Analysis of Unreplicated Split-Plot Experiments with Multiple Responses

Abstract

The purpose of this study is to demonstrate an effective strategy for analyzing unreplicated split-plot experiments with multiple responses. Through principal component analysis (PCA) the response variables are reduced to only those that describe different phenomena among the experimental samples. These selected response variables are then analyzed individually using ANOVA and Normal probability plots to identify the factors with the greatest influence on the quality and cost of the product. This approach makes it possible to take both the preferred quality characteristics and the production costs into account when studying a process or product. A case study from a fish food manufacturing company is used to illustrate our ideas.