Experiment At The Run Order Or Not

1301 WordsJun 30, 20166 Pages
6. Performing the Experiment: While performing the experiment we have to be careful whether we are performing the experiment according to the run order or not. In order to avoid the error, we rechecked the settings for every run and then we performed that run. To run the experiment effectively, we ran some trial runs such that we got an idea of how to perform the experiment and how to take the readings minimizing the errors. After performing the experiment, the values were recorded in the table, obtained from Minitab as shown below. Table 6.1: Response values of the experiment. Standard Order A B C D E Response (cm) 3 -1 1 -1 -1 -1 108 17 0 0 0 0 0 310 18 0 0 0 0 0 322 2 1 -1 -1 -1 -1 50 14 1 -1 1 1 -1 90 10 1 -1 -1 1 1 516 6 1 -1 1 -1 1…show more content…
Table 7.1: Analysis of Variance result. Source Degrees of Freedom Sum of Squares Mean square F value P value Model 16 1138506 94600 467.37 0.000 Linear 5 1038812 207762 1364.61 0.000 Factor A 1 2401 2401 15.77 0.029 Factor B 1 16002 16002 105.11 0.002 Factor C 1 48620 48620 319.34 0.000 Factor D 1 47306 47306 310.71 0.000 Factor E 1 924482 924482 6072.13 0.000 Interaction AB 1 3422 3422 22.48 0.018 Interaction AC 1 930 930 6.11 0.090 Interaction AD 1 1260 1260 8.28 0.064 Interaction AE 1 756 756 4.97 0.112 Interaction BC 1 361 361 2.37 0.221 Interaction BD 1 2304 2304 15.13 0.030 Interaction BE 1 4356 4356 28.61 0.013 Interaction CD 1 6084 6084 39.96 0.008 Interaction CE 1 25281 25281 166.05 0.001 Interaction DE 1 54289 54289 356.58 0.000 Curvature 1 650 650 4.27 0.131 Error 3 457 152 Total 19 1138963 From the Table 7.1, it was observed that the curvature was non-significant as its p value was greater than the alpha value (α = 0.05). Now, we have two procedures to follow one is steepest ascent method and another is differentiating the regression equation with respect to the factors and equating them to zero gives us the values of each factor. The regression equation was obtained from the coded coefficients table and was written below. In the regression equation, only the significant factors were considered and those factors were filtered using ANOVA result and Half normal plot. Response = 326 – 12.25A+ 31.62B
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