Incorporating learning curve analysis into medium-term capacity planning procedures: a simulation experiment

The purpose of this paper is to determine the type of company which can benefit from incorporating learning curve analysis into its medium-term capacity planning procedures and the effect of information aggregation on learning curve capacity projections. The research into these two issues uses a simulation study that describes the relevant production and information characteristics. Four production characteristic variables are investigated: (1) average learning rate, (2) run-time variance, (3) learning rate mix, and (4) run-time distribution. A fifth variable, level of data aggregation, is an information characteristic and is also investigated. The results of this study indicate that there are significant increases possible in the accuracy of medium-term capacity projections from the incorporation of learning curve analysis in firms with high rates of learning or with low noise levels in their data. However, when a company has either low to moderate rates of learning or moderate noise, a standard analysis, which uses the sample mean of the last planning horizon's data, provides projections approximately as accurate as a learning curve estimate.