Table of Contents
International Journal of Manufacturing Engineering
Volume 2014 (2014), Article ID 943643, 8 pages
http://dx.doi.org/10.1155/2014/943643
Research Article

Optimization of Fusion Zone Grain Size, Hardness, and Ultimate Tensile Strength of Pulsed Current Microplasma Arc Welded AISI 304L Sheets Using Genetic Algorithm

1Department of Mechanical Engineering, Anil Neerukonda Institute of Technology & Sciences, Visakhapatnam 530 003, India
2Department of Mechanical Engineering, AU College of Engineering, Andhra University, Visakhapatnam 531 162, India
3Centurion University of Technology & Management, Odisha 761 211, India

Received 18 September 2013; Accepted 28 January 2014; Published 5 March 2014

Academic Editor: Shia-Chung Chen

Copyright © 2014 Siva Prasad Kondapalli et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Austenitic stainless steel sheets have gathered wide acceptance in the fabrication of components, which require high temperature resistance and corrosion resistance, such as metal bellows used in expansion joints in aircraft, aerospace, and petroleum industry. In case of single pass welding of thinner sections of this alloy, Pulsed Current Microplasma Arc Welding (PCMPAW) was found beneficial due to its advantages over the conventional continuous current process. The quality of welded joint depends on the grain size, hardness, and ultimate tensile strength, which have to be properly controlled and optimized to ensure better economy and desirable mechanical characteristics of the weld. This paper highlights the development of empirical mathematical equations using multiple regression analysis, correlating various process parameters to grain size, and ultimate tensile strength in PCMPAW of AISI 304L sheets. The experiments were conducted based on a five-factor, five-level central composite rotatable design matrix. A genetic algorithm (GA) was developed to optimize the process parameters for achieving the desired grain size, hardness, and ultimate tensile strength.