AI-Powered Predictive Maintenance: Machine Learning, Industrial IoT, Fault Detection, and Data-Driven Asset Management

fatima ahmad
Rafbók
64
Síður
Gjaldgeng

Um þessa rafbók

AI-Powered Predictive MaintenanceUnlock the future of intelligent asset management with AI-driven predictive maintenance.Traditional maintenance strategies often result in unexpected equipment failures, costly downtime, and inefficient operations. This book provides a practical roadmap for leveraging Artificial Intelligence, Machine Learning, Industrial IoT, and advanced analytics to predict failures before they occur and optimize the performance of critical assets.Inside, you'll learn how predictive maintenance systems are designed, developed, and deployed across modern industrial environments. Explore machine learning models for fault detection, sensor data analysis, anomaly detection, remaining useful life estimation, and real-time monitoring. Discover how Industrial IoT devices generate valuable operational data and how AI transforms that data into actionable maintenance insights.This comprehensive guide covers predictive analytics fundamentals, data collection strategies, feature engineering, model training, deployment architectures, edge computing, cloud integration, digital twins, and maintenance optimization techniques. Real-world examples and practical workflows demonstrate how organizations reduce downtime, improve reliability, increase operational efficiency, and lower maintenance costs.Whether you're an engineer, data scientist, maintenance professional, operations manager, researcher, or technology enthusiast, this book provides the knowledge and tools needed to build intelligent maintenance solutions for Industry 4.0 environments.Inside the book:Foundations of predictive maintenance and Industry 4.0Machine learning techniques for equipment failure predictionIndustrial IoT data acquisition and sensor integrationFault detection and anomaly detection systemsPredictive analytics and remaining useful life estimationEdge AI and cloud-based monitoring architecturesDigital twins and intelligent asset managementReal-world industrial use cases and deployment strategiesBest practices for scalable predictive maintenance systems
AI-Powered Predictive MaintenanceUnlock the future of intelligent asset management with AI-driven predictive maintenance.Traditional maintenance strategies often result in unexpected equipment failures, costly downtime, and inefficient operations. This book provides a practical roadmap for levera...

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