Human-Centered Explainable Anomaly Detection for Smart Manufacturing in Industry 5.0

Dr. habil. Kim Phuc Tran is a Senior Associate Professor (Maître de Conférences HDR) at ENSAIT – University of Lille, France, and Senior Researcher at the GEMTEX Laboratory. He also serves as Founding Director of the International Chair in Data Science & Explainable AI at Dong A University (Vietnam).His research focuses on Industrial AI, Explainable and Federated Learning, Edge Intelligence, and Hybrid Modeling (Physics & Data), with applications spanning Smart Manufacturing, Healthcare, and Energy Systems.He has authored over 75 international publications, edited several Springer volumes, and serves on editorial boards including IEEE Transactions on Intelligent Transportation Engineering Applications of Artificial Intelligence.

• Introduction to Human-Centered Explainable Anomaly Detection for Smart Manufacturing in Industry 5.0.- Anomaly Detection for Catalyzing Operational Excellence in Complex Manufacturing Processes: A.- Survey and Perspective.- System Reliability: Inference for Common Cause Failure Model in Contexts of Missing Information.- .- Predictive maintenance enabled by a Light-Weight Federated Learning in Smart Manufacturing: Remaining Useful Lifetime Prediction.- Explainable Trustworthy, and Transparent Artificial Intelligence for Reliability Engineering and Safety Applications.- Human-Centered Explainable Anomaly Detection for Predictive Maintenance.- .- Reliability and Risk Assessment with Human-Centered Explainable Anomaly Detection.- An Human-Centered Explainable Anomaly Detection Framework for Safety and Reliability Engineering.- Wearable Technology for Workplace Safety with Human-Centered Explainable Anomaly Detection.- Safety and Reliability of Human-Centered Explainable Anomaly Detection systems.- Physics-informed machine learning for Human-Centered Explainable Anomaly Detection systems.