Journal of Materials Engineering and Performance, ( ISI ), Volume (23), No (11), Year (2014-11) , Pages (3975-3983)

Title : ( Process Control Strategies for Dual-Phase Steel Manufacturing Using ANN and ANFIS )

Authors: H. Vafaeenezhad , Sadegh Ghanei , S.H. Seyedein , Hossein Beygi Nasrabadi , Mohammad Mazinani ,

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Abstract

In this research, a comprehensive soft computational approach is presented for the analysis of the influencing parameters on manufacturing of dual-phase steels. A set of experimental data have been gathered to obtain the initial database used for the training and testing of both artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS). The parameters used in the strategy were intercritical annealing temperature, carbon content, and holding time which gives off martensite percentage as an output. A fraction of the data set was chosen to train both ANN and ANFIS, and the rest was put into practice to authenticate the act of the trained networks while seeing unseen data. To compare the obtained results, coefficient of determination and root mean squared error indexes were chosen. Using artificial intelligence methods, it is not necessary to consider and establish a preliminary mathematical model and formulate its affecting parameters on its definition. In conclusion, the martensite percentages corresponding to the manufacturing parameters can be determined prior to a production using these controlling algorithms. Although the results acquired from both ANN and ANFIS are very encouraging, the proposed ANFIS has enhanced performance over the ANN and takes better effect on cost-reduction profit.

Keywords

, adaptive neuro-fuzzy inference system, artificial neural networks, dual-phase steels, martensite, microstructure
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@article{paperid:1045209,
author = {H. Vafaeenezhad and Ghanei, Sadegh and S.H. Seyedein and Beygi Nasrabadi, Hossein and Mazinani, Mohammad},
title = {Process Control Strategies for Dual-Phase Steel Manufacturing Using ANN and ANFIS},
journal = {Journal of Materials Engineering and Performance},
year = {2014},
volume = {23},
number = {11},
month = {November},
issn = {1059-9495},
pages = {3975--3983},
numpages = {8},
keywords = {adaptive neuro-fuzzy inference system; artificial neural networks; dual-phase steels; martensite; microstructure},
}

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%0 Journal Article
%T Process Control Strategies for Dual-Phase Steel Manufacturing Using ANN and ANFIS
%A H. Vafaeenezhad
%A Ghanei, Sadegh
%A S.H. Seyedein
%A Beygi Nasrabadi, Hossein
%A Mazinani, Mohammad
%J Journal of Materials Engineering and Performance
%@ 1059-9495
%D 2014

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