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Production Cost CER Our dependent variable for production cost will be the cost given some specific unit number. However, the question is, what is the appropriate unit number? Previous studies have developed relation- ships at unit 1000 (T1000) (Large, 1970; Anderson, 1972; Nelson and Timson, 1974; Nelson, 1977; Nelson et al., 1979; Birkler, Garfinkle, and Marks, 1982) while others have used unit 100 (T100) (for exam- ple, Daley and Richey, 1994). To determine the appropriate unit number, we initially developed a regression equation for a T1 (unit 1) relationship that included a term that was related to the log of the cost improvement slope. The regression results are shown in Table 6.9, and Figure 6.5 shows the corresponding residual plot for new engines. Table 6.9 Production Cost Regression Statistical Analysis 79 Observa- Variable tions lnT1 24 lnslope 24 lnritf 24 ab 24 lndrywt 24 Mean Median 1.157 1.258 –0.032 –0.031 7.688 7.675 0.542 1.000 8.005 8.108 Standard Deviation Minimum 0.723 –0.099 0.051 –0.114 0.147 7.378 0.509 0.000 0.381 7.259 Maximum 2.273 0.097 7.922 1.000 8.436 lnT1 = –10.40 – 8.550 lnslope + 0.482 ab + 1.162 lnritf + 0.262 lndrywt (–13.02) (4.59) (3.63) (2.42) R-squared = 0.9703. Adjusted R-squared = 0.9641. RMSE = 0.13703. lnT1 = natural log of the production price for unit Number 1 in 2001 $millions. lnslope = natural log of the cost improvement curve slope. ab = binary variable (1) if it is an afterburning engine, (0) if not. lndrywt = natural log of the dry weight for the engine in pounds. lnritf = natural log of the rotor inlet temperature in degrees Fahrenheit.PDF Image | Military Jet Engine Acquisition Technology Basics and Cost-Estimating Methodology
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