AI for data-driven and self-configurable supply chains

Description

Today's markets are characterized by great product diversity and product customization. Demand is volatile and uncertain. In addition, product life cycles are shortened and production and delivery times acceptable to customers are increasingly short. Therefore, today's businesses need to deploy flexible production systems, robust supply chains, and agile planning processes. In this context, current analytical tools are starting to reach their limit. Nevertheless, technologies evolve and offer interesting prospects. We refer, in particular, to Industry 4.0 technologies and advances in artificial intelligence and data science.

In the perimeter of this Chair, we are developing innovative decision-support tools for the planning and management of production systems and the supply chains, by coupling optimization and simulation with artificial intelligence techniques. This approach should allow a higher efficiency and have (self) -adaptive solutions, in particular in the case of a dynamic or uncertain environment and when the problems are not well defined.

Chair events

12/02/2020 Industrial Workshop, Grenoble
15/04/2020 Visio seminar with industrial partners
02/06/2020 Visio seminar with industrial partners
08/07/2020 Visio seminar with industrial partners

Scientific publications

P. Seeger, Z. Yahouni, G. Alpan. Towards using data mining for efficient planning and scheduling of production workshops in the context of industry 4.0: a literature review. International Journal of Production Research, (submitted)

D. Koala, Z. Yahouni, G. Alpan, Y. Frein. Factors influencing drug consumption and prediction methods. CIGI QUALITA 2021 (submitted)