Supporting Affordability-Based Design Decisions in the Presence of Demand Variability

Abstract

In the years since the Cold War, the aerospace industry has seen a shift towards affordability-based design from the primarily performance-based designs of the past era. While many techniques, such as IPPD and PLM, have been implemented in support of this shift, recent developments in the industry have led to major cost overruns and production delays. The increased prevalence of demand variability in the aerospace industry and the difficulty to rapidly adapt production plans are a primary cause of these issues. Furthermore, traditional aircraft designers perform detailed manufacturing cost analysis late in the design process when the majority of the program costs are already committed. With the recent shift to more composite aerostructures, historical regressions and cost estimating relationships used to predict cost and manufacturability are no longer accurate, so postponing more detailed cost analyses to later design phases can lead to high costs due to sub-optimal early design decisions. The methodology presented in this paper addresses these problems by providing the ability to conduct multi-disciplinary trades in the early stages of design, when a large amount of design freedom and cost savings opportunities exist. To enable these multi-disciplinary trades, this paper describes how aircraft performance considerations are integrated with production rate, manufacturing cost, and financial planning metrics into a parametric, visual trade-off environment. The environment, combined with a multi-objective optimization routine, facilitate effective affordability-based trades during the early stages of design. An F-86 Sabre redesigned wingbox using 3 separate manufacturing concepts is used as a proof-of-concept for this research.

Program and Portfolio Affordability Tradeoffs Under Uncertainty Using Epoch‐Era Analysis

“…Bobinis, et al (2013) developed metrics to assess the contextual and dynamic attributes of affordable systems. Siedlak et al (2015) introduced a parametric design and visualization environment to conduct either multi-objective optimization or manual trade-off analyses for system affordability under demand uncertainty. Finally, Wu, Ross, & Rhodes (2014) employed EEA to explore system affordability under a variety of uncertainty factors to provide insight into changing contexts in potential futures.…”