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2007.201: Tailor-made split-plot designs for mixture and process variables

2007.201: Peter Goos and Alex Donev (2007) Tailor-made split-plot designs for mixture and process variables. Journal of Quality Technology, 39 (4). pp. 326-339. ISSN 0020-0255

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Official URL: http://proquest.umi.com/pqdweb?did=1368173061&sid=1&Fmt=2&clientId=44986&RQT=309&VName=PQD

Abstract

The design of efficient small experiments involving mixture variables and process variables is a difficult problem. An additional complication is that such experiments are often conducted using split-plot designs and therefore lead to correlated observations. The present article demonstrates how algorithmic search can be used for constructing efficient tailor-made split-plot mixture-process variable designs, when there may be constraints on the mixture components. The D-optimality criterion is used as the main design criterion. The article also shows how to construct efficient split-plot mixture-process variable designs when replication is required for independently estimating the variance components in the split-plot model. It is argued that it is better to spread the replications over different points of the design than to concentrate them in the center.

Item Type:Article
Uncontrolled Keywords:A-Optimality; D-Optimality; G-Optimality; Mixture Experiment; Pure Error Estimation; Replication; Response-Surface Designs, Split-Plot Experiment; V-Optimality.
Subjects:MSC 2000 > 62 Statistics
MIMS number:2007.201
Deposited By:Mrs Louise Healey
Deposited On:21 November 2007

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