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Prediction models for validating development phase cost estimates for missile development programs.

机译:用于验证导弹开发计划的开发阶段成本估算的预测模型。

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Cost estimates for missile development phase programs are almost always significantly underestimated. The purpose of this research was to determine if missile program development cost might be estimated using regression models at the uppermost Cost Estimating Structure (CES) level. Using this process, it would be possible to use this same model to validate development phase cost estimates made by summing estimates made at lower CES levels. A regression model developed at a higher CES level has the inherent advantage of including more unknown-unknowns (embedded in the historical data) than models created at more detailed CES levels. Unknown-unknowns are defined as cost related activities that are not known to the cost estimator at the time the estimate must be prepared. The results of this research indicate that statistically significant models are achievable, with a coefficient of determination ( r2) value greater than 90%. The resulting cost estimating models may be used to validate future development phase missile program cost estimates. Thus, missile developers, program managers, and acquisition authorities may use this information to make better, more confident decisions concerning the billions of dollars annually spent on missile development programs.
机译:导弹开发阶段计划的费用估算几乎总是被大大低估了。这项研究的目的是确定是否可以在最高成本估算结构(CES)级别使用回归模型估算导弹计划的开发成本。通过使用此过程,可以使用相同的模型通过汇总在较低CES水平下所做的估算来验证开发阶段的成本估算。与在更详细的CES级别上创建的模型相比,在更高的CES级别上开发的回归模型具有固有的优势,包括更多的未知数(嵌入在历史数据中)。未知-未知是指与成本相关的活动,在估计必须准备时,成本估算人员不知道。这项研究的结果表明,具有统计学意义的模型是可以实现的,其确定系数( r 2 )值大于90%。由此产生的成本估算模型可用于验证未来发展阶段导弹计划的成本估算。因此,导弹开发人员,项目经理和采购当局可以利用这些信息来做出更好,更自信的决策,这涉及每年在导弹开发项目上花费的数十亿美元。

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