Design Of Experiment
Design Of Experiment
In this entry, we were given a case study and have been tasked to do data analysis and find out which factor has the most impact on the desired result.
Here is the Case Study that i chose:
Case Study 1 Excel File
Next i performed Full Fractional Analysis.
To perform Full Factorial Analysis, I used the data from the table above and created 3 different graph as seen below. This graph would show how each factor would perform and how each factor have a different significance in terms of affecting the mass of unpopped popcorns.
Hence, it can be concluded that the power has the most significant effect followed by microwaving time and the diameter of bowl in terms of yield of unpopped popcorn. To maximise the yield of popped popcorn, power and microwaving time should be set to a high configuration whereas diameter of bowl can be either high or low configuration because it will not have too much an impact on the yield.
Fractional Factorial:
Next, i performed Fractional Factorial design analysis based on runs#1,2,3,6 as seen in the table below:
With the data available, I obtained the graph as seen below:
In conclusion, it can be concluded that the power has the most significant effect followed by microwaving time and the diameter
of bowl in terms of yield of unpopped popcorn. To maximize the yield of popped popcorn, power and microwaving time should be
set to a high configuration whereas diameter of bowl can be either high or low configuration because it will not have too much
an impact on the yield.
In addition, it is better to use Full factorial data analysis rather than Fractional Factorial because with full factorial, it will be possible to see the types of interaction between factors unlike Fractional Factorial.
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