# Question

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 samples, n = 3 sample size, p = 10 characteristics, a = 0.005

(a) Find the phase II control limits assuming that a = 0.005.

(b) Compare the control limits from part (a) to the chi-square control limit. What is the magnitude of the difference in the two control limits?

(c) How many preliminary samples would have to be taken to ensure that the exact phase II control limit is within 1% of the chi-square control limit?

m = 25 preliminary samples, n = 3 sample size, p = 10 characteristics, a = 0.005

(a) Find the phase II control limits assuming that a = 0.005.

(b) Compare the control limits from part (a) to the chi-square control limit. What is the magnitude of the difference in the two control limits?

(c) How many preliminary samples would have to be taken to ensure that the exact phase II control limit is within 1% of the chi-square control limit?

## Answer to relevant Questions

Rework Exercise 11.7, assuming that the subgroup size is n= 5.3 m= 25 preliminary samples, n = 5 sample size, p = 10 characteristics, a = 0.005 (a) Find the phase II control limits assuming that a = 0.005. (b) Compare the ...Consider the data in Table 12.1. Construct a bounded adjustment chart using λ = 0.4 and L = 10. Compare the performance of this chart to the one in Table 12.1 and Fig. 12.12. The following output was obtained from a computer program that performed a two-factor ANOVA on a factorial experiment. (a) Fill in the blanks in the ANOVA table. You can use bounds on the P-values. (b) How many levels were ...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 ...The data shown in Table 14E.5 were collected in an experiment to optimize crystal growth as a function of three variables x1, x2, and x3. Large values of y (yield in grams) are desirable. Fit a second-order model and analyze ...Post your question

0