What is it: Design of Experiments (DOE) is a branch of applied statistics that deals with planning, conducting, analyzing and interpreting controlled tests to evaluate the factors that control the value of a parameter or group of parameters. Or is a structured, organized method for determining the relationship between factors (Xs) affecting a process and the output of that process. The major types of Designed Experiments available are:

• Full Factorials
• Fractional Factorials
• Screening Experiments
• Response Surface Analysis (RSA)
• EVOP
• Mixture Experiments.

In Manufacturing the Screening Experiment are commonly used. They screen the factors, or variables, in the process and determine which are the critical variables (Power factor) that affect the process output, before factorial anylsis can be completed.

Why use it: DOE provides a cost-effective means for solving problems and developing new processes. A well-performed experiment may provide answers to questions such as:

• What are the key factors in a process?
• At what settings would the process deliver acceptable performance?
• What are the key, main and interaction effects in the process?
• What settings would bring about less variation in the output?

Where to use it: DOE is a systematic approach to investigation of a system or process. A series of structured tests are designed in which planned changes are made to the input variables of a process or system. The effects of these changes on a pre-defined output are then assessed.

When to use it: To identify the most important variables in the process (called the power factors) and help determine the best settings for those variables.

How to use it: The order of tasks to using this tool starts with identifying the input variables and the response (output) that is to be measured. For each input variable, a number of levels are defined that represent the range for which the effect of that variable is desired to be known. An experimental plan is produced which tells the experimenter where to set each test parameter for each run of the test. The response is then measured for each run. The method of analysis is to look for differences between response (output) readings for different groups of the input changes. These differences are then attributed to the input variables acting alone (called a single effect) or in combination with another input variable (called an interaction).

Using DOE successfully depends on understanding eight fundamental concepts.

1. Set good objectives
2. Measure responses quantitatively
3. Replicate to dampen uncontrollable variation (noise)
4. Randomize the run order
5. Block out known sources of variation
6. Know which effects (if any) will be aliased
7. Do a sequential series of experiments
8. Always confirm critical findings

Important Notes: The planning phase is crucial A DOE effort will fail if not properly planned. The team or individual responsible for the experiment needs to take the time to think through the entire activity. Without good planning, the DOE might yield poor results or, even worse, lead to misleading conclusions. Select the correct design for the experimental objectives.

 Name Format Preview (Click to enlarge) Design of Experiment Instructions Adobe PDF Format Three Factor DOE Template Microsoft ExcelFormat Orthogonal Arrays Illustrations Adobe PDF Format
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