Special Session 3: AI-Augmented Predictive Maintenance for Complex Industrial Systems
Please submit your manuscript via https://www.easychair.org/conferences/?conf=icsrs2026 and select Special Session 3
Chairs
Brief Introduction
This session focuses on advanced artificial intelligence techniques specifically tailored for predictive maintenance in complex, mission-critical systems. Topics include deep learning-based remaining useful life prediction, federated learning for distributed maintenance, generative AI for anomaly detection, physics-informed neural networks for degradation forecasting, and autonomous maintenance planning.
Sub-topics
• Foundation Models for Cross-Domain Fault Diagnosis
• Few-Shot Learning in Data-Scarce Industrial Settings
• Explainable AI for Maintenance Decision Justification
• Federated Learning Across Multi-Plant Maintenance Networks
• Attention Mechanisms in Multivariate Sensor Anomaly Detection
• Reinforcement Learning for Dynamic Maintenance Policies
• Causal Inference in Root Cause Analysis of Failures
• Graph Neural Networks for System-Level Fault Propagation
• Transformer Architectures for Time-Series Degradation Modeling
• Trustworthy AI Metrics for Safety-Critical PdM Deployment