Artificial Intelligence in Manufacturing leading to Sustainability and Industry5.0

AIMS5.0 aims at European digital sovereignty in comprehensively sustainable production, by adopting, extending, and implementing AI tools & methods and chip technology across the whole industrial value chain to further increase the overall efficiency.
In essence, the project will deliver:
- AI-enabled electronic components & systems for sustainable production
- AI tools, methods & algorithms for sustainable industrial processes
- SoS-based architectures & micro-services for AI-supported sustainable production
- Semantic modelling & data integration for an open access productive sustainability platform
- Acceptance, trust & ethics for industrial AI leading to human-centered sustainable manufacturing.
20 use cases in 10 industrial domains resulting in high TRLs will validate the project’s findings in an interdisciplinary manner. A professional dissemination, communication, exploitation, and standardization will ensure the highest impact possible.
AIMS5.0 will result in lower manufacturing costs, increased product quality through AI-enabled innovation, decreased time-to-market and increased user acceptance of versatile technology offerings.
They will foster a sustainable development, in an economical, ecological, and societal sense and act as enablers for the Green Deal and push the industry towards Industry5.0.
The innovations will leverage the experience of the 52 partners, such as renowned OEMs, Tier-1 and Tier-2 suppliers, technology and application large enterprises and SMEs, supported by academic research specialists in fields like AI, industrial hardware and software, decision making and management algorithms.
AIMS5.0 is a pan-European initiative to boost industrial competitiveness through interdisciplinary innovations, establishing sustainable ECS value chains and therefore contribute to European Digital Sovereignty addressing urgent issues like Security of Supply, Monitoring and Crisis Response, and Chip Shortage.
The Austrian AIMS5.0 consortium consists of 9 partners. Well-recognized large companies (IFAT, TIAG and KAI) and research organizations (AIT, RSA, WUW and ViF), as well as two SMEs (CISC and PYT) are contributing in the AIMS5.0 project. The project research and development performed in Austria will be demonstrated in seven (7) from twenty (20) project use cases. The research and development in these use cases will be completed up to TRL7.
The use cases will focus on the integration and evaluation of AI methods as follows: (i) NLP-driven adaptive security, automated policy creation and classification and clustering of production features, (ii) image classification and wireless signal classification for communication security (using e.g. ANN, SVM, Bayesian models), ML-driven sensor-based monitoring of devices and time-series data stamping in a production plant, (iii) automated decision-making and adapted behavior such as for scheduling, lot starts, line balancing, etc., (iv) XAI to explain predictions and importance of individual features for decision outcomes, (v) generic programming for parameter selection, (iv) CNN, ANN, RCN, RCNN methods for a meaningful data compression and real-time decisions.
By this, the Austrian consortium aims to enhance edge computing infrastructures for more secure and safe communication for indoor food production systems, to improve predictive analytics for reduction of process disruptions, novel smart, sustainable and robust semiconductor systems (e.g., decision making in wafer production automation targeting improved production cycle, elimination of defects, resource planning and quality control). All Austrian partners will also contribute to important human and ethical aspects of digitalization creating recommendations as well as change management guidelines for digital workspaces of the future considering acceptance trust in AI, ethics, legal and sustainability issues, and skills.
The AIMS5.0 project provides a unique balance between new generation of technological solutions and highly skilled working environments for (autonomous) production. Thus, laying the ground for reaching the next intelligent level of AI-supported operation.