In general usage, design of experiments (DOE) or experimental design is the design of any information-gathering exercises where variation is present, whether under the full control of the experimenter or not.
However in statistics these terms are usually used for controlled experiments.
In the design of experiments, the experimenter is often interested in the effect of some process or intervention (the factor / treatment) on some objects (the experimental units).
Design of experiments is thus a discipline that has very broad applications across all the natural and social sciences and engineering, and is a statistically based approach.

History of Design of Experiment (DOE)

Back in the 1920’s a methodology for design of experiments was proposed by Ronald A Fisher. He developed the methods of design of experiments to study the effects of different fertilizers, soils, etc., on crop yields.
As an example he described how to test the hypothesis that a person could distinguish by flavour alone whether the milk or the tea was first placed into the cup. This experiment allowed him to illustrate the most important ideas of experimental design.
The language of design of experiments comes from agricultural origins e.g. treatments, blocks and plots etc.

Aim of Design of Experiment (DOE)

Set up experiments in a way that the results can be analysed by either the analysis of variance techniques or non-parametric methods without making false assumptions.

Purpose of Design of Experiment (DOE)

Designed experiments consist of a series of runs or tests in which:

  • Input variables (factors) of a process are simultaneously changed.
  • Responses are observed.
    • Designed experiments are more efficient than the one factor at a time approach. You can change multiple factors.
    • Experimental Design is commonly an iterative approach.
    • Rarely does one run a large comprehensive design in which final conclusions are made.
    • Without properly designed experiments the effects of the interactions are often overlooked.
    • A tool that allows you to experiment on many factors simultaneously.

Applications of Design of Experiment (DOE)

Use designed experiments to:

  • Determine which factors have a significant effect on a response.
  • Identify the effect of an interaction between two factors.
  • Optimize process performance.
  • Reduce development time for new products.
  • Reduce variation in the process.
  • Determine optimal settings of factors.

If you are interested in DOE, then our 8D Problem Solving Training might be interesting for you.
It is a detailed training on how to effectively solve problems and prevent them from reoccurring, and cover the use of DOE as part of the training.

Alternatively please contact us if interested in a comprehensive training on DOE or continue to our quality training page for an overview of the training we provide.

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Design of Experiment