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What is a DOE? Design of Experiment

What is a DOE? Design of Experiment. Adapted from http://www.moresteam.com/toolbox/design-of-experiments.cfm#preparation. Why Use It?.

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What is a DOE? Design of Experiment

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  1. What is a DOE?Design of Experiment Adapted from http://www.moresteam.com/toolbox/design-of-experiments.cfm#preparation

  2. Why Use It? • Experimental design can be used at the point of greatest leverage to reduce design costs by speeding up the design process, reducing design changes, and reducing product material and labor. • Designed Experiments are also powerful tools to achieve manufacturing cost savings by minimizing process variation and reducing rework, scrap, and the need for inspection.

  3. Intro • Controlled experiments are carried out in a systematic procedure to discover an unknown effect, to test or establish a hypothesis, or to illustrate a known effect.

  4. Intro Cont. • Experiments can be designed in many different ways to collect this information. Design of Experiments (DOE) is also referred to as Designed Experiments or Experimental Design - all of the terms have the same meaning.

  5. Intro Cont. • When analyzing a process, experiments are often used to evaluate which process inputs (variables) have a significant impact on the process output or outcomes, and what the target level of those inputs (variables) should be used to achieve a desired result (output).

  6. Components of the Experimental Design Factors = Variables Levels = Settings How much of each factor. Selections must be based on research. Response = results

  7. Components of Experimental Design Factors = variables Temp, sugar, flour, eggs Levels= settings How much of each factor Response = results How good is the cake?

  8. Sample Key

  9. Factors • or inputs to the process. • Factors can be classified as either controllable or uncontrollable variables. In this case, the controllable factors are the ingredients for the cake and the oven that the cake is baked in. • There could be other types of factors, such as the mixing method or tools, the sequence of mixing, or even the people involved. • People are generally considered a Noise Factor an uncontrollable which causes variability under normal conditions. • We try to account for this by randomization.

  10. Levels • or settings of each factor. • Examples include the oven temperature setting and the amounts of sugar, flour, and eggs. • You will conduct a review of literature on your topic that will allow you to select appropriate levels for your factors.

  11. Examples of Sources • Cook books • Culinary Schools • Professional Contacts • Grocery Store Cross Referencing

  12. Response or output of the experiment. In the case of cake baking, the taste, consistency, and appearance of the cake are measurable outcomes potentially influenced by the factors and their respective levels. Experimenters often desire to avoid optimizing the process for one response/result at the expense of another. For this reason, important outcomes are measured and analyzed to determine the factors and their settings that will provide the best overall outcome for the critical-to-quality characteristics - both measurable variables and assessable attributes.

  13. Purpose of Experimentation Comparing Alternatives: In the case of our cake-baking example, we might want to compare the results from two different types of flour. If it turned out that the flour from different vendors was not significant, we could select the lowest-cost vendor. If flour were significant, then we would select the best flour. The experiment(s) should allow us to make an informed decision that evaluates both quality and cost.

  14. Identifying the Significant Inputs (Factors) Affecting an Output (Response) – • separating the vital few from the trivial many. • We might ask a question: "What are the significant factors beyond flour, eggs, sugar and baking?“

  15. Experiment Design Guidelines The Design of an experiment addresses the questions outlined above by stipulating the following: • The factors to be tested. • The levels of those factors. • The structure and layout of experimental runs, or conditions. A well-designed experiment is as simple as possible - obtaining the required information in a cost effective and reproducible manner.

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