Interactive Data Mining Informs Designed Experiments

摘要

We illustrate how a Six Sigma project team can apply recursive partitioning to a historical data set to narrow down a list of potential experimental factors and then construct an experimental design using information from the partition analysis. The paper illustrates the value of analyzing historical manufacturing data to inform the choice of factors and levels for statistically designed experiments.