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. 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. 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. 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. 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). 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 Factors (+) Values Standards (-) Values

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 Factors (-) Values Standards(+) Value Oven Temparture 150 150 °C 350 350 °C 450 450 °C Cups of Sugar ½ C 1 C 1 ½ c Number of Eggs 123

9. Factors or inputs to the process. 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. 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. 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. People are generally considered a Noise Factor an uncontrollable which causes variability under normal conditions. We try to account for this by randomization. We try to account for this by randomization.

10. Levels or settings of each factor. or settings of each factor. Examples include the oven temperature setting and the amounts of sugar, flour, and eggs. 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. 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 Cook books Culinary Schools Culinary Schools Professional Contacts Professional Contacts Grocery Store Cross Referencing 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. 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. 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. 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) – Identifying the Significant Inputs (Factors) Affecting an Output (Response) – separating the vital few from the trivial many. separating the vital few from the trivial many. We might ask a question: We might ask a question: "What are the significant factors beyond flour, eggs, sugar and baking?“ "What are the significant factors beyond flour, eggs, sugar and baking?“

15. Achieving an Optimal Process Output (Response). Achieving an Optimal Process Output (Response). "What are the necessary factors, and what are the levels of those factors, to achieve the exact taste and consistency of Mom's chocolate cake? Reducing Variability. Reducing Variability. "Can the recipe be changed so it is more likely to always come out the same?" "Can the recipe be changed so it is more likely to always come out the same?"

16. Minimizing, Maximizing, or Targeting an Output (Response). Minimizing, Maximizing, or Targeting an Output (Response). "How can the cake be made as moist as possible without disintegrating?" Improving process or product "Robustness" Improving process or product "Robustness" - fitness for use under varying conditions. "Can the factors and their levels (recipe) be modified so the cake will come out nearly the same no matter what type of oven is used?" "Can the factors and their levels (recipe) be modified so the cake will come out nearly the same no matter what type of oven is used?" Balancing Tradeoffs when there are multiple Critical to Quality Characteristics (CTQC's) that require optimization. Balancing Tradeoffs when there are multiple Critical to Quality Characteristics (CTQC's) that require optimization. "How do you produce the best tasting cake with the simplest recipe (least number of ingredients) and shortest baking time?" "How do you produce the best tasting cake with the simplest recipe (least number of ingredients) and shortest baking time?"

17. Experiment Design Guidelines The Design of an experiment addresses the questions outlined above by stipulating the following: The factors to be tested. The factors to be tested. The levels of those factors. The levels of those factors. The structure and layout of experimental runs, or conditions. 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.