Learning Curve Cost Reduction Calculator
Labor-intensive builds get cheaper as crews learn the work. This calculator turns a first-unit estimate and a learning rate into the average cost, last-unit cost and total for any quantity, so you can price a lot or a multi-year program with a defensible curve.
Your numbers
Cost or labor hours of unit 1. Hours work too, the math is the same.
Cost falls to this percent each time cumulative quantity doubles. 100 means no learning.
Total units produced in the lot or program.
Your results
Uses Wright's cumulative average model. Crawford's unit model gives somewhat different numbers. Always calibrate the learning rate against your own actuals.
Average and last-unit cost as quantity grows
Sweeps Cumulative units from 1 to 200, holding your other inputs fixed.
Fit a learning curve to your own job history
Optional: we can review your serial-number labor history and propose a calibrated curve.
Optional. The tool and every export work without this. No spam.
How to use the calculator
Enter the cost or hours of the first unit, the learning rate and the cumulative quantity. The learning rate is the percentage the cumulative average falls to each time quantity doubles, so an 85 percent curve means unit 2 averages 85 percent of unit 1 and the average of the first four is 85 percent of the average of the first two. Read the average cost for quoting a whole lot, the last-unit cost for follow-on pricing, and the saving line for the value of the learning you are assuming. The chart sweeps quantity from 1 to 200 so you can see where the curve flattens.
- Use hours instead of dollars if you want a labor-only curve, then apply rates afterwards
- Run 80, 85 and 90 percent to see the sensitivity
- Keep material cost out of the curve, material rarely learns
The method behind it
Wright's model says the cumulative average cost of n units equals T1 times n to the power b, where b = ln(rate) / ln(2). Total cost is n times that average, and the cost of the last unit is the difference between the total for n units and for n-1 units. Aerospace and defense estimators use this widely because cost proposals often require a documented learning assumption. Typical assembly-heavy work lands between 80 and 95 percent, while highly automated work sits near 100 percent because the machine sets the pace.
Common mistakes
The most frequent error is applying a steep curve to machine time. Machines run at programmed cycle time from unit one, so learning shows up in setups, handling and inspection, not spindle time. A second error is forgetting breaks in production: after a long gap, crews forget and the curve partly resets. Finally, do not extend a curve fitted on 20 units to 2,000 without evidence, because real curves flatten as improvement opportunities run out. In your ERP, compare actual job hours by cumulative serial number against the curve to recalibrate each lot.
Frequently Asked Questions
What learning rate should I use for assembly work?
Complex manual assembly commonly falls in the 80 to 90 percent range and simple repetitive work in the 90 to 95 percent range. Mixed machine and manual work is higher. Fit the rate to your own lot history where possible, since industry rules of thumb vary widely.
What is the difference between Wright and Crawford?
Wright tracks the cumulative average cost falling per doubling. Crawford tracks the individual unit cost falling per doubling. For the same percentage, Crawford produces a lower total because the whole unit curve drops, so state which model your customer expects.
Does learning apply to material cost?
Generally no. Material cost per unit is set by the bill of materials and supplier prices. Scrap and rework driven by workmanship can improve with learning, but treat that separately from the labor curve.
Can I use hours instead of dollars?
Yes. Enter first-unit hours, read the average and total in hours, then multiply by the labor rate. The currency symbol is only a label. This is usually cleaner because wage rates change independently of learning.
If your ERP holds actual labor by serial number, we can build a private report that fits the learning rate from your own history instead of assuming one.
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