Design of Experiments (DOE)
Design of Experiments (DOE) provides a structured way to test multiple inputs simultaneously to understand what drives performance. It replaces trial-and-error with planned learning, enabling organisations to identify key effects and interactions and make evidence-based decisions about process optimisation.
Technique Overview
Design of Experiments (DOE) Definition
Design of Experiments (DOE) is a systematic method for planning, conducting, analysing and interpreting experiments in which input variables are deliberately varied to observe their effect on an output. By using factorial and related designs, DOE enables efficient estimation of main effects and interactions, supporting valid cause-and-effect conclusions (Fisher, 1971; Selvamuthu and Das, 2018; Antony, 2023).
Design of Experiments (DOE) Description *
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Business Evidence
Strengths, weaknesses and examples of Design of Experiments (DOE) *
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Business Application
Implementation, success factors and measures of Design of Experiments (DOE) *
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Professional Tools
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Further Reading
Design of Experiments (DOE) web and print resources *
Design of Experiments (DOE) references (4 of up to 20) *
- Antony, J., 2023. Design of experiments for engineers and scientists. 3rd ed. Elsevier.
- Antony, J., Coleman, S., Montgomery, D.C., Anderson, M.J. and Silvestrini, R.T., 2011. Design of experiments for non-manufacturing processes: benefits, challenges and some examples. Proceedings of the Institution of Mechanical Engineers, Part B, 225(11), pp.2078–2087. doi:10.1177/0954405410395857
- Fisher, R.A., 1966. The design of experiments. 8th ed. Reprinted 1971. New York: Hafner Publishing Company.
- Goh, T.N., 2002. The role of statistical design of experiments in six sigma: perspectives of a practitioner. Quality Engineering, 14(4), pp.659–671.
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