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In recent years, a number of attempts have been made to estimate the cost of future weapon systems toward the goal of optimizing acquisition policy. This report focuses specifically on the effects of material mix, manufacturing techniques, and geometric part complexity on the cost of military airframes. It begins by offering background information on those materials that are most critical to airframe manufacture and on the relative advantages of both traditional and evolving part fabrication techniques. It then proceeds to a quantitative analysis of the cost implications of various materials and manufacturing techniques on airframe production, drawing both from an industry survey and from analysis of industry data. The data thus derived are then integrated with those of a comprehensive historical database. The report concludes that composites, while offering a number of advantages over metals in airframe manufacture, are generally associated with higher costs across a range of categories. At the same time, it concludes that while new manufacturing technologies hold the potential to diminish airframe manufacturing costs, the increased airframe complexity of future fighter aircraft may well offset this advantage. The report recommends that cost analysts remain abreast of changes in industry practice so that they may more accurately gauge the potential effects of such changes on future airframe costs.
Good cost estimates can make important contributions to effective acquisition policy. RAND has a long history of producing cost-estimating methodologies. Two of its more recent studies are Hess and Romanoff (1987) and Resetar, Rogers, and Hess (1991). This report both updates and extends these earlier studies, focusing on the effects of material mix, manufacturing technique, and part geometric complexity on cost. We collected two types of information on these effects. First, we surveyed the military airframe industry for estimates of how aircraft production costs vary with airframe structure material mix. Second, we analyzed a large set of actual part data from recent aircraft manufacturing efforts that we collected from industry. We also estimated a set of airframe relationships (CERs) for labor hours based on MACDAR, a historical airframe database. We then integrated the effects of material mix into these estimates.
CSIS senior adviser Mark Cancian annually produces a series of white papers on U.S. military forces, including their composition, new initiatives, long-term trends, and challenges. This report is a compilation of these papers and takes a deep look at each of the military services, the new Space Force, special operations forces, DOD civilians, and contractors in the FY 2021 budget. This report further includes a foreword regarding how the Biden administration might approach decisions facing the military forces, drawing on insights from the individual chapters.
This report is part of a project responding to a call by the U.S. Air Force to update cost estimating methodologies for new weapons systems-in particular, fighter aircraft. The Air Force was concerned that Cost Estimating Relationships (CERs) based on older aircraft did not adequately reflect the acquisition and manufacturing environment within which a new fighter, such as the Joint Strike Fighter (JSF) would be produced. This report is one of a series, all of which address some aspect of how to incorporate the new DoD acquisition and manufacturing environments into historical cost estimating relationships or methodologies (See Younossi, Graser, and Kennedy, 2001; Lorell and Graser, 2001). Using the CER methodology for example, the cost of a future aircraft is estimated as a function of its physical or characteristics or other program variables, using a series of equations wherein the performance and program variables are inputs, and cost or labor hours are the outputs. To create these equations, actual costs (or labor hours) to produce previous aircraft are collected and used as the dependent variables in statistical regression analysis. Explanatory variables typically include such factors as cumulative production quantity, annual production rate, such aircraft characteristics as weight and speed, and others. The resulting equations are referred to as "cost estimating relationships," or CERs. Obviously, the ability of these equations to forecast future systems costs hinges on how well past performance is a predictor of the future.
This report is part of a project responding to a call by the U.S. Air Force to update cost estimating methodologies for new weapons systems-in particular, fighter aircraft. The Air Force was concerned that Cost Estimating Relationships (CERs) based on older aircraft did not adequately reflect the acquisition and manufacturing environment within which a new fighter, such as the Joint Strike Fighter (JSF) would be produced. This report is one of a series, all of which address some aspect of how to incorporate the new DoD acquisition and manufacturing environments into historical cost estimating relationships or methodologies (See Younossi, Graser, and Kennedy, 2001; Lorell and Graser, 2001). Using the CER methodology for example, the cost of a future aircraft is estimated as a function of its physical or characteristics or other program variables, using a series of equations wherein the performance and program variables are inputs, and cost or labor hours are the outputs. To create these equations, actual costs (or labor hours) to produce previous aircraft are collected and used as the dependent variables in statistical regression analysis. Explanatory variables typically include such factors as cumulative production quantity, annual production rate, such aircraft characteristics as weight and speed, and others. The resulting equations are referred to as "cost estimating relationships," or CERs. Obviously, the ability of these equations to forecast future systems costs hinges on how well past performance is a predictor of the future.
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