STATISTICAL ANALYSIS ON MECHANICAL PROPERTIES OF FRICTION-STIR-WELDED SUPER DUPLEX STAINLESS STEEL SAF 2507 | ||||
| Journal of the Egyptian Society of Tribology | ||||
| Volume 21, Issue 2, April 2024, Page 93-104 PDF (739.71 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/jest.2024.282850.1086 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
M. H. El-Shazly1; Kh. M. Sakr2; R. I. Elsoeudy3; A. S. Ali  3
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| 1Department of Mechanical Design and Production Engineering, Faculty of Engineering, Cairo University, Giza | ||||
| 2Engineer Officer in the Egyptian Armed Forces | ||||
| 3Mechanical Engineering Dept., Faculty of Engineering, Suez Canal University, EGYPT. | ||||
| Abstract | ||||
| This work employs statistical analysis, including Analysis of Variance (ANOVA) through the Design of Experiment (DOE) approach, to systematically assess the impact of key process parameters on Friction Stir Welding (FSW) outcomes. The study focuses on modeling FSW for Super Duplex Stainless Steel SAF 2507 using Abaqus, utilizing ANOVA to understand the individual and interactive effects of parameters like tilt angle, welding velocity, rotation velocity, and axial force. Abaqus simulations offer detailed insights into the thermal and mechanical aspects of welding, followed by Response Surface Methodology (RSM) for predictive modeling and parameter optimization. The research, centered on the robust Super Duplex Stainless Steel SAF 2507 and a tungsten carbide tool, contributes valuable knowledge for enhancing FSW parameters and achieving superior weld quality in practical applications. | ||||
| Keywords | ||||
| Analysis of Variance (ANOVA); Design of Experiment (DOE); response surface methodology; super duplex stainless steel SAF 2507 | ||||
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