Machinery Oil Analysis & Condition Monitoring - Enhanced Edition: AI-Powered Oil Analysis for Predictive Maintenance #916379

Maximize equipment reliability. Reduce downtime. Harness the power of AI for smarter oil analysis.
In today's competitive industrial environment, machinery failures are costly—not just in repairs, but in lost production and efficiency. This enhanced edition of Machinery Oil Analysis & Condition Monitoring combines proven oil analysis methods with the latest in artificial intelligence, IoT, and predictive maintenance strategies.
Drawing on over a decade of engineering experience, Mohammed Hamed Ahmed Soliman provides a practical, hands-on guide to implementing modern oil analysis programs that deliver measurable ROI.
Inside You'll Learn:

• Fundamentals of Oil Analysis – Sampling, testing methods, and contamination control.
• Condition Monitoring Techniques – How oil data integrates with vibration, thermography, and ultrasonic testing.
• AI & Machine Learning in Oil Analysis – Predict failures before they happen with advanced analytics.
• Real-World Case Studies – From industrial plants to fleet maintenance operations.
• Step-by-Step Implementation Guide – Build your own AI-powered oil analysis program.
• Future Trends – Digital twins, autonomous maintenance, and sustainable lubrication strategies.

Whether you are a maintenance engineer, reliability professional, plant manager, or technical student, this book equips you to:

• Detect early signs of wear and contamination.
• Extend oil life and reduce waste.
• Cut costs through targeted, data-driven maintenance.
• Stay ahead of the curve in Industry 4.0 and 5.0 environments.

Includes:

• 12 updated chapters with enhanced figures, examples, and AI-powered insights.
• Implementation flowcharts, sample reports, and ROI calculation templates.
• Special coverage on integrating online sensors and predictive analytics.

Turn your oil analysis program into a competitive advantage.
Get the Enhanced Edition and start building smarter, more reliable machinery today.