- TABLE 6E.2 Bearing Diameter Data Sample Number i Sample Number R 1 34.5 3 13 35.4 8. 2 34.2 4 14 34.0 6 3 31.6 4 15 37.1 5 4 31.5 4 16 34.9 7 5 35.0 5 17 33.5 4 34.1 6. 18 31.7 3 7 32.6 4 19 34.0 8....

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Extracted text: - TABLE 6E.2 Bearing Diameter Data Sample Number i Sample Number R 1 34.5 3 13 35.4 8. 2 34.2 4 14 34.0 6 3 31.6 4 15 37.1 5 4 31.5 4 16 34.9 7 5 35.0 5 17 33.5 4 34.1 6. 18 31.7 3 7 32.6 4 19 34.0 8. 8 33.8 3 20 35.1 4. 9. 34.8 7 21 33.7 2 10 33.6 8 22 32.8 1 11 31.9 3 23 33.5 3 12 38.6 9 24 34.2 2 inside diameter of the bearing, with only the last three decimals recorded (i.e., 34.5 should be 0.50345). (a) Set up ī and R charts on this process. Does the process seem to be in statistical control? If nec- essary, revise the trial control limits. (b) If specifications on this diameter are 0.5030 ± 0.0010, find the percentage of nonconforming bearings produced by this process. Assume that diameter is normally distributed.


Extracted text: 6.7. The data shown in Table 6E.2 are ī and R values for 24 samples of size n=5 taken from a process produc- ing bearings. The measurements are made on the