24 Run Split-Plot Experiments for Robust Parameter Design

Abstract

Split-plot experiments where the whole plot treatments and the subplot treatments are made up of combinations of two-level factors are considered. Often in industry, due to time and/or cost constraints, the size of an experiment needs to be kept small. Sometimes these experiments involve noise factors and design factors and can be thought of as robust parameter designs. Using fractional factorials and confounding, a method for constructing sixteen run designs is presented. Semifolding is used to add eight more runs. The resulting 24 run design breaks some of the alias chains and provides some degrees of freedom for estimating a subplot error variance. Also, an alternative 24 run design based on the balanced incomplete block design is presented.

• Aliasing
• Design of Experiments
• Fractional Factorials
• Split-Plot Experiments

Additional information

Notes on contributors

Scott M. Kowalski

Dr. Kowalski is a Technical Trainer. He is a Member of ASQ. His email address is [email protected].