Design Of Experiments (DOE)
Master the design of experiments (DOE) to reach the optimum output of any process or product
What you will learn
Design experiments to optimise any process, machines, or products
Define the most influencing factors on the process and the interaction between these factors
Learn the required statistical background needed for DOE
Learn how to use the state of the art software to implement DOE
Why take this course?
What is DOE and what are it's benefits?
Let us assume that you are an owner of a pizza restaurant and of course you want to make the tastiest pizza, not in the world, let us be realistic, in your town. The quality of the pizza has a lot of factors, the pizza dough (flour, yeast and salt), the filling (sauce and cheese), also the oven temperature, the time in the oven and some other factors too. We will focus in our example on the recipe of the pizza dough. So we have the factors: x1 the amount of flour in gram, x2 the amount of yeast in gram and x3 the amount of salt in gram. The output is the taste of the pizza, let us say we have a taste expert, who judges the quality of the dough on a scale of 1 to 10, with 10 being best. *fig 2*.
By using the design of experiments method we can know:
Which of the factors (flour, yeast, or salt) affect the taste.
Which of those factors has the highest effect
If the interaction between the examined factors affects the quality of the dough. In other words, if we change for example the amount of the yeast, should we also have to change at the same time the amount of the flour to keep the taste at its desired level.
What is the best amount of grams for every factor to reach the best taste
And finally, we can predict what the taste would be, in case we change one factor or more. For example, if we mixed 600 g flour with 40 g yeast with 4 g salt, we can predict from this combination of values, what would be the taste of our dough
Doe is a method to plan an Experiment and then evaluate this experiment with statistical analysis.
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