Once again we are here with a topic that is difficult for many Six Sigma Black Belt certificate applicants to master. This time it is Design of Experiments.
The objective of Design of Experiments (DOE) is to Establish optimal process performance by finding the right settings for key process input variables. Design of Experiments, of course, is a way to intelligently form frameworks to decide which course of action you might take. This is helpful when you are trying to either sort out what factors impact a process.
First, Start off with our Design of Experiments Factorial Design Overview.
Next, we must understand the type of factors that can affect an outcome so we can create the appropriate design to determine how to structure our experiment.
It’s also helpful to see an example of the kinds of Factors that are in an Experiment. These are our variables to the possible and desired outcomes.
Review the common terminology used in Design of Experiments Factorial Design.
Full Factorial Design is a thorough an exhaustive way of determining how each factor or combination of factors affects the outcome of an experiment.
Finally there is Partial (or Fractional) Factorial Design. Often doing a full factorial design analysis is impossible or impractical. Here’s how you can optimize your resources and still achieve a rigorously-supported decision.
Design of Experiments Video
Good overview here:
Six Sigma Black Belt Certification Design of Experiments Questions:
(A) miss interactions
(B) gain efficiencies
(C) save time
(D) cost less
Answer: (a) Miss Interactions. If you are only evaluating one variable at each time, you’ll never know if having multiple variables active lead to new effects. C& D is incorrect as OFAT can require many, many sets leading to exhaustive costs and lots of time. B is incorrect for the same reason.