High Level Plan Develop a quantitative analysis of the sensitivity of the factors in relation to the response. Using Minitab a regression equation was formulated in order to determine the sensitivity of each factor. This equation takes into consideration the sensitivity of each factor in relation to tension as a response. Force = 55.4 + 2.89 WindSpeed - 1.86 Radius - 0.169 Beta + 1.11 TethLen Detailed analysis A regression equation was developed and reiterated to remove unusual observations and close the gap of the prediction interval. The issue with this regression was that there is no constant mean of zero (Figure 2); hence the value is extremely low. However, the significance of each factor can be checked when P stat is compared at an alpha of 0.05. This comparison leads to Wind speed, Flight Path Radius and Tether Length being highly significant. We concluded to important outcomes, which were that these factors are very sensitive to tension and would still consider the Beta angle sensitive because it is a factor when flying and testing the glider. The following equation displays the sensitivity of each factor in relation to response Force = 55.4 + 2.89 WindSpeed - 1.86 Radius - 0.169 Beta + 1.11 TethLen Figure represents the versus fit of regression model The output analysis displayed a very low R-square value (8.0 %) because of so much variation (Figure 2) between response values. However, when observing the value of the Analysis of Variance output of DOE, the value is significantly high (82.14 %) to conclude that it is a valid experiment because in this scenario Minitab uses the effect of blocking into the experiment. Blocking is a technique in which the user is able to take the effect of an uncontrollable factor into consideration. So a slight change of wind speed that affects the regression line significantly will not affect the DOE analysis.
High Level Plan Develop a quantitative analysis of the sensitivity of the factors in relation to the response. Using Minitab a regression equation was formulated in order to determine the sensitivity of each factor. This equation takes into consideration the sensitivity of each factor in relation to tension as a response. Force = 55.4 + 2.89 WindSpeed - 1.86 Radius - 0.169 Beta + 1.11 TethLen Detailed analysis A regression equation was developed and reiterated to remove unusual observations and close the gap of the prediction interval. The issue with this regression was that there is no constant mean of zero (Figure 2); hence the value is extremely low. However, the significance of each factor can be checked when P stat is compared at an alpha of 0.05. This comparison leads to Wind speed, Flight Path Radius and Tether Length being highly significant. We concluded to important outcomes, which were that these factors are very sensitive to tension and would still consider the Beta angle sensitive because it is a factor when flying and testing the glider. The following equation displays the sensitivity of each factor in relation to response Force = 55.4 + 2.89 WindSpeed - 1.86 Radius - 0.169 Beta + 1.11 TethLen Figure represents the versus fit of regression model The output analysis displayed a very low R-square value (8.0 %) because of so much variation (Figure 2) between response values. However, when observing the value of the Analysis of Variance output of DOE, the value is significantly high (82.14 %) to conclude that it is a valid experiment because in this scenario Minitab uses the effect of blocking into the experiment. Blocking is a technique in which the user is able to take the effect of an uncontrollable factor into consideration. So a slight change of wind speed that affects the regression line significantly will not affect the DOE analysis.
DOE%20experiment%201.1.docx