Unmixed Milk Powder Experiment

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Introduction

I have been using milk powder daily in my morning tea and I find it annoying when I go through the whole process of making my tea just to realize the result is globs of unmixed milk powder. I decided to use a designed experiment in Minitab to help me reduce the residue of unmixed milk powder, and find the optimal settings of my input factors to produce a smooth and a creamy tea.

Choosing Input Factors for the Experiment
Because I am using premade milk powder, I decided to use two brands for the experiment. For this project, I’ll call the brands A and B. I suspect the temperature and mixing time to be the ones that impact the residue of unmixed milk powder. Therefore, the factors/inputs that I decided to use for the experiment are:
1.
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Milk powder brand: A or B (categorical data)
2. Temperature: 70 or 90 degrees Celsius (continuous data)
3. Mixing time: 3 or 5 minutes (continuous data)

Measuring the Response
To measure the residue of milk powder remaining in the experiment, I used a consistent weight of milk powder of 7 grams (in the same cup of size 1/16th) and mixed with 250ml of distilled water and after mixing, filter the residue and dry it in preheated oven at 80 degrees for 15 minutes and then measure the dry weight of the residue with an electronic scale.

Designing the Experiment
For this experiment, I decided to construct a 23 factorial design. I chose number of blocks to be one as I am going to finish the experiment in less than one day. Also chose one center point to allow for some diversity in the values. To create my design in Minitab, Click Stat > DOE > Factorial > Create Factorial Design:

And then decided on the number of factors and other

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