Jan. 01, 2020 to Dec. 31, 2023
KYKLOS 4.0 aims to develop an innovative Circular Manufacturing ecosystem based on novel CPS (Circular Production System) and AI (Artificial Intelligence) technologies, enhanced with novel production mechanisms and algorithms, targeting personalized products with extended life cycle and promoting energy efficient and low material consumption intra-factory production processes, resulting in reduced greenhouse gas emissions and air pollutants.
KYKLOS 4.0 will demonstrate, in a realistic, measurable, and replicable way the transformative effects that CPS, PLM (Product Life Management), LCA (Life Cycle Analysis), AR (Augmented Reality) and AI technologies and methodologies will have on the Circular Manufacturing Framework. To this end, KYKLOS 4.0 will:
- perform large-scale piloting in 7 pilots to demonstrate the technical, environmental and economic viability of KYKLOS 4.0 Ecosystem to reshape intra-factory processes and services;
- show KYKLOS 4.0 value in terms of operational efficiency improvements by at least 15 percent;
- deliver resources reusable solutions (second use of material, part and components reuse) for the whole manufacturing sectors;
- ensure scalability for future scale of novel CM (Circular Manufacturing) technologies and services at least at the level of year 2024;
- strengthen the position of EU CM technologies providers and sector fostering a market share of up to 12 percent
In this project, Fraunhofer FOKUS is in charge of developing a cognitive toolkit that,
- provides added value services to the manufacturing processes such as supporting the design, customisation, and optimisation of the products being developed
- uses AI to learn for instance from the data gathered from the machines in a shop floor, and the data related to certain products, and offers recommendations regarding customization and optimisation for a variety of applications such as predictive maintenance and additive manufacturing
The KYKLOS 4.0 project comprises 29 partners from 14 countries. The project is funded as part of the EU research and innovation program Horizon 2020 under grant agreement number 872570.