AI for Predictive Maintenance in Industry 4.0: Extended PdM Methodologies: From Vibration & Thermal to Motor Current, Wear Debris, Pressure, and Efficiency Analysis - Couverture souple

Livre 9 sur 9: Condition Monitoring & Predictive Maintenance Series

Soliman, Mohammed Hamed Ahmed

 
9789403906454: AI for Predictive Maintenance in Industry 4.0: Extended PdM Methodologies: From Vibration & Thermal to Motor Current, Wear Debris, Pressure, and Efficiency Analysis
Couverture souple
ISBN 10 : 9403906456 ISBN 13 : 9789403906454
Editeur : Personal Lean Publications, 2026

Synopsis

Unlike traditional PdM books that focus on a single technique, this guide provides a practical overview of Extended Predictive Maintenance (PdM) methodologies in one volume. It covers both classical approaches―such as vibration, thermal, acoustic, and oil analysis―and advanced techniques including motor current analysis, wear debris monitoring, partial discharge, pressure, and efficiency monitoring.

Rather than replacing specialist handbooks, this book focuses on how to integrate multiple PdM techniques with sensors, industrial data, and AI/ML tools to design Industry 4.0–ready predictive maintenance systems.

You'll learn how to collect and analyze industrial data, apply AI and machine learning models, integrate multiple condition-monitoring methods, and build Industry 4.0–ready predictive maintenance systems. Covering topics from model development and deployment to Digital Twins, Cloud/Edge computing, and ROI evaluation, this book offers a practical roadmap for engineers, reliability professionals, and Industry 4.0 practitioners seeking to implement AI-driven maintenance strategies across modern industries.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

À propos de la quatrième de couverture

Unlike traditional PdM books that focus on a single technique, this guide provides a practical overview of Extended Predictive Maintenance (PdM) methodologies in one volume. It covers both classical approaches―such as vibration, thermal, acoustic, and oil analysis―and advanced techniques including motor current analysis, wear debris monitoring, partial discharge, pressure, and efficiency monitoring.

Rather than replacing specialist handbooks, this book focuses on how to integrate multiple PdM techniques with sensors, industrial data, and AI/ML tools to design Industry 4.0–ready predictive maintenance systems.

You'll learn how to collect and analyze industrial data, apply AI and machine learning models, integrate multiple condition-monitoring methods, and build Industry 4.0–ready predictive maintenance systems. Covering topics from model development and deployment to Digital Twins, Cloud/Edge computing, and ROI evaluation, this book offers a practical roadmap for engineers, reliability professionals, and Industry 4.0 practitioners seeking to implement AI-driven maintenance strategies across modern industries.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
Personal Lean Publications
Date d'édition
2026
Langue
anglais
ISBN 10 
9403906456
ISBN 13 
9789403906454
Reliure
Copertina flessibile
Numéro d'édition
1
Nombre de pages
260
Coordonnées du fabricant
Bookmundo
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