REEDEAM is a project where Luleå University of Technology, Mälardalen University and Örebro University, and industry will co-produce education for the business community’s climate transition. The project aims to strengthen cooperation between universities and industry by improving access to demand-driven competence development. REEDEAM also aims to establish long-term cooperation between the universities based on their scientific areas of expertise. A planned research school will provide the business community with greater access to doctoral competence and further strengthen the universities’ cooperation with the surrounding industry and society. Lessons learned, and experiences from the KK Foundation’s expert competence program are integrated to ensure efficiency and quality by creating a cohesive competence offering.
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This course is designed for engineers, scientists, operators, and managers interested in utilizing AI-based methods for condition monitoring and prognostics in industrial systems and high-value assets. Participants will learn to identify common failure causes and predict Remaining Useful Life (RUL) using historical data, involving tasks such as data processing, feature selection, model development, and uncertainty quantification. Led by experienced professionals from industry and academia, the course covers the basics of prognostics and introduces various AI methods, including deep learning. It represents state-of-the-art AI-driven prognostic techniques, advanced signal processing, and feature engineering methods. Scheduled online meetings November 11th 2024 January 15th 2025