.0 Flexible Scheduling Jobshop; Multi-Objective Optimization; Ergonomics; Digital Twin; Industry 5.0; Flexible Scheduling Jobshop

Domaines: Recherche opérationnelle [math.OC]

Madani Bezoui, Ilhem Slama, Ahcene Bounceur, Saeed Mian Qaisar, Mohammad Hammoudeh, et al.. Integrating Human-Centricity, Sustainability, and Resilience in Digital Twin Models for Industry 5.0 : A Multi-Objective Optimization Approach. Congrès Annuel de la Société Française de Recherche Opérationnelle et d’Aide à la Décision, Mar 2024, Amiens (Université Picardie Jules Verne), France. ⟨hal-04543143⟩