DOE Minitab. You are a consultant in the design of experiments for a chemical process company. One of the processes requires reaching and maintaining the temperature at which one of the company's processes is carried out, between 600 and 700 °F. To achieve this objective, the appropriate combination of five variables that affect temperature must be achieved: MgBr concentration (A); Oxygen rate (B); Nitrogen level (C); Ionization rate (D); and concentration of NaCl2 (E).
To achieve the desired combination, you propose to carry out three runs of a 2^5 factorial design. Since your proposal would entail a high cost for the company, you are authorized to carry out a 2^5-1 design with two replicates. The results are the following:
Factors
Temperature
A
B
C
D
E
Replica 1
Replica 2
Treatment
MgBr
Oxygen
Nitrogen
Ionization
NaCl2
Y1
Y2
1
20
1
200
5
0.9
765.9
768.7
2
20
1
200
10
0.1
243.6
234.1
3
20
1
500
5
0.1
495.1
593.5
4
20
1
500
10
0.9
518.3
456.4
5
20
10
200
5
0.1
505.4
522.9
6
20
10
200
10
0.9
487.9
498.6
7
20
10
500
5
0.9
768.0
702.8
8
20
10
500
10
0.1
296.7
271.7
9
80
1
200
5
0.1
635.3
622.8
10
80
1
200
10
0.9
387.0
380.9
11
80
1
500
5
0.9
676.3
680.0
12
80
1
500
10
0.1
366.1
325.4
13
80
10
200
5
0.9
640.1
650.7
14
80
10
200
10
0.1
357.3
347.2
15
80
10
500
5
0.1
526.8
527.4
16
80
10
500
10
0.9
419.9
411.0
a) Estimate the effects of the factors. What effects appear to be great?
b) Perform the analysis of variance to confirm your conclusions for part (a).
c) What is the equation to predict the temperature based on the results of this experiment? How good is this model? (hint: check model assumptions)
d) What levels of the factors (both significant and non-significant, if any) included in your model would you recommend using to achieve the objective? (hint: perform optimization)