GOAL OF THE EVENT

The Prognostics and Health Management Society invites your participation, including submission of original papers and posters, for presentation at the 9^th European Conference of the PHM Society, July 8^th to July 10^th, which will be a face-to-face event in Oslo, Norway.

Building on our past success for PHME24 in Prague, attend and learn from keynotes and special sessions integrated with panels and tutorials. Follow those developments and data challenge, doctoral symposium and other high value content on this web site.

The conference will highlight the broad aspects of Prognostics and Health Management across all disciplines, technologies, and levels. Past participants came from: ABB Schweiz AG, Airbus, Alstom, Amazon, Austrian Institute of Technology, Baker-Hughes, Ben Gurion University of the Negev, Chalmers University of Technology, Collins Aerospace, Concordia University, Cranfield University, Delft University of Technology, DLR, Dutch Rail, ECA, Flanders Make, GE, GM, Halmstad University, Honeywell, Huawei, Hyundai, IFSTTAR, IK-4 Tekniker, INP-ENIT, Irish Rail, KEPCO, KLM, Korea Aerospace University, KTH Royal Institute of Technology, KU Leuven, Linova, Lufthansa, Meggitt, Mercedes, Messier-Bugatti-Dowty, Mitsubishi, NI, Orsted, PARC, Politecnico di Torino, PREDICT, Prisma, PwC, Ricardo Rail, RK Diagnostics, Rolls Royce, Saab, Safran, Scania, Schlumberger, SKF, Snecma, Stratio, STMicroelectonics, Ureason and UTRC, Volkswagen AG, and many universities and public sector organizations, like CNRS, DLR, EDF, GVB, Inria, IVHM Centre, KIMM, KITECH, NASA, NLR.

TOPICS OF INTEREST

Submissions are invited for papers for presentation and inclusion in the proceedings. Be part of an active network including students, managers, practitioners, and scientists from academia, government, and industry, from across the globe addressing the following topics:

PHM Design:

• Systems engineering aspects of PHM
• PHM related standards and methodologies
• PHM Design and PHM Architectures
• Uncertainty, Explainablility and Causal Inference
• Deep Learning/Machine Learning methods for PHM
• PHM at the Component/Sub-system/System level

PHM Development:

• Physics of failure for anomaly detection, diagnostics and prognostics
• Fault-adaptive control methods
• Prognostics sensors and detection
• Fault detection and prognostics of MEMS
• Model-based diagnostics
• Data-driven, model-based and hybrid prognostics
• Condition-based and predictive maintenance technologies
• Software and hardware for PHM
• Degradation modelling

PHM Applications:

• Asset health management
• Structural health management
• PHM for electronics and electrical engineering systems and plants
• PHM in Cyber-Physical Systems
• Cost Benefit and Return-on-Investment analysis
• PHM for Automotive, Rail, Marine, Wind and Energy
• PHM for Manufacturing (Production planning and Control)
• Deployed applications and success stories