Design Of Experiment
In the Design Of Experiment (DOE) practical, we used a set of factors, arm length, stop angle, and projectile weight to find out which was the most important to the process of using a catapult to launch the projectile. DOE also allowed us to find out how we can optimise the process performance in a quick and cost-effective way.
LEARNING REFLECTION
Learning design of experiment has allowed me to approach experiments differently. It gives me a statistics based approach, a method to find out how each factor affects the dependent variable and a way to optimise the process. Doing the practical was really interesting. We were able to work with catapults and other equipments and collect our data. At the same time, we were able to see how each factor changed can affect the distance travelled by the ball.
There were times where we felt lost because we were still new to DOE back then. We had questions such as what is the high and low factor or maybe even how does factor A affect the dependent factor as not all our results were consistent. As a result, we had to compare out data with other groups occasionally.
During the challenge at the end of the practical, my group discovered that the rubber band used for our catapult was much weaker than the rest of the groups and the furthest distance we can reach is lesser than the furthest target. As such, we had to improvise. One method we used was to use two rubber bands instead of 1 for the catapult. This creates more power for the catapult. Another method we used was to put the catapult on the edge of the table. This allowed us to lauch the catapult further back, increasing the projectile distance travelled.
CASE STUDY
1. Diameters of bowls to contain the corn, 10cm and 15cm
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 experiments and the measured variable is the amount of "bullets" formed in grams and data collected are shown below.
Full Factorial data analysis
From the graph, we can see that factor A has the least significant effect on the mass of bullets produced , followed by factor B and then Factor C. This can be seen from the gradient of the lines whereby as each factor decreases from high to low, the mass of bullets produced will also increase accordingly.
Fractional Factorial analysis
For fractional factorial analysis, the same steps can be used, just that only 4 runs need to be used.
As the diameter decreases the mass of bullets produced decreases greatly. From the graph, we can see that factor A has the most significant effect on the mass of bullets produced due to the difference between its high and low points being the largest.
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