ISSN

2231-3915 (Online)
2231-3907 (Print)


Author(s): Praful Daharwal, Prashant Awchat

Email(s): prafuldaharwal@gmail.com

DOI: 10.5958/2231-3915.2018.00007.X   

Address: Praful Daharwal1*, Prashant Awchat2
1Student, M. Tech.,G.H. Raisoni Academy of Engineering and Technology, Nagpur
2Professor, G.H. Raisoni Academy of Engineering and Technology, Nagpur
*Corresponding Author

Published In:   Volume - 8,      Issue - 1,     Year - 2018


ABSTRACT:
Welding process for joining similar and different materials is one of the economical and is a much faster process of joining. Because of its reliability, submerge arc welding is one of the chief metal joining process employed in industry. With the proper selection of equipment, submerge arc welding can be applied to a wide range of industrial applications. The high quality of welds, the high depositional rates, the deep penetration and the adaptability to automatic operation makes it the process particularly suitable for fabrication of large weldments. The quality of SAW is mainly influenced by independent variables such as welding current, voltage, and travel speed and electrode stickout. The automation of SAW application is often desirable due to somewhat unpleasant working condition that the process creates. The application of Taguchi techniques and regression analysis to determine the optimal process parameters for the submerge arc welding and the quality improvement. The quality engineering method of Taguchi employing of experiment provides are efficient and systematically way to optimise design for performing, quality and cost. It is one of the most important statical tools for designing high quality system at reduced cost. The use of Taguchi method simplifies the optimization procedure for determining the optimal welding parameter in the submerge arc welding.


Cite this article:
Praful Daharwal, Prashant Awchat. Quality Improvement in Submerged Arc Welding Process Using Taguchi Method and Regression Analysis. Int. J. Tech. 2018; 8(1): 41-46 doi: 10.5958/2231-3915.2018.00007.X


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RNI: Not Available                     
DOI: 10.5958/2231-3915 


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