Abstract The paper presents an Artificial Intelligence-driven approach to predictive maintenance for Product-Service System (PSS) development. This study focuses on time-based and condition-based maintenance, utilizing variational autoencoders to identify both predicted and unpredicted maintenance issues in autonomous haulers. By analyzing data patterns and forecasting future values, this approach enables proactive maintenance and informed decision-making in […]
Read MoreHandshake with VIA University College
- 16th October 2024
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From September 30 to October 2, the BTH team—Marco Bertoni, Carl Toller Melén, Giulia Wally Scurati, and our visiting fellow from Politecnico of Milano Riccardo Giussani—visited Denmark for a collaborative event with VIA University College, AugmentCity, and Region Central Denmark. The focus was on the expanding field of Extended Reality (XR) and its applications in […]
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