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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 |
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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