GOAL OF THE EVENT

The Prognostics and Health Management Society invites your participation, including submission of original papers and posters, for presentation at the 7^th European Conference of the PHM Society*, July 6^th to July 8^th, which will finally be a face-to-face event in Turin, Italy.

Building on our past success with 282 participants for PHME20, and 142 in 2021, 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: Airbus, Alstom, Amazon,Baker-Hughes, Dutch Rail, ECA, GE, GM, Honeywell, Huawei, Hyundai, IFSTTAR, IK-4 Tekniker, Irish Rail, KEPCO, Linova, Lufthansa, Meggitt, Mercedes, Messier-Bugatti-Dowty, Mitsubishi, NI, Orsted, PARC, PREDICT, Prisma, PwC, Ricardo Rail, RK Diagnostics, Rolls Royce, Saab, Safran, Scania, Schlumberger. SKF, Snecma, STMicroelectonics, Ureason and UTRC, and many universities and public sector organizations, like CNRS, DLR, EDF, GVB, Inria, IVHM Centre, KIMM, KITECH, NASA, NLR.

* The Prognostics and Health Management Society (PHM Society) is a non-profit organization dedicated to the advancement of PHM as an engineering discipline. It serves industry, academia, and government leaders in this international community.

Recommendations about Covid

To prepare your travel and your stay in Italy, please read our special page here.

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