Simultaneous Optimization of Machining Process Parameters of Near-Dry Rotary EDM Using Grey Relational Analysis

2020 ◽  
pp. 209-226
Author(s):  
Pankaj Gaigole ◽  
S. G. Kale ◽  
J. K. Bagwan ◽  
B. Rajiv ◽  
B. B. Ahuja
Keyword(s):  
Process Parameters ◽  
Grey Relational Analysis ◽  
Machining Process ◽  
Simultaneous Optimization ◽  
Relational Analysis ◽  
Rotary Edm ◽  
Grey Relational

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.

scholarly journals Grey Relational Analysis of EDM of Ti6Al4V using TiC/Cu Composite Tool Electrode Made with Nano and Micron Sized Particles

2019 ◽  
Vol 9 (1) ◽  
pp. 6154-6162
Keyword(s):  
Process Parameters ◽  
Grey Relational Analysis ◽  
Optimum Combination ◽  
Ti6al4v Alloy ◽  
Machining Process ◽  
Dominant Factor ◽  
Tool Electrode ◽  
Peak Current ◽  
Relational Analysis ◽  
Grey Relational

This paper covers the use of Taguchi based grey relational analysis in EDM process. The analysis is used to determine an optimum combination of process parameters, which involves individual and simultaneous improvement of surface roughness (SR) and the micro hardness (MH) of Ti6Al4V alloy in electric discharge machining (EDM). The tool used in the machining process is TiC/Cu powder metallurgy (P/M) electrode. Taguchi’s L18 mixed orthogonal array is used to plan experimentations which includes the machine tool and electrode parameters as the study parameters. The analysis of variance (ANOVA) for grey relational grade showed that particle size EDM electrode was the most dominant factor (64.13%) followed by peak current (7.41%) in influencing surface quality of EDMed Ti6Al4V alloy. Whereas, peak current is the most influential parameter while evaluating the individual responses of SR and MH. Finally, the optimum combination of process parameters was validated by confirmation experiments that considerably improved the multiple quality characteristics simultaneously.

Optimization of EDM Parameters in Machining AISI D3 Tool Steel by Grey Relational Analysis

2013 ◽  
Vol 330 ◽  
pp. 747-753
Author(s):  
Othman Belgassim ◽  
Abdurahman Abu-Saada
Keyword(s):  
Taguchi Method ◽  
Tool Steel ◽  
Process Parameters ◽  
Grey Relational Analysis ◽  
Pulse Current ◽  
Machining Process ◽  
Relational Analysis ◽  
Grey Relational ◽  
Pulse On Time ◽  
D3 Tool Steel

This study presents optimization of multiple performance characteristics [material removal rate (MRR), surface roughness (Ra), and overcut (OC)] of hardened AISI D3 tool steel in electrical discharge machining (EDM) using Taguchi method and Grey relational analysis. Machining process parameters selected were pulse current Ip, pulse-on time Ton, pulse-off time Toff and gap voltage Vg . Based on ANOVA, pulse current is found to be the most significant factor affecting EDM process. Optimized process parameters simultaneously leading to a higher MRR, lower Ra, and lower OC are then verified through a confirmation experiment. Validation experiment shows an improved MRR, Ra and OC when Taguchi method and grey relational analysis were used.

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