Consider the p = 4 process variables in Table 11.6. After applying the PCA procedure to the first 20 observations data (see Table 11.7), suppose that the first three principal components are retained.
Answer to relevant QuestionsConsider the p = 9 process variables in Table 11.5 (a) Perform a PCA on the first 30 observations. Be sure to work with the standardized variables. (b) How much variability is explained if only the first r = 3 principal ...Consider a T2 control chart for monitoring p = 10 quality characteristics. Suppose that the subgroup size is n= 3 and there are 25 preliminary samples available to estimate the sample covariance matrix. m = 25 preliminary ...Consider the data in Table 12.1. Suppose that an adjustment is made to the output variable after every observation. Compare the performance of this chart to the one in Table 12.1 and Figure 12.12. R.D. Snee (“Experimenting with a Large Number of Variables,” in Experiments in Industry: Design, Analysis and Interpretation of Results, by R.D. Snee, LB. Hare, and J.B. Trout, eds., ASQC, 1985) describes an experiment ...An article in Quality Progress describes the use of factorial experiments to improve a silver powder production process. This product is used in conductive pastes to manufacture a wide variety of products ranging from ...
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