CP5070-2022-2B05-Group 3-Asraf-Blog 5 (DOE)
- Effect of single factors and their ranking
Factor A: Diameter of bowls to contain the corn. 10cm
and 15cm
Factor B: Microwaving time. 4 minutes and 6 minutes
Factor C: Power setting of microwave. 75% and 100%
The quantity of unpopped popcorn kernels, or "bullets," that stay at the bottom of the bag of popcorn is most significantly influenced by component C, followed by factor B and factor A.
This can be deduced from the gradients of each factor's linear graph since a higher gradient indicates a factor's greater significance in relation to the experimental outcomes. The linear equations shown on the graph can be used to derive these gradients.
Gradient of factor A: - 0.15
Gradient of factor B: - 0.79
Gradient of factor C: - 2.11
The gradients of the three elements are then seen to be all negative. This explains that a + (HIGH) value for all three parameters will lead to fewer bullets and, as a result, a larger yield of edible popcorn.
- Determine the interaction effects
(AxB)
At low B,
Average of LOW A = (0.74 +3.12)/2=1.93
Average of HIGH A = (3.66+0.95)/2=2.305
Total effect of A = 2.305-1.93=0.375 (Increase)
At HIGH B,
Average of LOW A = (2.66 + 0.66) / 2 = 1.66
Average of HIGH A = (1.66 + 0.32) / 2 = 0.99
Total effect of A = 0.99 - 1.66 = - 0.67 (Decrease)
Both lines have different gradients (one is +, the other is -). As a result, A and B have a considerable interaction.
(A x C)
At LOW C,
Average of LOW A = (2.66 + 3.12) / 2 = 2.89
Average of HIGH A = (3.66 + 1.35) / 2 = 2.505
Total effect of A = 2.505 - 2.89 = - 0.385 (Decrease)
At HIGH C,
Average of LOW A = (0.74 + 0.66) / 2 = 0.7
Average of HIGH A = (0.95 + 0.32) / 2 = 0.635
Total effect of A = 0.635 - 0.7 = -0.065 (Decrease)
Both lines have different gradients (one is +, the other is -). As a result, A and C have a considerable interaction.
(B x C)
At LOW C,
Average of LOW B = (3.66 + 3.12) / 2 = 3.39
Average of HIGH B = (2.66 + 1.66) / 2 = 2.16
Total effect of B = 2.16 - 3.39 = - 1.23 (Decrease)
At HIGH C,
Average of LOW B = (0.74 + 0.95) / 2 = 0.845
Average of HIGH B = (0.32 + 0.66) / 2 = 0.49
Total effect of B = 0.49 - 0.845 = - 0.355 (Decrease)
Both lines' gradients differ and have different values. As a result, although the interaction is minimal, B and C do interact. There will not be an interaction if the two lines are parallel.
- Tables and graphs and excel file
- Conclusion
The number of bullets is most significantly impacted by factor C (microwave power setting). Factor A (diameter of the bowl used to contain the corn) has the least significant effect on the number of bullets, whereas factor B (microwaving time) has a substantial effect.
The conclusion is that an. the + (HIGH) side, despite the fact that each factor's impact on the number of bullets varied.
Furthermore, there is a strong interaction between variables A and B. The same applies to factors A and C. The relationship between components B and C, however, is less significant.
FRACTIONAL FACTORIAL
- Effect of single factors and their ranking
Factor A: Diameter of bowls to contain the corn, 10 cm and 15 cmFactor B: Microwaving time, 4 minutes and 6 minutes
Factor C: Power setting of microwave, 75% and 100%
Four experimental runs with an equal amount of - (LOW) and + (HIGH) data for each factor are to be chosen to begin the fractional factorial data analysis. As a result, the data are balanced and orthogonal, which gives them favorable statistical qualities. Runs 2, 3, 4, and 5 were chosen as a result.
The quantity of unpopped popcorn kernels, or "bullets," that stay at the bottom of the bag of popcorn is significantly influenced by factors B and C, with factor A coming in third.
This can be deduced from the gradients of each factor's linear graph since a higher gradient indicates a factor's greater significance in relation to the experimental outcomes. These gradients can be obtained from the linear equations displayed on the graph.
Gradient of factor A: - 0.395
Gradient of factor B: 1.005
Gradient of factor C: - 1.005
Because the gradients of factors B and C are of equal magnitude, their effects on the number of bullets are equally important. Factor A has the lowest level of importance because it has the smallest gradient.
The gradients of factors A and C can thus be seen to be negative. This indicates that a + (HIGH) number will produce fewer bullets and, as a result, a larger yield of edible popcorn.
Contrarily, factor B has a positive gradient. This indicates that a + (HIGH) number will produce more bullets and, as a result, a lesser yield of edible popcorn.
- Tables and graphs and excel file
- Conclusion
Factor A (Diameter of the bowl used to contain the corn) has the least significant effect on the number of bullets, whereas factors B (Microwaving duration) and C (Power setting of the microwave) have the most effects.
The decrease in bullets and consequent rise in the output of palatable popcorn can be seen to follow an increase in factors A and C.
On the other side, an increase in factor B will lead to more bullets and a consequent decrease in the amount of consumable popcorn produced.
Therefore, factor A and C should be on the + (HIGH) side, while factor B should be on the - (LOW) side, to produce the best yield of popcorn. This goes against the result of the entire factorial data analysis, which states that for a larger yield of consumable popcorn, all components should be on the plus (HIGH) side.
This is due to the "less than full" nature of fractional factorial data analysis. There is a chance of missing information, yet it is more effective and efficient with resources. In order to still offer enough data to assess the factor effect, fewer treatments than all those that could be used are selected.
- Tutorial
Learning about DOE also enables us to comprehend how to design an experiment for research with changing parameter values.
I had always believed that settings were changed at random to achieve the best experimental outcome.
Without understanding about DOE, I would never have known how such experiments are planned or how to vary parameters so that an orthogonal balanced design is carried out with equal - (LOW) and + (HIGH) values of each parameter.
- Practical
I was given the job of conducting a straightforward experiment with my teammates during the practical session. This involves utilizing a ball and catapult to measure the distance the ball travels while using three distinct parameters at - (LOW) and + (HIGH) values. The three variables are the ball's weight, the catapult arm's length, and the angle at which the arm stops firing. The only issue is that we have to repeat the process eight times for each run, which is by far one of our largest issues. After compiling these results, we followed DOE's instructions to plot the necessary graphs in order to identify the most important factors that affected the experimental outcomes in what order. We also used fractional factorial, which required us to run the operation more frequently and so took longer.
But after completing the experiment and creating the excel spreadsheet, our final task is to use our catapult and the selected parameter to knock down the most lecturers. The top finisher will receive an additional mark. We totaled 4 runs and 3 shots. As we were evaluating the distance and angle, my squad did poorly on the first run. Because of the angle, we were frequently little short. But after that, we consistently knock Mr. Ting to the ground during the subsequent runs, and to be honest, I believe that is my class's objective—to knock Mr. Ting and Dr. Noel to the ground the most frequently among the other lecturers.
is a hands-on activity that teaches us not just the module content but also valuable life lessons. For example, my team initially gave up hope because we didn't knock anyone down during the first run, but we were able to rally as a team and finished in second place.
That's all for Blog 4, see you till the next blog. Have a great day ahead.
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