journal article·2016-10

Analysis of mechanical properties and optimization of gas tungsten Arc welding (GTAW) parameters on dissimilar metal titanium (6Al 4V) and aluminium 7075 by Taguchi and ANOVA techniques

K. Nandagopal, C. Kailasanathan

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Abstract

Abstract The Gas Tungsten Arc Welding (GTAW) is carried out between the two dissimilar materials titanium (6Al 4V) and aluminium 7075 with filler material as aluminium AA 4047. The welding is carried out for twenty five samples to enhance and validate the mechanical and metallurgical properties. This welding is carried out with three set of process parameter with five levels of values. The mechanical property such as tensile strength and hardness value is measured for work piece and the maximum value is said to 342.20 MPa and 183.10 Hv respectively. Taguchi L 25 orthogonal array is used to optimize the process parameters to attain the optimal joint strength and quality of joint in the welded samples and also it is used to identify the most influential process parameter in this welding process. The three process parameter with five set of values are welding current (80–100 A), welding speed (60–80 mm/min), and arc voltage (14–18 V). ANOVA method is used to determine the percentage contribution by each process parameter. The metallurgical studies have been carried out for the weld samples such microscopic test, Scanning electron microscope and energy dispersive X-Ray test on the welded samples. The microstructural studies reveals the about the welding configuration which is capable of producing defect-free welds. Scanning electron microscope (SEM) and Energy-dispersive X-ray analysis (EDX) is carried out to measure the nature of the matrix and chemical element distribution in the weld interface.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Welding Techniques and Residual Stresses · Advanced Welding Techniques Analysis · Titanium Alloys Microstructure and Properties

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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