Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/2094
Title: DOE and ANN models for powder mixture packing
Authors: Akkurt, Sedat
Romagnoli, Marcello
Sütçü, Mücahit
Keywords: Design of experiments
Artificial neural networks
Alumina powder compact
Sensitivity analysis
Issue Date: Jul-2007
Publisher: American Ceramic Society
Source: Akkurt, S., Romagnoli, M., and Sütçü, M. (2007). DOE and ANN models for powder mixture packing. American Ceramic Society Bulletin, 86(7), 9101-9111.
Abstract: Design of experiments (DOE) and artificial neural network (ANN) techniques were used to study packing of fused alumina powders composed of three different sizes of particles. The first is the mixture design technique that produces a polynomial model of the powder-packing system. While, the ANN technique is extensively used to model complex systems in many fields. The methodological approach used is mixture design, which can be used to study the influences of two or more additives. It is a structured and organized method for determining the relationship between the components and the output of that process. The mixture design approach permits optimization of size distribution to obtain a target value of porosity. Sensitivity analysis involves the use of the developed ANN model to predict outputs (porosity) at varying levels of the input factor effects.
URI: http://hdl.handle.net/11147/2094
ISSN: 0002-7812
0002-7812
Appears in Collections:Mechanical Engineering / Makina Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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