Testing and Experimentation Facility for Manufacturing

Topic description

ExpectedOutcome:

Outcomes and deliverables

The Testing and experimentation Facility for manufacturing will be set up and deployed. The project will focus on factory-level optimisation, collaborative robots, and circular economy. It will give innovators the possibility to test and validate their new AI solutions in real-life manufacturing environments before deploying their solutions to the market.

As a result, new AI and data ecosystems, that are compatible with open frameworks that support data sharing, can be used for the improvement of quality and sustainability of the production.

Pressing technological challenges and effects of an aging workforce can be addressed through the deployment of AI and robotics technologies across the manufacturing domain.

This will contribute to the innovation capacity and competitiveness of the European manufacturing sector.

Furthermore, the training, testing and validation of AI applications that respect European values can become a focal point for certification.

Contribution to AI innovation:

• Boosting the competitiveness of the European industry, including SMEs in AI, a technology of high strategic relevance;
• Contributing to boost European IP and products based on European technology;
• Creation of world-class experimentation facilities in Europe, offering a comprehensive support combining the necessary expertise, meeting the needs of European innovators. The organisations running the TEFs and their process will ensure the highest level of trust and security for the users of the TEFs, and the highest quality of the testing and validation to guarantee trust and security in the tested solutions, key for their broad diffusion
• Contributing to European technology sovereignty and open strategic autonomy in AI, and AI-enabled solutions.

The world-class large-scale reference site for testing and experimentation of AI-powered solutions will enable integrating state-of-the-art AI and robotics technologies in the manufacturing domain, and will foster the deployment of trustworthy, transferable and scalable Industrial AI in Europe. A transition towards a more AI-driven manufacturing industry will improve the quality and sustainability of production.

The manufacturing TEF will provide physical and virtual access to real-life manufacturing resources that can be used for testing and experimenting with AI solutions. Examples of such manufacturing resources are model factories that combine different technologies such as additive manufacturing, machine tools, intelligent conveyor systems, automated warehousing, trusted and secured access to data, IoT infrastructure and more, covering multiple industrial processes.

The manufacturing TEF will address the manufacturing sector’s needs for Industrial AI, taking into account domain-specific requirements in terms of time criticality, safety, security and effective interaction and collaboration between robots, AI solutions, and humans who are in control, as well as resource efficiency and environmental performance. The TEF site will offer support and best practices in AI solution implementation, testing and training of algorithms including: full integration, industrial validation and demonstration up to pilot manufacturing in dedicated assembly lines and production cells. The TEF needs to support testing and experimentation of main AI-related services, which cover areas of machine learning, robotics, planning and scheduling, optimisation, self-configuration, computer vision, formal methods, natural language processing, automated reasoning, game theory, multi-agent systems, complex systems, system verification, bioinformatics and others.

The TEF site will define and establish European test and training data sets in cooperation with manufacturing data spaces. The project is encouraged to collaborate with other relevant Digital Europe Programme projects, in particular the edge AI and other sectorial Testing and Experimentation Facilities, to ensure appropriate synergies.

The scope and resources of the manufacturing TEF will be driven by use cases of significant economic value and will provide adequate coverage of activities allowing the deployment of the latest AI-based technologies in real manufacturing environments. The TEF has to be relevant to all kinds of AI innovators, allowing them to test and demonstrate their new AI solutions and support business development, standardization, certification and benchmarking. Aspects such as ethics, cybersecurity and data protection are taken into account, where appropriate. The manufacturing TEF may include regulatory sandboxes, i.e. areas where regulation is limited or favourable to testing new products and services.

When required by the use cases, the manufacturing TEF also needs to cater for edge computing. In manufacturing context, this means that AI tools are brought to sensors and devices, i.e. there where data is produced. These AI tools need to deal with manufacturing requirements related to latency, throughput, stream processing, etc. High-performance computing should be also offered where needed.

The manufacturing TEF will address the following key areas in an agile setup:

• Factory-level optimization (flexible production in high-throughput and high variety environments, rapid prototyping); testing and assessment of AI technology for autonomous decision making within the real world, i.e. interaction with and decision for humans and other machines; supporting e.g. to rearrange the manufacturing process dynamically (incl. choice of manufacturing techniques and logistics);
• Collaborative robotics (mobile, intelligent AI-powered robots enabling safe human-robot collaboration, also in teams; also in sectors like textiles, tourism or construction);
• Circular economy: minimise resource consumption, optimize supply chains in uncertain environments, use of substitute material, collection, sorting and treatment of products that have become waste (making available secondary raw materials and maximum extraction of value), reverse logistics, remanufacturing.

Digital Agenda