【正文】 t Data Means for Liters Per HFormulation 1 Has Lowest Fuel Consumption DESIGN OF EXPERIMENTS (DOE) FUNDAMENTALS First Create an Experimental Design... Go to ?Stat… ?DOE… ?Factorial... ?Create Factorial Design... First Create an Experimental Design... Select 2 Level Factorial design with 3 factors Then go to Display Available Designs…. Bowling Example (continued) We can now see the available experimental designs…. We will be using the Full (Factorial) for 3 factors and we can see that it will require 8 runs… Now, select OK and go back to the main screen. Once at the main screen select Designs... Bowling Example (continued) Select your design…. We will be using the Full (Factorial) and again we can see that it will require 8 runs… Now, select OK and go back to the main screen. Once at the main screen select Factors... Bowling Example (continued) Fill in the names for your factors…. Then fill in the actual conditions for low () or high (+) Now, select OK and go back to the main screen. Once at the main screen select Options... Bowling Example (continued) Remove the option to Randomize Runs…. Now, select OK and go back to the main screen. Once at the main screen select OK... Bowling Example (continued) Minitab has now designed our experiment for us…. Now, type your Data from each of your experimental treatments into C8. We are now ready to analyze the results… Bowling Example (continued) Go to ?Stat…. ?DOE… ?Factorial... ?Analyze Factorial Design... Bowling Example (continued) Highlight your Data column and use Select to place it in the Responses box. Then, select the Terms Option. Bowling Example (continued) Note that Selected Terms has all of the available choices already selected. We need do nothing further. Select OK. Then, at the main screen select Graphs Bowling Example (continued) Select your Effects Plots and reset your Alpha to .05. Select OK to return to the main screen and then select OK again. Bowling Example (continued) Note that only one effect has a significance greater than 95%. All the remaining factors and interactions are not statistically significant. Bowling Example (continued) ?Another way we can look at the data is to look at the Factorial Plots of the resulting data. ?Go to ?DOE…. ?Factorial… ?Factorial Plots…. Bowling Example (continued) ?Select Main Effects Plot and then Setup… Bowling Example (continued) ?Select C8 as your response ?Select “Wristband”, “Ball” and “Lane” as your factors. ?Then select “OK” and OK again on the main screen. Bowling Example (continued) ?The magnitude of the vertical displacement indicates the strength of the main effect for that factor. Here we see that the wristband has dramatically more effect than any other factor. We know from our earlier plots that the wristband is the only statistically significant effect 95% confidence. ?This plot also shows you the direction of the main effects. We clearly see that the “with” condition is related to the higher level of performance. Bowling Example (continued) ?Now lets look at the interactions.... ?Go to ?DOE…. ?Factorial… ?Factorial Plots… Bowling Example (continued) ?Select InteractionPlot and then Setup….. Bowling Example (continued) ?Select C8 as your response variable. ?Select “Wristband”, “Ball” and “Lane” as your factors. ?Then select “OK” and OK again on the next screen…. Bowling Example (continued) ?The more the lines diverge from being parallel, the more the interaction. ?We see that the strongest interaction (still not significant) is between the lane and the ball. ?We know from our earlier analysis that none of these interactions were statistically significant for this experiment….. Bowling Example (Session Window) ?You can also see that there is zero error ?This is because only 1 run was performed with no replications ?This is where Minitab shows us the Main Effects and Interaction Effects.. ?Note that Wristband has the strongest effect followed by the interaction between the Wristband and the Lane... 演講完畢，謝謝觀看！