Covers early anomaly detection, fault diagnosis, and remaining useful life prediction for enhanced system reliability
Discusses optimization control and self-healing techniques to improve maintenance efficiency
Explores applications in production, renewable energy, maritime, power, and smart devices systems
Focuses on dynamic systems with real-time model updates to maintain predictive accuracy
Includes case studies and decision support tools for handling big data and IoT infrastructures
Summarized by Shop
This book provides a complete picture of several decision support tools for predictive maintenance. These include embedding early anomaly/fault detection, diagnosis and reasoning, remaining useful life prediction (fault prognostics), quality prediction and self-reaction, as well as optimization, control and self-healing techniques. It sho