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Design of Experiment: Full Factorial design - Assignment Example

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This assignment tries to evaluate the time to mill a 90Kgs bag of corn using oil viscosity and power input. We subjected our data to a Statistical package Minitab and evaluated the data in a full-factorial design. We use a 2k or 2-Level Factorial design where k = 2…
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Design of Experiment: Full Factorial design
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The assignment "Design of Experiment: Full Factorial design" tries to evaluate the time to mill a 90Kgs bag of corn using oil viscosity and power input. We subjected our data to a Statistical package Minitab and evaluated the data in a full-factorial design. We use a 2k or 2-Level Factorial design where k = 2.A population N = 12 and a sampling technique of an exclusive mutual technique in stratified quota sampling was used, with a low oil viscosity, high oil viscosity, 220v and 240v power interacted to measure time used to mill one bag of 90kg corn.

Hence, an observation time method was used to record the results. The experiment uses a 90 Kg bag of corn on repetitive manner 12 runs of production. Blocking 1 is used to ensure that interaction between Oil viscosity and power factors is in assessing by the design module. This ensures that interaction between the oil viscosity and power is confounded. The experiment was conducted on single replicate of the time factor. Thus, Ho = rejected if p<.05 p= 0.015 as indicated in Table 1 ANOVA and F-test for time milling.

The two-way interaction indicates that the effects are non-significant at p < .05 in the coded coefficient Table 2. At predicted value time = 6.3. At 95%, CI the milling mean time falls within Plan B of High Viscosity and High voltage would fall between 5.7 to 7 minutes. The graph indicates that at 6.25 minutes to mill the 90kg bag of corn at high voltage and viscosity. We would recommend the use of Plan B of high viscosity and 240v.

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