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How to Institute DOE in Your Company by Davis Balestracci:
Design of Experiments (DoE) was developed by R.A. Fisher in the 1920s (related terms: factorial design, multivariate expertness). Six Sigma was the first general management approach that specifically highlighted the use of Designed Experiments for improvement. Still the use of factorial designed experiments is much less than it could be.
A Brief Overview of DOE from the Macomb Intermediate School District which has a high school course on the topic.
Design of Experiments can seem complicated but at the core it is fairly simple and powerful. By applying the proper techniques it allows you to gage the effect of several variables and, very importantly, the interactions of those variables with a small number of experiments (or tests or pilots).
George Box is a wonderful author (and friend) who can write for mangers who are not knowledgeable about statistics and statisticians. Statistics for Discovery does a good job of explaining how organizations should use experiments to improve.
While the adoption of DoE is still growing slowly, an increasing number of organizations are using DoE to improve. In the past most companies (in most industries anyway) did not have to compete with others that were using DoE to improve. But as more adopt DoE as one more tool to help increase the pace of improvement those that fail to take advantage of this tool will find themselves at a serious disadvantage.
Related links:
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November 3rd, 2007 at 11:29 am
[...] As I have said a number of times it is a powerful and under-utilized tool for improvement. Related: Using Design of Experiments - design of experiments articles - posts on public sector management - Why Use Designed Factorial [...]
February 4th, 2008 at 10:11 am
“Another difficulty in industrial experimentation is the existence of interactions. As has been stated, manufacturing processes are complex with many factors involved. In many processes these factors interact…”
June 29th, 2008 at 10:34 pm
“Kodak researchers use DOE to develop tests that examine first-order, second-order, and multiple factor effects simultaneously with relatively few simulation runs. The result is that the analyst can iterate to a globally optimized design with a far higher level of certainty and in much less time than the traditional approach…”
July 29th, 2008 at 1:31 pm
Some good resources for more on the topics discussed above: What Can You Find Out From 8 and 16 Experimental Runs? by George Box…