Open AccessOptimization of Welding Parameters by Regression Modelling and Taguchi Parametric Optimization Technique
Author(s) -
Arvind Kumar Kachhoriya,
Ajay Bangar,
Rajan Sharma,
Neetu Neetu
Publication year - 2012
Publication title -
international journal of mechanical and industrial engineering
Language(s) - English
Resource type - Journals
ISSN - 2231-6477
DOI - 10.47893/ijmie.2012.1038
Subject(s) - taguchi methods , welding , orthogonal array , design of experiments , parametric statistics , selection (genetic algorithm) , regression analysis , enhanced data rates for gsm evolution , range (aeronautics) , engineering , mechanical engineering , computer science , structural engineering , mathematics , statistics , artificial intelligence , machine learning , aerospace engineering
There are many welding parameters In welding process, the major factors whose selection contributes to the welded product as they all affect the strength and quality to a larger extent are weld design (edge preparation), Root face, and Root gap. The purpose of this paper is to efficiently determine the optimum welding operation parameters for achieving the highest ultimate strength in range of parameters. In order to meet the purpose in terms of both efficiency and effectiveness, this study will utilize the Taguchi parameters design methodology. The study includes selection of parameters, utilizing an orthogonal array, conducting experimental runs, data analysis, determining the optimum combination, finally the experimental verification and comparison by regression modelling.