Twelve working calculators I use on the floor — pick one from the list and it opens with a live figure that responds as you type. No sign-up, nothing saved.
OEE is a product, not an average — each factor punishes the others. The gauge fills to your OEE and changes colour by benchmark band.
The reliability trio behind the Availability factor in OEE. Enter run time, failures, and total downtime.
Enter the replacement value of your plant's equipment. The bars show average, best-in-class, and top-quartile spare-parts inventory against it — in dollars.
Unplanned downtime rarely shows up as one line item, so it stays underinvested against. Put a real annual number on it.
Takt is the drumbeat of demand — how often you must finish a unit to keep up. If your cycle time is longer than takt, the line can't meet demand.
Changeover time recovered is production time gained — on equipment you already own. Enter current and target changeover times.
Lead time = WIP ÷ throughput. Cut the work-in-process and lead time drops in exact proportion — no faster machines required.
Each step looks fine alone — but yields multiply. Enter first-pass yields of up to four steps and watch end-to-end yield decay: the "hidden factory."
Translate defects into the universal quality language: defects per million opportunities, yield, and sigma level. The gauge fills to your yield.
Can your process actually hold the spec? Enter the spec limits, your process mean and standard deviation — the bell curve redraws against the limits, and you get Cp and Cpk.
Most losses come from a few causes. Enter your causes and counts (downtime minutes, defects, complaints). The chart sorts them, draws the cumulative line, and highlights the vital few that drive 80%.
Before you put AI or Industry 4.0 on top of your data, the measurement layer has to be real. Check what's true today — the ring fills as you go.
Want a hand applying any of these on your own floor? Let's talk.
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