Artificial Intelligence Revolution in Manufacturing: Modernizing Operations, Maintenance, and Service Delivery

Who this book is for

• Curious readers who want a grounded view of Artificial Intelligence Revolution in Manufacturing without the applause soundtrack.
• Operators, managers, and curious readers who want to know whether AI in manufacturing improves the workflow or just adds another dashboard to ignore.
• Anyone who wants clear context on where AI is already being used in manufacturing today — and where uptime, scrap, and margins bite before they trust the louder claims.
• Readers looking for sharper judgement on the day-to-day pressure points are uptime, quality, and plant reality rather than recycled buzzwords.

Key themes

• Manufacturing
• Artificial Intelligence
• AI Trends

What you’ll learn

• Where AI is already being used in manufacturing today — and where uptime, scrap, and margins bite.
• The day-to-day pressure points are uptime, quality, and plant reality.
• Key themes including predictive maintenance, quality control, automation, supply chains.
• The limits, risks, and awkward questions worth asking before you sign off on the sales pitch.

Audience fit

Best for people weighing real adoption choices in Manufacturing. It is written for operations leaders, plant teams, engineers, and readers tracking industrial automation who want practical context rather than brochure copy.

Deeper overview

A guide to AI in manufacturing — predictive maintenance, automated production, optimised supply chains, and how intelligent operations are reshaping modern industry. It keeps the focus on the stubborn realities inside Manufacturing, especially where uptime, scrap, and margins bite.

Why this title is useful in practice

In practice, Artificial Intelligence Revolution in Manufacturing: Modernizing Operations, Maintenance, and Service Delivery is most useful when the real issue is the point where promised efficiency in manufacturing meets maintenance logs, handovers, and failure modes. It is written for readers who want a grounded, non-technical view of AI in Manufacturing, including operations leaders, plant teams, engineers, and readers tracking industrial automation, and it tackles questions such as where AI is already being used in manufacturing today — and where uptime, scrap, and margins bite., which makes it more useful than a generic explainer when someone has to decide what happens next in an actual workflow, classroom, policy setting, or team.

Practical outcomes

You should finish it with a clearer feel for where AI in manufacturing improves the workflow, where it adds fragility, and what to pilot before anyone starts chest-thumping.

• Understand why manufacturing matters now and what the evidence actually says.
• Assess whether manufacturing is applicable to your context before committing resources.
• Ask the right governance and implementation questions before adoption decisions become expensive.

Chapter-level signals

What makes this title distinct

Artificial Intelligence Revolution in Manufacturing: Modernizing Operations, Maintenance, and Service Delivery keeps its boots on the ground, looking at workflow, failure modes, and whether the gains survive contact with real operations in manufacturing.

Because decisions in Manufacturing affect uptime, throughput, quality, and worker safety. Once AI enters the loop, sloppy assumptions get expensive very quickly.