Abstract #300459

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JSM 2003 Abstract #300459
Activity Number: 456
Type: Invited
Date/Time: Thursday, August 7, 2003 : 10:30 AM to 12:20 PM
Sponsor: Section on Quality & Productivity
Abstract - #300459
Title: Modifying a Central Composite Design to Model the Process Mean and Variance within a Split-Plot Structure
Author(s): Scott M. Kowalski*+ and Geoff Vining and Douglas C. Montgomery
Companies: Minitab, Inc. and Virginia Polytechnic Institute and State University and Arizona State University
Address: 1611 Silk Tree Cir., Sanford, FL, 32773-8197,
Keywords: split-plot design ; central composite design ; robust parameter design
Abstract:

An important question within industrial statistics is how to find operating conditions that achieve some goal for the mean of a characteristic of interest while simultaneously minimizing the characteristic's process variance. Often, people refer to this kind of situation as the robust parameter design problem. The robust parameter design literature is rich with ways to create separate models for the mean and variance from this type of experiment. Many times time and/or cost constraints force certain factors of interest to be much harder to change than others. An appropriate approach to such an experiment restricts the randomization, which leads to a split-plot structure. This talk first establishes how one can modify the common central composite design to accommodate efficiently a split-plot structure. It then modifies this design to allow the estimation of separate models for the characteristic's mean and variance. The appropriate analysis of the experimental results will be discussed.

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Revised March 2003