Senior Lecturer Reliability and Maintenance Engineering at ZHAW School of Engineering
Deep Learning and Artificial Intelligence in Maintenance
Deep learning and artificial intelligence are currently on everyone’s lips. Several impressive achievements and breakthroughs could be recently observed: For example, the artificial intelligence Software AphaZero, created by DeepMind, has achieved a superhuman level in chess, Go and shogi, just by playing against itself in just 24 hours. Computer vision, natural language processing and speech recognition have also recently made significant advances gradually becoming an integral part of people’s everyday lives. But what is the potential of these emerging technologies for railway maintenance? Is it just a hype without real benefits to the railway industry? What has already been applied and what is under development and is a future vision? Where could the development go and how could potential transformation look like? How could deep learning and artificial intelligence be integrated in decision making of asset managers supporting them to make optimal decisions?
Olga Fink is SNSF (Swiss National Science Foundation) professor for intelligent maintenance systems at ETH Zürich (starting from October 2018). Before joining ETH faculty, she was heading the research group “Smart Maintenance” at the Zurich University of Applied Sciences (ZHAW). Olga received her Ph.D. degree in civil engineering from ETH Zurich, and Diploma degree in industrial engineering from Hamburg University of Technology. She has gained valuable industrial experience as reliability engineer for railway rolling stock and as reliability and maintenance expert for railway systems. Olga’s research focuses on data-driven condition-based and predictive maintenance of complex industrial systems; recently with a particular focus to deep learning applications in predictive maintenance