Please use this identifier to cite or link to this item:
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. 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 using Matlab toolbox functions. Data set required to train the models are obtained through finite element simulation. Results from the fuzzy model are compared with the developed artificial neural network model, and these models are also validated.
Page(s): 351-360
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.