Multidisciplinary Institute in Artificial intelligence

Even if industry is sensor/data intensive and decision-making is at the heart of major industrial processes, the application of artificial intelligence is still nascent in manufacturing. Yet, the potentials of AI in industry are widely recognized (up to 20% cost reduction). Grenoble has a long history of research and education on industrial engineering, materials and processes and participates to the EIT Manufacturing6 on these topics. The originality of the Grenoble approach lies in the consideration that human beings are still the major industrial actors, a paradigm sometimes referred to as Industry 4.H. The aim of the chairs of this topic is to integrate AI tools in manufacturing processes to enhance product and process quality, meet the high personalization of the customers’ demand and support the promising industrial strategies, such as servitization and circular economy. A collaboration agreement with Fraunhofer (IPA and IML) has been signed to this end.

• Gülgün Alpan - AI for data-driven and self-configurable supply chains
• Massih-Reza Amini & Alexis Deschamps - Machine learning for mAterial desiGN and Efficient sysTems (MAGNET)