Manufacturing AI: Building the Data Foundation for the Next Industrial Revolution

· UMDA Publishing · Narrated by Brian Arens
1 review
Audiobook
11 hr 1 min
Unabridged
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About this audiobook

Turn Manufacturing Data into a Scalable Competitive Advantage

Factories create massive amounts of data from IoT sensors, MES, SCADA, quality systems, supply chain, maintenance, and others. Yet most organizations can’t turn it into decisions fast enough. The result is reactive firefighting and AI pilots that stall.

The Unified Manufacturing Data Architecture (UMDA) is a practical framework built for industry, not adapted from IT. It shows you how to handle real-time streams, integrate legacy systems, enforce security, and scale AI across sites.


What you’ll learn

  • Design Common Data Models (CDMs) that unify complex, multi-system data
  • Use edge federation for low-latency, on-site decisions
  • Build a Unified Data Layer (UDL) that powers analytics and LLMs
  • Apply data contracts for quality, security, and compliance
  • Deploy Edge Intelligence Hubs and agentic AI/LLM routing
  • Connect digital threads/twins to real-time operations

Potential outcomes when UMDA is implemented well

  • Identify failure patterns earlier and plan maintenance proactively
  • Catch quality drift in real time and reduce scrap/rework
  • Synchronize planning with live constraints for fewer schedule breaks
  • Shorten time-to-value by standardizing data and integrations
  • Share proven improvements across sites with less friction

Stop drowning in data. Build an AI-ready architecture that anticipates, adapts, and continuously improves by turning information into measurable results.

Turn Manufacturing Data into a Scalable Competitive Advantage Factories create massive amounts of data from IoT sensors, MES, SCADA, quality systems, supply chain, maintenance, and others. Yet most organizations can’t turn it into decisions fast enough. The result is reactive firefighting and AI ...

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Ratings and reviews

1 review
John Harwood
October 5, 2025
Most books talk about use cases. This one shows you how to build the plumbing so use cases actually work. Manufacturing AI is the rare audiobook that treats the factory as it is: mixed vintages, mixed vendors, and real constraints. The UMDA framework lays out a clear path from edge signals to governed enterprise analytics to agentic AI, with data contracts and feedback loops tying it together.
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About the author

Ryan has spent more than 25 years helping manufacturers turn complex technology into real-world results. He started his career in the automotive industry, working directly with MES applications, legacy systems, lean accelerators, equipment, PLCs, and HMIs. That hands-on experience gave him a practical understanding of how factories really run, a perspective that continues to shape his work today. Now working as a leader in manufacturing technology consulting, Ryan oversees global efforts in digital transformations involving AI and analytics enablement. His work supports some of the most advanced and demanding manufacturing environments in the world, where clear data and smart systems are key to staying competitive. Throughout his career, Ryan has helped companies in industries including pharmaceuticals, food & beverages, industrial products, and discrete manufacturing. He specializes in applying lean manufacturing practices and his knowledge of manufacturing standards to build scalable architectures that connect legacy factory infrastructure with modern platforms in a cohesive, intelligent framework. His technical focus includes IoT enablement, data modeling, contextualized pipelines, governance frameworks, and emerging AI technologies. What drives Ryan is a belief that data should work for the people who use it. He designs and builds architectures that are built to last, easy to maintain, and ready to grow with the evolving needs of modern manufacturing.
Ryan has spent more than 25 years helping manufacturers turn complex technology into real-world results. He started his career in the automotive industry, working directly with MES applications, legacy systems, lean accelerators, equipment, PLCs, and HMIs. That hands-on experience gave him a prac...

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