Introduction to Statistical Quality Control
7th Edition
ISBN: 9781118146811
Author: Montgomery, Douglas C.
Publisher: John Wiley & Sons Inc
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Chapter 4, Problem 42E
An article in the Journal of the Electrochemical Society (Vol. 139, No. 2, 1992, pp. 524–532) describes an experiment to investigate the low-pressure vapour deposition of polysilicon. The experiment was carried out in a large-capacity reactor at SEMATECH in Austin, Texas. The reactor has several wafer positions, and four of these positions are selected at random. The response variable is film thickness uniformity. Three replicates of the experiment were run, and the data are shown in Table 4E.8.
- (a) Is there a difference in the wafer positions? Use the analysis of variance and α = 0.05.
- (b) Estimate the variability due to wafer positions.
- (c) Estimate the random error component.
- (d) Analyze the residuals from this experiment and comment on model adequacy.
TABLE 4E.8
Uniformity Data for the Experiment in Exercise 4.42
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An article in the Journal of the Electrochemical Society (Vol. 139, No. 2, 1992, pp. 524–532) describes anexperiment to investigate the low-pressure vapor deposition of polysilicon. The experiment was carried outin a large-capacity reactor at Sematech in Austin, Texas. The reactor has several wafer positions, and fourof these positions are selected at random. The response variable is film thickness uniformity. Threereplicates of the experiment were run, and the data are as follows:a. Test the significance of these wafer position with α=0.05.b. If proven significant, perform a multiple comparison method using Fisher’s LSD.
In Applied Spectroscopy, the infrared reflectance spectra properties of a viscous liquid used in the
electronics industry as a lubricant were studied. The designed experiment consisted of the effect
of band frequency x1 and film thickness x2 on optical density y using a Perkin-Elmer Model 621
infrared spectrometer. (Source: Pacansky, J., England, C. D., and Wattman, R., 1986.) y.
Q4.
0.231
740
1.10
0.107
0.053
0.129
0.069
0.030
1.005
0.559
0.321
2.948
1.633
0.934
740
740
SO5
805
805
0.62
0.31
1.10
0.62
0.31
1.10
0.62
0.31
1.10
0.62
980
980
980
1235
1235
1235
0.31
Estimate the multiple linear regression equation.
Chapter 4 Solutions
Introduction to Statistical Quality Control
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