Multi-response optimization of process parameters for laser beam welding of AA6061-Ti6Al4V by grey relational analysis. (2021)

• Record Type: Journal Article
• Authors: Chandran, Sudhin; Rajesh, R.; Dev Anand, M.
• Is Part Of: Materials today. Volume 46:Part 17(2021)
• Page Start: 7492
• Page End: 7496
• Publication Date: 2021
• Subjects: Laser Beam Welding (LBW) -- Mechanical properties -- Grey relational analysis -- Factorial method -- ANOVA; Materials science -- Congresses -- Periodicals; 620.1
• DOI: 10.1016/j.matpr.2021.01.172
• Languages: English
• ISSNs: 2214-7853

Abstract

Abstract: Laser beam welding (LBW) is employed for consolidating distinct materials, aluminium (AA6061) and titanium (Ti6Al4V). LBW, attributable to appealing highlights, to be specific, low heat input, high heat focus, high-power density, and low contortion, is a more useful technique for welding and fixing airplane and turbine motor components built from superalloy. This investigation concentrates on optimizing process parameters for laser beam welding of AA6061-Ti6Al4V utilizing factorial-based grey relational analysis. The welding input parameters assume a fundamental part in optimized preferred weld quality. The input parameter picked were laser power, welding speed, and offset. The welding is done for 27 specimens to elevate and endorse the mechanical and metallurgical properties. This welding is completed with three sets of process parameters with three levels of values. The three-process parameter with three sets of values are welding power (1600–2000 W), welding speed (2–2.4 m/min), and offset (0.2–0.4 mm). ANOVA technique was utilized to evaluate the centrality of variables on the finest quality of the weldment. ANOVA results demonstrated that laser power assumed a significant part of the quality targets (Tensile strength and hardness) of the weldments trailed by welding speed and offset. Grey relational analysis is implemented to optimize the input parameters at the same time considering multiple output variables.