scholarly journals Multi attribute decision making parametric optimization in weld bead by gas metal arc welding through grey relation analysis: A case study

2020 ◽  
Vol 12 (2) ◽  
pp. 59-66
Author(s):  
Saadat Ali Rizvi ◽  
Wajahat Ali
Keyword(s):  
Process Parameters ◽  
Grey Relational Analysis ◽  
Gma Welding ◽  
Welding Process ◽  
Weld Bead ◽  
Feed Speed ◽  
Taguchi Technique ◽  
Relational Analysis ◽  
Input Parameters ◽  
Grey Relational

The basic purpose of this study was to identify the effect of gas metal arc (GMA) welding process parameters on the weld bead geometry of IS2062 structural steel of A grade. L16 Taguchi orthogonal array (OA) design with the idea of S/N (signal to noise) ratio was applied to obtain objective function to be optimized within the experimental field. In this research work the Taguchi technique was joined with grey relational analysis to solve the multi-response optimization problem. ANOVA (Analysis of Variance) was applied to estimate the most significant input parameters which contribute toward the output parameters. Arc voltage, gas flow rate, and wire feed speed were carefully selected as input parameters, whereas weld bead, depth of penetration, and reinforcement were output respectively. The optimal GMA welding process parameters were identified in order to enhance the productivity and curtail the overall functional cost of weld. Keywords: grey-relational analysis (GRA), Taguchi technique, optimization, GMAW, ANOVA.

Multi Response Optimization of Submerged Friction Stir Welding Process Parameters Using Grey Relational Analysis

2016 ◽  
Author(s):  
Senthil Kumar Velukkudi Santhanam ◽  
Sankar Ramaiyan ◽  
Lokesh Rathinaraj ◽  
Rathinasuriyan Chandran
Keyword(s):  
Friction Stir Welding ◽  
Process Parameters ◽  
Grey Relational Analysis ◽  
Welding Process ◽  
Friction Stir ◽  
Friction Stir Welding Process ◽  
Response Characteristics ◽  
Relational Analysis ◽  
Response Optimization ◽  
Grey Relational

Friction stir welding (FSW) invented by TWI is a solid-state joining process, which is used to weld high-strength aluminum alloys and other metallic alloys which are non weldable by conventional fusion welding process. In this work, AA6063-O alloy of 150 mm in length, 75 mm in width and 6mm thickness is taken and friction stir welded in submerged condition in order to improve the joint properties. The chosen process parameters are tool pin profiles (cylindrical, threaded and tapered), rotational speed and welding speed. The process parameters are optimized with multi response characteristics including hardness and average grain size at the nugget zone. The traditional Taguchi approach is insufficient to solve a multi response optimization problem. Therefore, Grey Relational Analysis (GRA) is used in this current work. The optimal result indicates that the multi response characteristics of the AA6063-O during the submerged friction stir welding process can be enhanced through Grey Relational Analysis. In order to investigate the significance of process parameters, Analysis of Variance (ANOVA) is carried out. The mechanical properties and microstructure variation of both the normal FSW and submerged FSW joints are compared.

scholarly journals Analysis and optimization of laser drilling process during machining of AISI 303 material using grey relational analysis approach

2021 ◽  
Vol 3 (3) ◽  
Author(s):  
V. Chengal Reddy ◽  
Thota Keerthi ◽  
T. Nishkala ◽  
G. Maruthi Prasad Yadav
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Grey Relational Analysis ◽  
Pulse Frequency ◽  
Laser Drilling ◽  
Simultaneous Optimization ◽  
Fibre Laser ◽  
Drilling Process ◽  
Relational Analysis ◽  
Grey Relational

AbstractSurface roughness and heat-affected zone (HAZ) are the important features which influence the performance of the laser-drilled products. Understanding the influence of laser process parameters on these responses and identifying the cutting conditions for simultaneous optimization of these responses are a primary requirement in order to improve the laser drilling performance. Nevertheless, no such contribution has been made in the literature during laser drilling of AISI 303 material. The aim of the present work is to optimize the surface roughness (Ra) and HAZ in fibre laser drilling of AISI 303 material using Taguchi-based grey relational analysis (GRA). From the GRA methodology, the recommended optimum combination of process parameters is flushing pressure at 30 Pa, laser power at 2000 W and pulse frequency at 1500 Hz for simultaneous optimization of Ra and HAZ, respectively. From analysis of variance, the pulse frequency is identified as the most influenced process parameters on laser drilling process performance.

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