AI Driven industrial Equipment product life cycle boosting Agility, Sustainability and resilience (AIDEAS)

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Budget
6 610 338,75 €
Partners
17
The AIDEAS project is developing a series of AI technologies to support this endeavour focusing on four core elements: design, manufacturing, use and repair/reuse/recycling. The proposed solutions will be tested and validated in four pilots involving manufacturers that provide industrial equipment to the metal, stone, plastics and food sectors. AIDEAS will develop AI technologies for supporting the entire lifecycle (design, manufacturing, use, and repair/reuse/recycle) of industrial equipment as a strategic instrument to improve sustainability, agility and resilience of the European machinery manufacturing companies.

 

Machinery industry in Europe is a basis for employment, growth and wealth, with around 3.2 million people employed. Industrial equipment is considered a key enabler for industrial development and the EU has a historically strategic position in this sector. However, it lives from a technological edge in a very competitive landscape. Hereby, it is crucial to provide all stakeholders of the EU with AI technologies that guarantee a resilient design, deployment and reuse of industrial equipment for an increased global competitiveness and a reinforcement of its industrial strategic autonomy and resiliency.

AIDEAS will develop AI technologies for supporting the entire lifecycle (design, manufacturing, use, and repair/reuse/recycle) of industrial equipment as a strategic instrument to improve sustainability, agility and resilience of the European machinery manufacturing companies. AIDEAS will deploy 4 integrated Suites: 1) Design: AI technologies, integrated with CAD/CAM/CAE systems, for optimising the design of industrial equipment structural components, mechanisms and control components; 2) Manufacturing: AI technologies for industrial equipment purchased components selection and procurement, manufactured parts processes optimisation, operations sequencing, quality control and customisation; 3) Use: AI technologies with added value for the industrial equipment user, providing enhanced support for installation and initial calibration, production, quality assurance and predictive maintenance for working on optimal conditions; 4) Repair-Reuse-Recycle: AI technologies for extending the useful life of machines through prescriptive maintenance (repair), facilitating a second life for machines through a smart retrofitting (reuse) and identification of the most sustainable end-of-life (recycle).

The AIDEAS Solutions will be demonstrated in 4 Pilots of machinery manufacturers that provide industrial equipment to different industrial sectors: metal, stone, plastic and food.

 

 

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