Manufacturing Digital Transformation

Données Générales
Programme Académique	Incoming Exchange Student Courses			Responsable(s) Module : MARCONNET Bertrand
Type d'EC : Cours	Manufacturing Digital Transformation (LIIExp07EManuDigiTrans)
TD : 24h00 Cours : 6h00 Projet : 8h00 Travail personnel : 22h00 Durée totale: 60h00	Statut Obligatoire	Periode Semester 7 - Industrial Engineering And Supply Chain Management	Langue d'enseignement : English

Acquis d'apprentissage
• Assimilate and implement machines and tools adapted to production • Both capitalize data and information related to the project • Find ways of improvement by analyzing the product/process couple in a PLM strategy • Implementation and simulation of Factory 4.0 flows • State the benefits of PLM (Product Lifecycle Management) • Analyze and deploy XR in a plant (Virtual Reality/Augmented Reality) • Acquire fundamental concepts and techniques for creating virtual reality experiences • Learn about alternatives with low-tech solutions • To be aware of scientific research • Understand and apply AI and Big Data methods for industrial systems, including data processing, predictive maintenance, and smart manufacturing analysis • Design and evaluate a low-tech Karakuri solution using eco-design, LCA, and QCDHSE criteria, while working in a team on a prototype and scientific deliverables.

Acquis d'apprentissage

• Assimilate and implement machines and tools adapted to production
• Both capitalize data and information related to the project
• Find ways of improvement by analyzing the product/process couple in a PLM strategy
• Implementation and simulation of Factory 4.0 flows
• State the benefits of PLM (Product Lifecycle Management)
• Analyze and deploy XR in a plant (Virtual Reality/Augmented Reality)
• Acquire fundamental concepts and techniques for creating virtual reality experiences
• Learn about alternatives with low-tech solutions
• To be aware of scientific research
• Understand and apply AI and Big Data methods for industrial systems, including data processing, predictive maintenance, and smart manufacturing analysis
• Design and evaluate a low-tech Karakuri solution using eco-design, LCA, and QCDHSE criteria, while working in a team on a prototype and scientific deliverables.

Contenu
• XR: - Discover SimLab software solutions for developing VR/AR applications - Developing the first VR experience - Understanding how SimLab software works with VR/AR equipment • Product Lifecycle Management - PLM : - PLM Introduction - Windchill PLM software - Project view • Plant Layout 2 : - Redo the implementation from last year, with the simulation flows of robotic equipment • KARAKURI Challenge (eco-design and low tech): - Working as a team to design a low-tech conveyor and reduce environmental impact - Knowing how to write a scientific article - Research awareness • AI in Industry and Big Data: - ML basics, data/AI pipeline, industrial applications, sustainability, and predictive maintenance practice with Altair AI Studio / RapidMiner

Contenu

• XR:
- Discover SimLab software solutions for developing VR/AR applications
- Developing the first VR experience
- Understanding how SimLab software works with VR/AR equipment
• Product Lifecycle Management - PLM :
- PLM Introduction
- Windchill PLM software
- Project view
• Plant Layout 2 :
- Redo the implementation from last year, with the simulation flows of robotic equipment
• KARAKURI Challenge (eco-design and low tech):
- Working as a team to design a low-tech conveyor and reduce environmental impact
- Knowing how to write a scientific article
- Research awareness
• AI in Industry and Big Data:
- ML basics, data/AI pipeline, industrial applications, sustainability, and predictive maintenance practice with Altair AI Studio / RapidMiner

Bibliographie
Introduction to Materials management – Global Edition. Steve Chapman. Pearson; 8e édition (23 juin 2016)