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Using response surface methodology to investigate bone china characteristics: (II) physical characteristics

Using response surface methodology to investigate bone china characteristics: (II) physical... This paper is in the following of our previous study about modeling of bone china optical properties as functions of feed composition. In the present study, the effect of feed composition on bone china physical characteristics such as bulk density, thermal expansion coefficient (TEC), and firing shrinkage by using response surface methodology (RSM) and MATLAB software was investigated. In this regard, based on batch calculation diagram, 13 feed compositions around commercial composition of bone china were chosen and investigated according to RSM methodology. Second-order polynomial equations were used to simulate these properties and RSM model validations showed the accuracy of the estimated models. Also, the similarity between surface plot areas and real changes during firing cycle showed that the models are trustable to predict these physical features. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of the Australian Ceramic Society Springer Journals

Using response surface methodology to investigate bone china characteristics: (II) physical characteristics

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Publisher
Springer Journals
Copyright
Copyright © 2017 by Australian Ceramic Society
Subject
Materials Science; Ceramics, Glass, Composites, Natural Materials; Materials Engineering; Inorganic Chemistry
ISSN
2510-1560
eISSN
2510-1579
DOI
10.1007/s41779-016-0018-2
Publisher site
See Article on Publisher Site

Abstract

This paper is in the following of our previous study about modeling of bone china optical properties as functions of feed composition. In the present study, the effect of feed composition on bone china physical characteristics such as bulk density, thermal expansion coefficient (TEC), and firing shrinkage by using response surface methodology (RSM) and MATLAB software was investigated. In this regard, based on batch calculation diagram, 13 feed compositions around commercial composition of bone china were chosen and investigated according to RSM methodology. Second-order polynomial equations were used to simulate these properties and RSM model validations showed the accuracy of the estimated models. Also, the similarity between surface plot areas and real changes during firing cycle showed that the models are trustable to predict these physical features.

Journal

Journal of the Australian Ceramic SocietySpringer Journals

Published: Jan 3, 2017

References