leArning and robuSt deciSIon SupporT systems for agile mANufacTuring environments

The ASSISTANT project aims to create intelligent digital twins through the joint use of machine learning (ML), optimization, simulation and domain models. ASSISTANT targets a significant increase in flexibility and reactivity, products/processes quality, and in robustness of manufacturing systems, by integrating human and machine intelligence in a sustainable learning relationship.

Artificial Intelligence for improved PROduction efFICIEncy, quality and maintenance

The AI-PROFICIENT project aims to develop proactive control strategies to improve manufacturing processes in terms of production efficiency, quality and maintenance. The overall goal is to increase the positive impact of AI technology on the manufacturing process as a whole, while keeping the human in a central position, assuming supervisory (human-on-the-loop) and executive (human-in-command) roles.

Towards AI powered manufacturing services, processes, and products in an edge-to-cloud-knowlEdge continuum for humans

The knowlEdge project will address the need for new AI solutions that are agile, reusable, distributed, scalable, accountable, secure, standardised and collaborative. The proposed new framework will ensure the secure management of distributed data and facilitate knowledge exchange. 

Multi-Agent Systems for Pervasive Artificial Intelligence for assisting Humans in Modular Production Environments

The MAS4AI project will develop a system that allows the deployment and synchronisation of different AI agents in manufacturing for autonomous modular production and human assistance. By incorporating AI technologies, the project will optimise manufacturing costs and adapt routes, tools and parameters.

Safe and Trusted Human Centric Artificial Intelligence in Future Manufacturing Lines

The STAR project aims to research and integrate leading-edge AI technologies like active learning systems, simulated reality systems, explainable AI, human-centric digital twins, advanced reinforcement learning techniques and cyber-defence mechanisms, to allow the safe deployment of sophisticated AI systems in production lines. 

Human-AI Teaming Platform for Maintaining and Evolving AI Systems in Manufacturing

The TEAMING_AI project aims to develop a human AI teaming framework that integrates the strengths of both, the flexibility of human intelligence and scale-up capability of machine intelligence. 

Explainable Manufacturing Artificial Intelligence

The XMANAI project will focus on explainable AI, a concept that contradicts the idea of the ‘black box’ in machine learning, where even the designers cannot explain why the AI reaches at a specific decision. XMANAI will carve out a ‘human-centric’, trustful approach that will be tested in real-life manufacturing cases. The aim is to transform the manufacturing value chain with ‘glass box’ models that are explainable to a ‘human in the loop’ and produce value-based explanations.

Advancing Collaboration and Exchange of Knowledge Between the EU and Japan for AI-Driven Innovation in Manufacturing

The EU-Japan.AI project will develop a platform-based approach to connect relevant stakeholders from the EU and Japan and support knowledge exchange on innovative AI applications for manufacturing. In addition to other tools, this platform will include an open-information hub.