Sensitivity Analysis for Process Parameters in Cladding of Austenitic Stainless Steel by Pulsed Metal Inert Gas Welding Process

R. Prabhu; T. Alwarsamy

doi:10.4028/www.scientific.net/AMM.813-814.474

Paper Titles

Multiple Performance Characteristics Optimization for AA8011 on Friction Stir Welding by RSM Based DEA
p.451

Optimization of GMAW Parameters to Improve the Mechanical Properties
p.456

Parameter Optimization for Friction Stir Welding AA1100
p.462

Prediction of Weld Strength of PC-TIG Welded Al-8% SiC Metal Matrix Composite – An Empirical Model (EM) Approach
p.467

Sensitivity Analysis for Process Parameters in Cladding of Austenitic Stainless Steel by Pulsed Metal Inert Gas Welding Process
p.474

Studies on Mechanical Properties, Fracture Morphology and Corrosion Behavior of Pulsed MIG Welded AZ31B Magnesium Alloy Sheets
p.480

Weld Properties of Low Carbon Steel Using Shielded Metal Arc Welding
p.486

A Review on Optimization of Friction and Wear Parameters (Al Alloy-B₄C) Composite Using Taguchi Technique
p.491

An Approach on Fuzzy and Regression Modeling for Hard Milling Process
p.498

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 813-814Sensitivity Analysis for Process Parameters in...

Sensitivity Analysis for Process Parameters in Cladding of Austenitic Stainless Steel by Pulsed Metal Inert Gas Welding Process

Abstract:

In recent scenario, the automation in weld cladding process has a challenging task for most of the industries like automotive, petrochemical and food processing industries. Because to achieve the best quality of the weld clad bead geometry during automated process it is important to have complete control over the selected process parameters. The cladding process enhances the base material properties. Therefore, it is essential to predict the relationship between the process parameters and response the second order polynomial regression equation has to be developed. It makes more effectiveness of automated weld cladding processes. Palani and Murugan [1] developed a mathematical model for a flux cored arc welding process using an RSM method to study the direct effects and interaction effects of process parameters on clad bead geometry.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 813-814)

Pages:

474-479

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.813-814.474

Citation:

Cite this paper

Online since:

November 2015

Authors:

R. Prabhu*, T. Alwarsamy

Keywords:

Bead Geometry, Cladding, Pulsed Metal Inert Gas Welding, Regression Analysis, Sensitivity Analysis

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] P. K. Palani and N. Murugan, Development of mathematical models for prediction of weld bead geometry in cladding by flux cored arc welding. Int. J. Adv. Manuf. Technol. 30 (2006) 669-676.

DOI: 10.1007/s00170-005-0101-2

Google Scholar

[2] K. Marimuthu and N. Murugan, Sensitivity analysis of process parameters in PTA hardfacing of valve seats using response surface methodology. Materials Science and Technology. 21 (2005) 941-947.

DOI: 10.1179/174328405x51640

Google Scholar

[3] P. K. Palani and N. Murugan, Sensitivity Analysis for Process Parameters in Cladding of Stainless Steel by Flux Cored Arc Welding. Journal of Manufacturing Processes. 8 (2006) 90-100.

DOI: 10.1016/s1526-6125(06)80004-6

Google Scholar

[4] C.H. Chuang and G.J. Hou, Eigenvalue sensitivity analysis of planar frames with variable joint and support locations, AIAA Journal 30 (2) (1999) 2138–2147.

DOI: 10.2514/3.11192

Google Scholar

[5] B. Choi, Y.H. Park and K.K. Choi, Shape design optimization of joining mechanism using doubly curved shell, Computers and Structures, 77 (2000) 495–507.

DOI: 10.1016/s0045-7949(99)00234-5

Google Scholar

[6] I. S. Kim, K. J. Son, Y. S. Yang and P. K. D. V. Yaragada, Sensitivity analysis for process parameters in GMA welding processes using a factorial design method. Int. J. Mach. Tools Manuf. 43(2003) 763–769.

DOI: 10.1016/s0890-6955(03)00054-3

Google Scholar