Cost Estimating Using a New Learning Curve Theory for Non-Constant Production Rates

Authored by: Dakotah Hogan , John Elshaw , Clay Koschnick , Jonathan Ritschel , Adedeji B. Badiru , Shawn Valentine

Handbook of Scholarly Publications from the Air Force Institute of Technology (AFIT), Volume 1, 2000–2020

Print publication date:  December  2022
Online publication date:  December  2022

Print ISBN: 9781032116679
eBook ISBN: 9781003220978
Adobe ISBN:


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Traditional learning curve theory assumes a constant learning rate regardless of the number of units produced. However, a collection of theoretical and empirical evidence indicates that learning rates decrease as more units are produced in some cases. These diminishing learning rates cause traditional learning curves to underestimate required resources, potentially resulting in cost overruns. A diminishing learning rate model, namely Boone’s learning curve, was recently developed to model this phenomenon. This research confirms that Boone’s learning curve systematically reduced error in modeling observed learning curves using production data from 169 Department of Defense end-items. However, high amounts of variability in error reduction precluded concluding the degree to which Boone’s learning curve reduced error on average. This research further justifies the necessity of a diminishing learning rate forecasting model and assesses a potential solution to model diminishing learning rates.

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