Statistics Spotlight: Why Not Sequential DoEs?
Approach maximizes knowledge and avoids costly, wasteful mistakes
- Quality Progress
- November 2020
- Volume 53 Issue 11
- pp. 44-47
- Anderson-Cook, Christine M. , Lu, Lu
- Los Alamos National Laboratory, Los Alamos, NM, University of South Florida, Tampa, FL
Data collection is expensive, and time- and labor-intensive. The sequential approach to experimentation allows for maximal knowledge to be used to guide choices at each stage, which can help avoid costly and wasteful mistakes. It allows a calculated, thoughtful response to surprises—both good and bad. In addition, it helps to break the often- complicated designed experiment process into more manageable, easy-to-implement steps.