AI-DRIVEN PREDICTIVE MAINTENANCE FOR INDUSTRIAL OPERATIONS

Your Plant Is Bleeding Millions. The Warning Signs Were There for Weeks.
At 2:47 a.m., a bearing in a centrifugal pump at a Gulf Coast petrochemical facility reached the end of its service life. The failure had been developing for nine weeks. The vibration data showed it. The temperature trends confirmed it. Nobody was watching.
Seventy-one hours later, after an emergency shutdown, a contaminated process line, and a rush parts order, the total damage exceeded $1.08 million.
The bearing that started it all cost $340.
This is not a story about bad luck. It is a story about a maintenance strategy built for a world that no longer exists, and it happens thousands of times every year across manufacturing plants, refineries, utilities, and processing facilities worldwide.
The technology to prevent it exists right now. The barrier is no longer financial. The barrier is knowledge. This book closes that gap.
The Only Book That Takes You From Failure Physics to Full AI Deployment, Without Losing You Along the Way
AI-Driven Predictive Maintenance for Industrial Operations is the practitioner's implementation guide that the industrial maintenance world has been missing.
Not a vendor whitepaper. Not an academic ML textbook. A complete, end-to-end field guide written by an industrial AI architect who has personally led PdM programs from single-plant pilots to enterprise deployments spanning dozens of sites and thousands of monitored assets.
This Book Is for You If...

• You are a Maintenance Manager being asked to deliver AI results with limited budgets and legacy infrastructure
• You are a Reliability Engineer who understands FMEA and failure physics but has never trained a machine learning model
• You are a Data Scientist who knows Python but has never worked with IIoT sensor data or plant-floor operational realities
• You are a Plant or Controls Engineer responsible for IIoT infrastructure, SCADA integration, or edge architecture
• You are an Operations or Technology Leader building the business case or evaluating vendor platforms

• 50-70% reduction in unplanned downtime
• 20-40% reduction in maintenance costs
• 40% extension in average asset lifespan
• Up to 30:1 ROI within 18 months