Optimization of Welding Parameters on Mechanical Properties of Dissimilar Metal Welds Using GTAW Process.
Mrugesh Solanki
, Prof. Ketan Shah
GTAW, Dissimilar Welding, AISI 316
— Tungsten Inert Gas (TIG) welding also known as GTAW (Gas Tungsten Arc Welding) is highly used fabrication process to join metals. Dissimilar material welding is complex technique due to difference in chemical and thermal properties. The purpose of this research work is to obtain perfect process parameters using Gas Tungsten Arc Welding for dissimilar metals. Study the mechanical properties of weld joint and optimizing process parameters so as to achieve optimum weld strength and micro hardness. With control over welding parameters such as root gap, joint angle, welding current, etc. The experiment is done by setting the parameters range based on trial experiments and studying research paper. The DOE (Design of Experiment) method used for the experiments is Response Surface method (RSM) with Central Composite Design (CCD). The DOE are designed by MINITAB software. The readings for UTS and micro hardness are noted of the weld joint. Moreover microstructure will be performed to examine microscopic description of the individual constituent of material. Optimization of process parameters will be been carried out using the Response Surface Methodology (RSM).
"Optimization of Welding Parameters on Mechanical Properties of Dissimilar Metal Welds Using GTAW Process.", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.1, Issue 5, page no.553 - 558, May-2016, Available :https://ijsdr.org/papers/IJSDR1605106.pdf
Volume 1
Issue 5,
May-2016
Pages : 553 - 558
Paper Reg. ID: IJSDR_160391
Published Paper Id: IJSDR1605106
Downloads: 000347064
Research Area: Engineering
Country: Ahmedabad, Gujarat, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave