Defense Acquisition Research Journal Issue 95

A Learning Curve Model Accounting for the Flattening Effect in Production Cycles

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To address this research gap, our study aims to model a function that has the added precision of diminishing learning effects over time by introducing a learning curve decay factor that more closely models actual production cycle learning. We will accomplish this by developing a new learning curve model that minimizes the amount of error compared to current estimation models. Learning curves, specifically when estimating the expected cost per unit of complex manufactured items such as aircraft, are frequently modeled with a mathematical power function. The intent of these models is to capture the expected reduction in costs over time due to learning effects, particularly in areas with a high percentage of human touch labor. Typically, as produc tion increases, manufacturers identify labor efficiencies and improve the process. If labor efficiencies are identified, it translates to unit cost savings over time. The general form of the learning curve model frequently used today is based on Wright’s theory and is shown in Equation 2. Note that the structure of the exponent b ensures that as the number of units produced doubles, the cost will decrease by a given percentage defined as the learning curve slope (LCS). For example, when LCS is 0.8, then the cost per unit will decrease by 80% between units 2 and 4.

Cost ( x ) = Ax b

(2)

Where: Cost(x) = cumulative average cost per unit

A = theoretical cost to produce the first unit x = cumulative number of units produced b = ln Learning Curve Slope ln 2

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Defense ARJ, January 2021, Vol. 28 No. 1 : 72-97