DOE Case Study
Hello everyone! Welcome back to my 4 th blog entry! In this blog entry, I will be discussing about the topic of Design of Experiment (DOE) and what I have learnt about it. This blog entry contains a full factorial and fractional factorial analysis for a given case study on ESP Brightspace, followed by a learning reflection of my tutorial and practical sessions. FULL FACTORIAL Data Analysis Effect of each factor & their rankings Factor A: Diameter of bowls to contain the corn, 10 cm and 15 cm Factor B: Microwaving time, 4 minutes and 6 minutes Factor C: Power setting of microwave, 75% and 100% The most impactful factor which affected the number of inedible “bullets” (un-popped kernels) is factor C, followed by factor B and lastly, factor A. This result is obtained from each factor’s gradient on a linear graph. The gradient of a factor will determine the significance of the factor’s impact on the result, i.e. a higher magnitude will re