Actualité - Annonce de Thèse/HDR

Date : Sept. 26, 2023, 10 a.m. - Type : Thesis - Mahdi EL ALAOUI EL ABDELLAOUI - Amphi A22 - Espace Fauriel

Methodology of Enterprise Modeling oriented Industry 4.0 : Application for Decision Support Systems in Manufacturing Systems
The new industrial revolution, “Industry 4.0” complicates the decision making in manufacturing systems due to many challenges, such as short product life cycle, data integration, and consideration of sustainability. Companies need help to overcome these challenges and deploy a smart factory.
This Ph.D. falls within this context and proposes a new methodology for implementing Industry 4.0-oriented decision support systems.  First, we identify and classify the decision problems of a manufacturing system and examine their interactions.  Then, we study their main evolutions in Industry 4.0 and propose cartography to represent them.
On this basis, using enterprise modeling, we aim to develop agile and rapidly reconfigurable decision support systems adapted to Industry 4.0. Furthermore, we identify gaps in existing enterprise modeling frameworks and propose a new Industry 4.0-oriented enterprise modeling methodology called «MEMO I4.0».
MEMO I4.0 offers a structured two-step approach. The strategic/tactical step is to create the basic modules and enrich the library of modules. The operational step is to build the integrated model and evaluate performance. Finally, the application of MEMO I4.0 on industrial case studies of the company «elm.leblanc» to derive decision support systems has shown its ability to considerably reduce the development time of modeling projects and its compatibility with Industry 4.0.
Keywords: Industry 4.0, Smart manufacturing, Enterprise architecture, Enterprise modeling, Manufacturing systems, Digital twin, Simulation, Optimization, Decision support systems, New key performance indicators.
The thesis defense committee is composed of:
DA CUNHA Catherine          Professor                  Ecole Centrale de Nantes                                Reviewer
SGARBOSSA Fabio             Professor                 Norwegian University of Science and Technology    Reviewer
VALLESPIR Bruno               Professor       Université de Bordeaux         Reviewer
DELORME Xavier                Professor                 Ecole des mines de Saint-Etienne                             Director of thesis
GRIMAUD Frédéric              Professor                 Ecole des mines de Saint-Etienne                  Co-director of thesis
GIANESSI Paolo                  Doctor                  Ecole des mines de Saint-Etienne                Co-supervisor
STEPHENS Erwan               Engineer       elm.leblanc, Bosch Group                                         Guest.