A Manufacturing Entropy book ยท Ebook pre-order
Bringing AI Into Manufacturing Without the Sales Pitch. By Nathan Scalf.
AI can do real work in a plant. Whether it does depends on what you feed it and how you bring it in. This book is the order of work I use: find where value is leaking, pick one decision, get clean data for that decision, test whether the tool tells the truth, and prove it on one line with the people who run it. About 30,000 words in 10 chapters.
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Written by Nathan Scalf from his working life in quality and manufacturing, with help from Grok Bot (AI) as a writing assistant.
A plant is different.
Manufacturing is a fact-based business. There's not room for pleasant lies in an environment that can kill people or produce a product that's detrimental to the future of the company.
That's the line I keep coming back to. You can't integrate AIs that are built to please into processes that require truth. And you can't build AI systems on mixed or unclear signals.
From Chapter 1, "The Pitch and the Floor"
Stack enough of those over forty or fifty years and the data starts arguing with itself. The shift log says one thing. The system says another. A summary report is built on another summary report. People on the floor usually know which one to trust. The software doesn't.
Now plug AI straight into that.
If you don't clean up the underlying data first, you're building a highly advanced system on a faulty premise.
From Chapter 1, "The Pitch and the Floor"
The board is useful. It's also where a lot of loss hides.
Value erosion is value leaving the plant while the board still looks fine. A part waits an extra hour and nobody logs it. A handoff drops one detail and the next shift works around it. A machine runs, but not at the rate it should. None of that may show as red on the board. All of it costs money.
From Chapter 2, "Where Value Leaks"