Towards improving the future of manufacturing through digital twin and augmented reality technologies

Souad Rabah (1) , Ahlem Assila (2) , Elio Khouri (3) , Florian Maier (1) , Fakreddine Ababsa (3) , Valéry Bourny (4) , Paul Maier (5) , Frédéric Merienne (3)

1 École Supérieure d'Ingénieurs en Électronique et Électrotechnique
2 LINEACT - Laboratoire d'Innovation Numérique pour les Entreprises et les Apprentissages au service de la Compétitivité des Territoires
3 LISPEN - Laboratoire d’Ingénierie des Systèmes Physiques et Numériques
4 LTI - Laboratoire des technologies innovantes - UR UPJV 3899
5 EREM - Société EREM

We are on the cusp of a technological revolution that will fundamentally change our relationships to others and the way we live and work. These changes, in their importance, scope, and complexity, is different than what humanity has known until now. We do not yet know what will happen, but one thing is certain: our response must be comprehensive and it must involve all stakeholders at the global level: the public sector, the private sector, the academic world and civil society. Applications for the industrial sector are already numerous: predictive maintenance, improved decision-making in real time, anticipation of stocks according to the progress of production, etc. So many improvements that optimize the production tools every day a little more, and point to possibilities for the future of Industry 4.0, the crossroads of an interconnected global world. This work comes to contribute as a part of this industrial evolution(Usine 4.0). In this paper we introduce a part of a collaboration between industry and research area in order to develop a DT and AR industrial solution as a part of a predictive maintenance framework. In this context, we elaborate a proof-of-concept that was developed in special industrial application.

Mots clés: Digital twin; Augmented reality; Predictive maintenance; Industry 4.0; Automation; Evaluation

Domaines: Synthèse d'image et réalité virtuelle [cs.GR]; Interface homme-machine [cs.HC]; Ingénierie assistée par ordinateur

Souad Rabah, Ahlem Assila, Elio Khouri, Florian Maier, Fakreddine Ababsa, et al.. Towards improving the future of manufacturing through digital twin and augmented reality technologies. Procedia Manufacturing, 2018, 17 (Special issue on 28th International Conference on Flexible Automation and Intelligent Manufacturing), pp.460-467. ⟨10.1016/j.promfg.2018.10.070⟩. ⟨hal-02009635⟩