Axis 7: Industry 4.0

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 Manufacturing 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 this axis 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. Two main programmes support this axis: human-centric manufacturing and predictive quality.

Human-centric manufacturing

The challenge is to make AI the support for maintaining humans within industry of the future. New jobs, responsibilities and tools will make industry more attractive and effective. The objective of the programme is to develop reasoning and learning techniques to enhance human-machine collaboration through collaborative robotics and augmented reality, and to develop novel decision-making methods for highly reactive operations and supply chain management.

  • AI for data-driven and self-configurable supply chains - Gülgün Alpan

7.2. Predictive quality

The challenge is zero defect manufacturing for a more societal and environmental industry. Quality is the main competitive advantage of European companies. The objective is to develop machine learning, classification and image analysis techniques to predict quality of new materials, products, production processes, maintenance activities and industrial systems.

  • Machine Learning for Materials Design & Efficient Systems - Massih-Reza Amini (AI) & Alexis Deschamps (Material science)