Question 2 A nickel-titanium alloy is used to make components for jet turbine aircraft engines. Cracking is a potentially serious problem in the final part because it can lead to nonrecoverable failure. A test is run at the parts producer to determine the effect of four factors on cracks. The four factors are: pouring temperature (A), titanium content (B), heat treatment method (C), amount of grain refiner used (D). Two replicates of a 24 design are run, and the length of crack (in mm x10-2) induced in a sample coupon subjected to a standard test is measured. The data are shown in Table 2. 1 (a) Estimate the factor effects. Which factor effects appear to be large? (b) Conduct an analysis of variance. Do any of the factors affect cracking? Use a = 0.05. (c) Write down a regression model that can be used to predict crack length as a function of the significant main effects and interactions you have identified in part (b). (d) Analyze the residuals from this experiment. (e) Is there an indication that any of the factors affect the variability in cracking? (f) What recommendations would you make regarding process operations? Use interaction and/or main effect plots to assist in drawing conclusions. Table 2: Crack Experiment for Exercise 2 A B C D Treatment Combination Replicate I II (1) 7.037 6.376 a 14.707 15.219 b 11.635 12.089 ab 17.273 17.815 с 10.403 10.151 ас 4.368 4.098 bc 9.360 9.253 abc 13.440 12.923 d 8.561 8.951 ad 16.867 17.052 bd 13.876 13.658 abd 19.824 19.639 cd 11.846 12.337 acd 6.125 5.904 bcd 11.190 10.935 abcd 15.653 15.053
Question 2 A nickel-titanium alloy is used to make components for jet turbine aircraft engines. Cracking is a potentially serious problem in the final part because it can lead to nonrecoverable failure. A test is run at the parts producer to determine the effect of four factors on cracks. The four factors are: pouring temperature (A), titanium content (B), heat treatment method (C), amount of grain refiner used (D). Two replicates of a 24 design are run, and the length of crack (in mm x10-2) induced in a sample coupon subjected to a standard test is measured. The data are shown in Table 2. 1 (a) Estimate the factor effects. Which factor effects appear to be large? (b) Conduct an analysis of variance. Do any of the factors affect cracking? Use a = 0.05. (c) Write down a regression model that can be used to predict crack length as a function of the significant main effects and interactions you have identified in part (b). (d) Analyze the residuals from this experiment. (e) Is there an indication that any of the factors affect the variability in cracking? (f) What recommendations would you make regarding process operations? Use interaction and/or main effect plots to assist in drawing conclusions. Table 2: Crack Experiment for Exercise 2 A B C D Treatment Combination Replicate I II (1) 7.037 6.376 a 14.707 15.219 b 11.635 12.089 ab 17.273 17.815 с 10.403 10.151 ас 4.368 4.098 bc 9.360 9.253 abc 13.440 12.923 d 8.561 8.951 ad 16.867 17.052 bd 13.876 13.658 abd 19.824 19.639 cd 11.846 12.337 acd 6.125 5.904 bcd 11.190 10.935 abcd 15.653 15.053
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Transcribed Image Text:Question 2
A nickel-titanium alloy is used to make components for jet turbine aircraft engines. Cracking is a potentially
serious problem in the final part because it can lead to nonrecoverable failure. A test is run at the parts producer
to determine the effect of four factors on cracks. The four factors are: pouring temperature (A), titanium content
(B), heat treatment method (C), amount of grain refiner used (D). Two replicates of a 24 design are run, and
the length of crack (in mm x10-2) induced in a sample coupon subjected to a standard test is measured. The
data are shown in Table 2.
1
(a) Estimate the factor effects. Which factor effects appear to be large?
(b) Conduct an analysis of variance. Do any of the factors affect cracking? Use a = 0.05.
(c) Write down a regression model that can be used to predict crack length as a function of the significant
main effects and interactions you have identified in part (b).
(d) Analyze the residuals from this experiment.
(e) Is there an indication that any of the factors affect the variability in cracking?
(f) What recommendations would you make regarding process operations? Use interaction and/or main effect
plots to assist in drawing conclusions.
Table 2: Crack Experiment for Exercise 2
A B C D Treatment Combination
Replicate
I
II
(1)
7.037
6.376
a
14.707 15.219
b
11.635 12.089
ab
17.273 17.815
с
10.403 10.151
ас
4.368
4.098
bc
9.360
9.253
abc
13.440
12.923
d
8.561
8.951
ad
16.867 17.052
bd
13.876 13.658
abd
19.824 19.639
cd
11.846 12.337
acd
6.125 5.904
bcd
11.190 10.935
abcd
15.653 15.053
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