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Title: ANFIS for prediction of weld bead width in a submerged arc welding process
Authors: Dhas, J Edwin Raja
Kumanan, S
Keywords: ANFIS
Bead width
Multiple regression model
Submerged arc welding
Issue Date: Apr-2007
Publisher: CSIR
Series/Report no.: G06N7/02
Abstract: This paper proposes an intelligent technique, Adaptive Neuro-Fuzzy Inference System (ANFIS), to predict the weld bead width in the submerged arc welding (SAW) process for a given set of welding parameters. Experiments are designed according to Taguchi’s principles and its results are used to develop a multiple regression model. Multiple sets of data from multiple regression analysis are utilized to train the intelligent network. The trained network is used to predict the quality of weld. The proposed ANFIS, developed using MATLAB functions, is flexible, accurate than existing models and it scopes for a better online monitoring system.
Description: 335-338
ISSN: 0022-4456
Appears in Collections:JSIR Vol.66(04) [April 2007]

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