Multiobjective Optimization of Friction Stir Welding Process Parameters on Aluminum Alloy AA 5083 Using Taguchi-Based Grey Relation Analysis

Process Parameters Optimization for Producing AA6061/TiB2 Composites by Friction Stir Processing

“…The optimum values were rotational speed of 1800 rpm, transverse speed of 180 m/min, tool tilt angle of 1˚ and pin length of 2.9 mm. S. Vijayan et al [45] studied friction stir welding (FSW) of AA 5083 with multiple responses based on orthogonal array with grey relational analysis. The process parameters such as speed, feed and axial load were considered and optimized parameters towards high the tensile strength of the joint and input power.…”

“…K. Jitender et al [41] studied the optimization of process parameters in FSW of AA5083 alloy using taguchi grey analysis and the objective was to find the optimum levels of speed, feed, tilt angle for maximizing UTS, Elongation and Micro Hardness. S. Vijayan et al [42] studied the optimization of process parameters in FSW of aluminium alloy with multiple responses based on orthogonal array using grey relational analysis. The objective was to find the optimum levels of the process parameters in which it yields maximum tensile strength and consumes minimum power.…”

Multiobjective Optimization for Wire Edm of Wc-Co Composite Using Gra With Entropy Measurement

“…The obtained weights of each performance characteristics have been further used to calculate the grey relational grade by using Eq. (14). Table 5lists the grey relational coefficient and grey relational grade for each experimental run.…”

“…By using GRA cutting speed and surface roughness was predicted within 5% error. G. Rajyalakshmi et al [13], S. Vijayan et al [14] also applied the GRA method for finding the optimal setting of process parameters, satisfactory results were obtained in all the cases which shows the effectiveness of GRA method, however later it was proposed by some researchers that taking average of grey relational coefficient for finding grey relational grade is not an appropriate step as each performance characteristic may have different sensitivity for the machining parameters. For solving this problem a new approach called grey entropy was introduced.…”

Multi Response Objective Optimization of Friction Stir Welding Parameters of Dissimilar Metals of AA 6061 Aluminumand IS319 Brass Joining Through Taguchi’s Method

“…VIJAYAN [2] reported the optimization of process parameters for aluminum alloy analysis and also given multiple objective optimization to get optimum response characteristics. T parameters such as spindle rotational speed, (UTS) and hardness of welded joints studied [ desirability approach [4].…”