AI in Maintenance & Reliability: Predictive and Prescriptive Maintenance with Artificial Intelligence - Softcover

Soliman, Mohammed Hamed Ahmed

 
9789403911854: AI in Maintenance & Reliability: Predictive and Prescriptive Maintenance with Artificial Intelligence
Softcover
ISBN 10: 9403911859 ISBN 13: 9789403911854
Publisher: Personal Lean Publications, 2026

Synopsis

In today's competitive industrial landscape, downtime is costly - not just in money, but in reputation, customer trust, and operational efficiency. The future of maintenance lies in harnessing the power of Artificial Intelligence to move from reactive fixes to predictive insight and prescriptive action. Dr. Soliman - engineer, professor, and industry consultant - takes you on a practical journey into the world of AI-driven maintenance. Transform operational data into actionable intelligence, reduce unplanned failures, extend equipment life, and maximize return on assets. Inside: The evolution from reactive and preventive maintenance to predictive and prescriptive strategies How to collect, prepare, and leverage industrial data for AI applications Core AI and machine learning techniques for failure prediction Prescriptive maintenance models that recommend optimal interventions Case studies from manufacturing, energy, and transportation sectors Steps to integrate AI into existing systems and measure ROI Preparing your organization for Industry 4.0 and beyond Transform your maintenance strategy. Predict. Prescribe. Perform.

"synopsis" may belong to another edition of this title.

About the Author

Dr. Mohammed Hamed Ahmed Soliman is an internationally recognized Lean expert, lecturer in Industrial Engineering and Management Systems at the American University in Cairo (AUC), executive advisor, and author of more than 150 books and scientific publications on Lean management, the Toyota Production System, quality systems, operational excellence, automotive engineering, and modern publishing systems. He is a member of the Advisory Committee of the IEOM International Society and brings nearly two decades of academic, industrial, and consulting experience across manufacturing, public services, education, and infrastructure sectors. His work bridges engineering, policy, and leadership, helping organizations design systems that flow intelligently and improve continuously. Dr. Soliman has trained professionals throughout the Middle East and has worked with organizations including Princess Nourah University in Saudi Arabia and Vale Oman Pelletizing Company. He is the founder of Personal Lean Publications and continues to write on Lean transformation, industrial systems, automotive technologies, and the evolving global publishing ecosystem.

From the Back Cover

In today’s competitive industrial landscape, downtime is costly ― not just in money, but in reputation, customer trust, and operational efficiency. The future of maintenance lies in harnessing the power of Artificial Intelligence to move from reactive fixes to predictive insight and prescriptive action.

Dr. Soliman ― engineer, professor, and industry consultant ― takes you on a practical journey into the world of AI-driven maintenance. Transform operational data into actionable intelligence, reduce unplanned failures, extend equipment life, and maximize return on assets.

Inside:

The evolution from reactive and preventive maintenance to predictive and prescriptive strategies

How to collect, prepare, and leverage industrial data for AI applications

Core AI and machine learning techniques for failure prediction

Prescriptive maintenance models that recommend optimal interventions

Case studies from manufacturing, energy, and transportation sectors

Steps to integrate AI into existing systems and measure ROI

Preparing your organization for Industry 4.0 and beyond

Transform your maintenance strategy. Predict. Prescribe. Perform.

"About this title" may belong to another edition of this title.

Publisher
Personal Lean Publications
Publication date
2026
Language
English
ISBN 10 
9403911859
ISBN 13 
9789403911854
Binding
Taschenbuch
Edition number
1
Number of pages
128