Online Workshop on November 24 and 25, 2021: AI, digitalization and materials modeling for better lifetime predictions
In materials and component research, artificial intelligence methodologies will lead to massive upheavals in the coming years. The processes of material development, material processing, lifetime prediction and material characterization will change significantly. By combining AI methods and new forms of knowledge representation, the data-based management of product life cycles will take on new qualities. To address this emerging field of research Fraunhofer IWM set up the online workshop »AI Methods for Fatigue Behavior Assessment and Component Life Prediction« on November 24 and 25, 2021.
Manufacturers and operators of facilities and plants are faced with the challenge of ensuring and reconciling performance and economic efficiency as well as the reliability and safety of their systems. This requires suitable monitoring and maintenance concepts plus valid decision-making fundamentals for adapting operating points to changing operating conditions. Prerequisites for this are material models for service life assessment, methods for the qualification of critical components and a sound database.
The combination of AI methods and knowledge graphs introduces new possibilities for the data-based management of product life cycles. With a view to assessing the fatigue behavior of materials and predicting the service life of components, this results in a new quality of predictions and new starting points for reducing failure costs and increasing plant and systems availability.
In the workshop, renowned experts from science and industry will present corresponding concepts as well as how methods of artificial intelligence and digitalization of materials can be integrated into product development and systems and facilities operation.
Reasons for participation
• International experts from industry and leading research institutions will provide a
new perspective on the topic of AI-supported material and component evaluation.
• Discover how lifetime expectancy predictions, material/component development and
product lifecycle management are taking on a new quality through the combination
of artificial intelligence, data structures and materials modeling.
• Learn how material and component simulation will manifest itself in the future as well
as how this will lead to improved decision-making in product development and plant
and systems operations.
• Find out about the current state of investigation in an innovative research field and
connect with international experts from different disciplines.
• Talks from Schaeffler Technologies, Karlsruhe Institute of Technology KIT, Georgia
Institute of Technology, German Research Center for AI, DFKI, Citrine Informatics,
Federal Institute for Materials Research and Testing BAM, MINES Paris Tech (École
des Mines de Paris), Fraunhofer IWM
The event language is English. Participation is free of charge. Registration is required, please register by November 12. Link to website: https://www.iwm.fraunhofer.de/de/ueber-uns/veranstaltungen/online-workshop-ai-methods.html
Wissenschaftlicher Ansprechpartner:
Thomas Götz
Phone +49 761 5142- 153
thomas.goetz@iwm.fraunhofer.de
Wiebke Beckmann
Phone +49 761 5142- 293
wiebke.beckmann@iwm.fraunhofer.de
Weitere Informationen:
https://www.iwm.fraunhofer.de/de/ueber-uns/veranstaltungen/online-workshop-ai-methods.html Program and Registration
https://www.iwm.fraunhofer.de/en/press/press-releases/04_11_21_ai_workshop_lifetime_predictions.html Press Release
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