Blog: Shop Floor to AI: From Signals, to Context, to Decisions#4507
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Blog: Shop Floor to AI: From Signals, to Context, to Decisions#4507sumitshinde-84 wants to merge 6 commits intomainfrom
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…shop-floor-to-ai-signals-context-decisions.md
andreguerra7
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Feb 6, 2026
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@sumitshinde-84 Approved, added minor comments
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| You can't fix a three-layer problem with a one-layer solution. | ||
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| Companies repeatedly make the same mistake: they drop AI models directly onto the signal layer (pure time-series analysis on raw sensor data) then wonder why predictions are worthless. The model identifies a pattern, but it's blind to the fact that context just changed. It flags anomalies that are actually normal for this product recipe. It misses failures because the signal appeared fine while the context indicated problems. |
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@sumitshinde-84 Might be: drop AI models directly into the signal layer
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| In a UNS, a motor current is no longer just a number stored in a historian. It's published as *Line 3 / Conveyor 2B / Motor Current*, alongside the active recipe, operating mode, ambient conditions, and relevant maintenance history. Every system sees the same structured truth, continuously updated. | ||
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| This architectural shift is what makes AI viable on the factory floor. |
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@sumitshinde-84 suggestion: This shift in architecture is what makes AI viable on the factory floor.
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| We instrumented everything: motors, conveyors, bearings, valves, streaming thousands of data points per second. Historians filled to capacity. Dashboards displayed every metric. Yet despite this data visibility, we couldn't see what was happening until something broke. | ||
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| This article reveals the missing link from shop floor to AI: why raw signals create noise, not understanding, how context transforms that noise into meaning, and why meaning is the prerequisite for decisions anyone will trust. |
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@sumitshinde-84 suggestion: This article reveals the missing link from shop floor to AI: why raw signals create noise instead of understanding, how context transforms that noise into meaning....
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