Consider the cascade process data in Table 11.5. In fitting regression models to both y1 and y2 you will find that not all of the process variables are required to obtain a satisfactory regression model for the output variables. Remove the nonsignificant variables from these equations and obtain subset regression models for both y1 and y2. Then construct individuals control charts for both sets of residuals. Compare them to the residual control charts in the text (Fig. 11.11) and from Exercise 11.18. Are there any substantial differences between the charts from the two different approaches to fitting the regression models?
Answer to relevant QuestionsA product has three quality characteristics. The nominal values of these quality characteristics and their sample covariance matrix have been determined from the analysis of 30 preliminary samples of size n = 10 as ...Reconsider the situation in Exercise 11.2. Suppose that the sample mean vector and sample covariance matrix provided were the actual population parameters. What control limit would be appropriate for phase II of the control ...Use the data in Exercise 12.9 to construct a bounded adjustment chart. Use = 0.2 and set L = 4. How does the bounded adjustment chart perform relative to the integral control adjustment procedure in part (a) of Exercise ...Consider the observations in Table 12E.2. The target value for this process is 50. (a) Set up an integral controller for this process. Assume that the gain for the adjustment variable is g = 1.6 and assume that = 0.2 in ...One of the variables in the experiment described in Exercise 13.19, heat treatment method (C), is a categorical variable. Assume that the remaining factors are continuous. (a) Write two regression models for predicting crack ...
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