Time Phasing Aircraft R&D Using the Weibull and Beta Distributions

Abstract

Early research on time phasing primarily focuses on the theoretical foundation for applying the cumulative distribution function, or S-curve, to model the distribution of development expenditures. Minimal methodology prior to 2002 provides for estimating the S-curve’s parameter values. Brown et al. (2002) resolved this shortcoming through regression analysis, but their methodology is not specific to aircraft and does not consider aircraft-specific variables, such as first flight. Using a sample of 26 Department of Defense aircraft programs, we build upon Brown et al.’s work by examining whether a model driven by aircraft-specific variables can more accurately predict budget requirements. As a baseline, we compare our model to the commonly cited 60/40 “rule of thumb,” which assumes 60% expenditures at 50% schedule. We discover that our developed Weibull model explains 74.6% of total variation in annual budget, improving the estimation of budgets by 6.5%, on average, over the baseline 60/40 model.