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Draft Addendum to the Statistical Summary of the Mack T10 Precision/BOI Matrix Including IR Oxidation. Summary. This is a preliminary analysis. Data are not available yet for used oil viscometrics.

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**Draft Addendum to theStatistical Summary of theMack T10**Precision/BOI MatrixIncluding IR Oxidation**Summary**• This is a preliminary analysis. Data are not available yet for used oil viscometrics. • A draft analysis of the IR Oxidation numbers is presented in this draft. It is not a consensus analysis. • Method 2 IR at 300 hours benefits from using the -0.8 power transformation. • Method 5 IR at 300 hours benefits from a natural logarithm transformation. • Both IR measures were strongly correlated with each other and with delta lead.**Summary(continued)**• Labs and stands within labs were significant for both IR measures. • Technology had a significant effect for both IR measures. • Base Oil had a significant effect for Method 2 IR. • Observations with large Studentized residuals were seen for both IR measures. • Oil means and standard deviations are given for potential use in LTMS.**Data Set**• Table 1 shows the design for the matrix. • All operationally valid data with the exception of CMIR 38815 are included. • The T10 Task Force decided to eliminate CMIR 38815 from the analysis. • This was an early test in Lab B on Oil A which had high silicon and aluminum in the used oil. It also had high ring weight loss with low cylinder liner wear. The lab ran Oil A again with non-anomalous results. The matrix remains intact as planned. • IR Oxidation numbers using Method 2 and Method 5 from the SwRI analyses of samples at 300 hours have been added.**Table 2. Mack T10 Precision Matrix Datafrom TMC 07/16/01 (IR**from Joe Franklin 08/03/01)**Transformations**• Box-Cox procedure was applied using all matrix data. • Delta lead benefits from a natural logarithm transformation. • Method 2 IR at 300 hours is best raised to a power of -0.8 for analyses. • Method 5 IR at 300 hours likes a natural logarithm transformation. • No data transformations are indicated for other responses analyzed.**M2IR300-0.8Summary of Model Fit**• Model factors include Laboratory (A,B,D,F,G), Stand within Laboratory (A1,A2,G1,G2), Technology (X,Y,Z), Base Oil (1,2,3) and Technology by Base Oil interaction. • Technology, Base Oil, Lab, and Stand within Lab were significant. • Root MSE from the model was 0.000223 (13 df). • The R2 for the model was 0.94. • Figure 1 illustrates the least squares means by oil. • Figure 2 summarizes least squares means for technologies and base oils. • Figure 3 summarizes least squares means for labs and stands within labs. • Stand within Lab significance was driven by the two stands in Lab G which were significantly different from each other. • Power transformation was appropriate. • The test of Oil E in stand G2 had a large Studentized residual.**Figure 2Technology and Base Oil Least Squares Means for**tM2IR**Figure 3Lab and Stand within Lab Least Squares Means for**tM2IR**Ln(M5IR300)Summary of Model Fit**• Model factors include Laboratory (A,B,D,F,G), Stand within Laboratory (A1,A2,G1,G2), Technology (X,Y,Z), Base Oil (1,2,3) and Technology by Base Oil interaction. • Technology, Lab, and Stand within Lab were significant. • Root MSE from the model was .3215 (13 df). • The R2 for the model was 0.91. • Figure 4 illustrates the least squares means by oil. • Figure 5 summarizes least squares means for technologies. • Figure 6 summarizes least squares means for labs and stands within labs. • Stand within Lab significance was driven by the one stand in Lab G which was significantly different from all others. • Natural logarithm transformation was appropriate. • The second test of Oil A in stand G2 had a large Studentized residual.**Figure 6 Lab and Stand within Lab Least Squares Means for**ln(M5IR)

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