Please use this identifier to cite or link to this item: http://nopr.niscair.res.in/handle/123456789/13241
Title: Weld residual stress prediction using artificial neural network and Fuzzy logic modeling
Authors: Dhas, J Edwin Raja
Kumanan, Somasundaram
Keywords: Weld residual stress
Artificial neural network
Fuzzy logic
Finite element analysis
Issue Date: Oct-2011
Publisher: NISCAIR-CSIR, India
Abstract: intelligent tools such as expert systems, artificial neural network and fuzzy logic support decision-making are being used in intelligent manufacturing systems. Success of intelligent manufacturing systems depends on effective and efficient utilization of intelligent tools. <span style="mso-bidi-font-weight:bold">Weld residual stress depends on different process parameters and its prediction and control is a challenge to the researchers. In this paper, intelligent predictive techniques artificial neural network (ANN) and fuzzy logic models are developed for weld residual stress prediction. The models are developed<span style="mso-bidi-font-weight:bold"> using Matlab toolbox functions<span style="mso-bidi-font-weight:bold">. Data set required to train the models are obtained through finite element simulation. Results from the fuzzy model are compared with the developed <span style="mso-bidi-font-weight: bold">artificial neural network model, and these models are also validated. </span></span></span></span>
Description: 351-360
URI: http://hdl.handle.net/123456789/13241
ISSN: 0975-1017 (Online); 0971-4588 (Print)
Appears in Collections:IJEMS Vol.18(5) [October 2011]

Files in This Item:
File Description SizeFormat 
IJEMS 18(5) 351-360.pdf1.55 MBAdobe PDFView/Open


Items in NOPR are protected by copyright, with all rights reserved, unless otherwise indicated.