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Is your plant AI-ready?
Twelve honest checks across data, sensors, process maturity, and governance. Score yourself before you spend a dollar on models or sensors.
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The 12-Point Checklist
4 sections · 12 checks01
Data Foundation
- You collect machine/process data automatically (not just manual logs) on key presses.
- Process data is stored, time-stamped, and retrievable — not trapped on the machine.
- You can link a part or batch back to the process conditions that produced it.
02
Sensors & Process Maturity
- Your processes are characterized with scientific molding / DOE, not just dialed in by feel.
- You have the sensing (pressure, temperature, etc.) that the decisions you want to automate depend on.
- Your process is stable enough that today's data reflects how it actually runs.
03
Problem & ROI Clarity
- You can name a specific, costly pain point (scrap, cycle time, downtime, inspection cost).
- You have a rough sense of what solving it would be worth per year.
- You're prepared to start where ROI is clearest, not everywhere at once.
04
Governance & Readiness
- If you're regulated, you know AI touching the process must be validated and explainable.
- There's an owner who would maintain a model after it's deployed.
- Leadership expects an honest answer about where AI is premature — not just where it helps.
How to Read Your Score
- 9–12 checked: You’re AI-ready. The opportunity is prioritizing the highest-ROI use case and deploying it validated.
- 5–8 checked: You’re close. A focused assessment will identify the few gaps to close before AI pays off.
- 0–4 checked: Start with the data foundation. AI on top of weak data produces confident, wrong answers.
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An AI Readiness Assessment turns this self-check into a scored, prioritized roadmap for your specific operation.