Design of Experiment
Design of Experiment case studies:
In this case study that I am doing with my associate (Andrew),
we role-played as the CEO (team leader) and CFO (Chief Financial Officer) to find
the ranking of the factors that affected the number of inedible unpopped kernels
that remained in popcorn.
3 factors were identified, namely:
1. Diameter of bowls to contain the corn, 10 cm and 15 cm.
2. Microwaving time, 4 minutes and 6 minutes.
3. Power setting of microwave, 75% and 100%.
8 runs were performed with 100 grams of corn used in every experiment
and the measured variable is the amount of “bullets” formed in grams and data
collected are shown below. This data will be used for full factorial data
analysis.
|
Run order |
A |
B |
C |
Bullets (grams) |
|
1 |
+ |
- |
- |
3.5 |
|
2 |
- |
+ |
- |
1.6 |
|
3 |
- |
- |
+ |
0.7 |
|
4 |
+ |
+ |
- |
1.2 |
|
5 |
+ |
- |
+ |
0.7 |
|
6 |
+ |
+ |
+ |
0.3 |
|
7 |
- |
+ |
+ |
0.5 |
|
8 |
- |
- |
- |
3.1 |
I have sorted the data into their respective run orders in this table below as shown in excel:
Factor A was the Diameter of bowls to contain the
corn, 10 cm and 15 cm.
Factor B was the Microwaving time, 4 minutes and 6 minutes.
Factor C was the Power setting of microwave, 75% and 100%.
After tabulating all the results into the excel table as seen above, I have acquired the data plots for the average weight of the bullets for high and low levels of the corresponding factors. The graph obtained is shown below:
Effects of factor C is the greatest, followed by B and
lastly A.
Interaction effects of each factor:
I have deduced that the weight of bullets is affected the greatest
due to change of level of factor C, followed by factor B, and lastly factor A.
Conclusion of the data analysis
When the power setting of the microwave is at 75%, there is
a greater number of inedible unpopped kernels.
When the microwaving time is at 4 minutes, there is a greater number of
inedible unpopped kernels.
When the Diameter of bowls to contain the corn is 10 cm, there is a greater
number of inedible unpopped kernels.
To use subsequent data for fractional factorial data
analysis, I will be using runs 1, 2, 3 and 6. The sorted data in their
respective run order is in this table below as shown in excel:
Interaction effects of each factor:
I have deduced that the weight of bullets is affected the greatest
due to change of level of factor C, followed by factor B, and lastly factor A.
Conclusion of the data analysis
When the power setting of the microwave is at 75%, there is
a greater number of inedible unpopped kernels.
When the microwaving time is at 4 minutes, there is a greater number of
inedible unpopped kernels.
When the Diameter of bowls to contain the corn is 10 cm, there is a smaller
number of inedible unpopped kernels.
The data file for the fractional factorial data analysis can
be found in the link below:
The data file for the full factorial data analysis can be
found in the link below:
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