LearningCurveCalculator

LearningCurveCalculator - 1460.78 73.04 Coefficient,...

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Learning Curve Calculator 10% <--Note: You can change any value in yel ow 90% 1 100.00 100.00 100.00 The log-log regressions wil often show larger scatter 2 90.00 190.00 95.00 in the early quantities and wil not provide a "perfect" 3 84.62 274.62 91.54 curve fit. 4 81.00 355.62 88.91 5 78.30 433.92 86.78 6 76.16 510.08 85.01 This data is from Figure 1 of the technical paper: 7 74.39 584.47 83.50 Predict Future Failures From Your Maintenance Records 8 72.90 657.37 82.17 by H. Paul Barringer, P.E., 2003 9 71.61 728.98 81.00 10 70.47 799.45 79.94 11 69.46 868.90 78.99 12 68.54 937.45 78.12 13 67.71 1005.16 77.32 14 66.96 1072.11 76.58 15 66.26 1138.37 75.89 16 65.61 1203.98 75.25 17 65.01 1268.99 74.65 18 64.45 1333.44 74.08 19 63.92 1397.35 73.54 20 63.42
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Unformatted text preview: 1460.78 73.04 Coefficient, A--> Exponent, B--> Improvement Rate--> Learning Rate--> <--Note: Everytime the quantity doubles, the previous doubled unit cost is multiplied by the learning rate. Typical Learning Rates are 96% for raw materials to 75% for repetitive electrical operations with most values around 80-90% Unit Number (quantity produced, pieces) Unit Cost (hrs/pc) Cum Total Cost (hrs) Cum Average Cost (hrs/pc) http://www.barringer1.com/pdf/PredictFutureFailures.pdf R--> The beta value < 1 tells you fewer hours/piece are being expended R^2 = 0.989 for goodness of fit...
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This note was uploaded on 12/28/2011 for the course SCM 372 taught by Professor Cook during the Fall '11 term at Michigan State University.

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LearningCurveCalculator - 1460.78 73.04 Coefficient,...

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