Step-by-Step Guide to DoE (Design of Experiments)

DOE or Design of experiments helps identify the various factors that affect the productivity and the outcomes of a particular process or a design. The individual influence of the factors as well as the interactive power of these factors to influence the outcome comes to light through an efficient design of experiment.
The trial and error approach of the past to consequently achieve the desired productivity and efficiency is obsolete. The sophisticated statistical approach taken by DOE makes it convenient for the businesses to design, conduct and analyze the experiments that can help multiply the output.
Here is a systematic, step-by-step guide to design a fruitful experiment.

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Set Objectives
Clearly defined goals and objectives of the experiment are important to get the intended answer. A comprehensive brain storming session or an interactive meeting can help the team prioritize the goals.
The type of design of the experiment depends heavily on your objectives.
Comparative Design: It lets you compare between two or more factors or effects to find out the one with the greatest impact.
Screening Design: It is vital when you are dealing with many factors and want to filter out a few important ones.
Response Surface Modeling: Typically employed when you want to maximize or minimize a response.
Regression Modeling: It is used to help figure out the degrees of dependence of a response on the factors.

Choose Your Variables
The next step is to shortlist your variables. Choose your input i.e. factors and your output i.e. responses carefully, as this will define the efficacy and usability of your experiment.
Setting the constraints or the range of the factors is vital. Two-level designs that involve a high and a low level for the factors seem to be the most efficient one, with +1 and -1 notations respectively.

Consider the Interactions
The greatest advantage of Design of Experiments over traditional experiments is its allowance of analyzing the synergized impacts of the various factors on the responses. When many factors are in play together, finding out the combinations of factors that manage to inflict the most affect is crucial.
The team needs to carefully prioritize the interactions they want to test. If you are using DOE software, it is best to run the experiment for all the possible interactions of factors.

Run the Experiment
Once you have decided upon the type of experiment and the most important input and output, it is time to simply run the experiment. Ensuring all the relevant data is accurate and in process, is vital to your results. Before running the experiment, go over the design one more time.
The team should come up with the minimum number of times to run the experiment to get any significant result. Run all the experiments with the same set of assumptions as well as factors and responses.

Analyze the Results
After the necessary runs of your experiment have been carried out, the next obvious step is the analysis of the data obtained because of the experiment. Graphs and diagrams can help you greatly assess the data.
Histograms, flowcharts as well as scatter diagrams can give an insight on the effects of various factors on different responses. Try to find correlations between input and output, the interactive impacts of the many factors as well as the magnitude of affects on the responses.
Simple and step-by-step approach to design of experiments efficiently lets you test out the different ways in to improve a particular process. The results and findings of an experiment allow you to make the necessary tweaks and adjustments in a system to improve the yield.

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