Category: Design of Experiments (DOE)

Six Sigma projects in various industries often deal with experiments whose outcomes are not continuous variable data, but ordered categorical data. Analysis of variables (ANOVA) is a technique used to analyze continuous experimental data, but is not adequate for analyzing categorical experimental outcomes. Fortunately, many other methods have been developed to deal with categorical experiments, […]

Most Master Black Belts would probably cite design of experiments (DOE) as the most underused statistical tool in financial services. Yet, designed experiments are a favorite tool of statisticians and Six Sigma practitioners working in general business environments because they are an extremely efficient way of identifying what matters in a process and what does […]

For its Design for Six Sigma training course, one company sought a new, engaging way to teach DOE that was also budget friendly and provided consistent results. Solution: A toy motorcycle.

When it comes to mastering design of experiments, there can be a steep learning curve. Through a DOE simulation, trainees can get firsthand experience applying DOE concepts, learning how to set up the experimental design and how to interpret its results.

Each step of the DMAIC methodology brings a distinct set of tools to bear on the project objective. For the Analyze and Improve phases, design of experiments (DOE), combined with analysis of variance, is the Six Sigma power tool.