PHM Theory and Methods:
Condition-based and Predictive Maintenance
Explainable and trustworthy Detection, Diagnostics & Prognostics Methods
Artificial Intelligence (including machine learning and deep learning)
Data-driven, Model-based, and Hybrid methodologies for Modeling of Degradation
Verification and Validation
Physics-of-Failure
Fault-Adaptive Control
PHM Design and Integration:
Digital Twin and Digital Thread
IoT for PHM cost-benefit and Return-on-investment analysis
Failure Mode, Effects & Criticality Analysis
Smart Manufacturing (Planning, Automation, Device, Sensor)
Decision Support Systems
Software and Hardware for PHM
Standards for PHM
PHM and Emerging AI Applications:
Large language models for Manufacturing
Foundation models for manufacturing
Emerging AI models (federated learning, self-supervised learning, continual learning, reinforcement learning, few-shot learning, etc.)
Energy Systems (power plants, wind turbines, photovoltaics, etc.)
Mobility and Transport (automobiles, rail, marine, etc.)
Aerospace Systems (aviation, UAVs, rocket engines, artificial satellites, etc.)
Process Industry (steel, chemical, glass, oil & gas, semiconductor, etc.)
Electronic and Electrical Systems (semiconductors, batteries, substrates, solder, elevators, HVAC, automatic ticket gates, etc.)
Structural Health Monitoring (bridges, roads, buildings, tunnels, etc.)
Cyber Physical Systems (smart grids, autonomous vehicles,medical monitoring, etc.)
Commercial Aviation and Maintenance Repair Organizations