Experimental Investigation of Electrochemical Micromachaning Process Parameters on Pure-Titanium Using Taguchi-Grey Relational Analysis

2016 ◽  
Vol 852 ◽  
pp. 198-204
Author(s):  
T. Geethapriyan ◽  
K. Kalaichelvan
Keyword(s):  
Process Parameters ◽  
Grey Relational Analysis ◽  
Metal Removal ◽  
Removal Rate ◽  
Pure Titanium ◽  
Electrochemical Machining ◽  
Electrochemical Micromachining ◽  
Influence Of Process Parameters ◽  
Relational Analysis ◽  
Grey Relational

Non-conventional machine are nowadays plays a vital role in manufacturing complex shaped products and to produce the product with high accuracy the electrochemical machining is widely used to machine complicated shapes for electrically conducting difficult-to-machine materials such as super alloys, Ti-alloys, alloy steel, tool steel, stainless steel, etc. such titanium-based alloys are in common use for aero engine components such as blades and blisks (blade integrated disks). Therefore, in this present work to investigate the influence of some predominant electrochemical process parameters such as applied voltage, electrolyte concentration, Micro-tool feed rate and duty cycle on the metal removal rate , overcut and surface roughness to fulfill the effective utilization of electrochemical machining of Pure-titanium. The purpose of this study is to investigate the influence of process parameters on machining characteristics and optimize the combination of those parameters using Taguchi-grey relational analysis. From this result, it is observed that process parameters have significant role in Electrochemical Micromachining process and the optimization values has been found using proposed multi-response methodology.

scholarly journals Multi Performance Optimizationof Shoulder Milling Process Parameters of AA6063 T6 Aluminium Alloy by Taguchi Based GRA

2019 ◽  
Vol 8 (10S) ◽  
pp. 420-425
Keyword(s):  
Process Parameters ◽  
Grey Relational Analysis ◽  
Removal Rate ◽  
Analysis Data ◽  
Milling Process ◽  
Depth Of Cut ◽  
Analysis Method ◽  
Relational Analysis ◽  
Grey Relational Grade ◽  
Grey Relational

In this paper, a grey relational analysis method based on Taguchi is proposed to improve the multi-performance characteristics of VMC shoulder milling process parameters in the processing of AA6063 T6. Taking into account four process parameters such as coolant, depth of cut,speed and feed, there are three level of each process parameter in addition to two levels of coolant. 18 experiments were used by L18 orthogonal array using the taguchi method. Multi-performance features like surface roughness and material removal rate are used. Grey Relational Analysis method is used to obtain the Grey Relational Grade, and the multiperformance characteristics of the process are pointed out. Then, the Taguchi response table method and ANOVA are used to analysis data. In order to ensure the validity of the test results, a confirmation test was conducted. The study also shows that this method can effectively improve the multi-function characteristics of shoulder milling process.In his work microstructure and mechanical properties of AA6063 T6before and after shoulder milling have been investigated.

Performance analysis of process parameters on machining α–β titanium alloy in electrochemical micromachining process

2016 ◽  
Vol 232 (9) ◽  
pp. 1577-1589 ◽  
Author(s):  
T Geethapriyan ◽  
K Kalaichelvan ◽  
T Muthuramalingam ◽  
A Rajadurai
Keyword(s):  
Surface Roughness ◽  
Titanium Alloy ◽  
Grey Relational Analysis ◽  
Material Removal ◽  
Electrolyte Concentration ◽  
Removal Rate ◽  
Electrochemical Micromachining ◽  
Relational Analysis ◽  
Micro Tool ◽  
Grey Relational

Due to inherent properties of Ti-6Al-4V alloy, it is being used in the application of fuel injector nozzle for diesel engine, aerospace and marine industries. Since the electrochemical micromachining process involves the no heat-affected zone, no tool wear, stress- and burr-free process compared to other micromachining processes, it is widely used in the manufacturing field to fabricate complex shape and die. Hence, it is highly important to compute the optimum input parameters for enhancing the machining characteristics in such machining process. In this study, an attempt has been made to find the influence of the process parameters and optimize the parameters on machining α–β titanium alloy using Taguchi-grey relational analysis. Since applied voltage, micro-tool feed rate, electrolyte concentration and duty cycle have vital role in the process, these parameters have been chosen as the input parameters to evaluate the performance measures such as material removal rate, surface roughness and overcut in this study. From the experimental results, it has been found that micro-tool feed rate has more influence due to its importance in maintaining inter electrode gap to avoid micro-spark generation. It has also been found that lower electrolyte concentration with lower duty cycle produces lower surface roughness with better circularity on machining α–β titanium alloy. The optimum combination has been found using Taguchi-grey relational analysis and verified from confirmation test. It has also been inferred that the multi-response characteristics such as material removal rate, surface roughness and overcut can be effectively improved through the grey relational analysis.

Multi-response optimization of CNC turning parameters of austenitic stainless steel 303 using Taguchi-based grey relational analysis

2020 ◽  
Vol 44 (4) ◽  
pp. 592-601
Author(s):  
S.R. Sundara Bharathi ◽  
D. Ravindran ◽  
A. Arul Marcel Moshi
Keyword(s):  
Stainless Steel ◽  
Process Parameters ◽  
Grey Relational Analysis ◽  
Removal Rate ◽  
Regression Equations ◽  
Turning Process ◽  
Cnc Turning ◽  
Relational Analysis ◽  
Grey Relational ◽  
Cnc Turning Process

Extensive research has been carried out to optimize the process parameters of several machining processes. Optimizing the influencing parameters of the turning operation is a precise action that determines the desired level of quality. This study focuses on the multi-criteria optimization of the CNC turning process parameters of stainless steel 303 (SS 303) material to achieve minimum surface roughness (Ra) with maximum material removal rate (MRR) by means of Taguchi-based grey relational analysis. A CNC machine was tested following Taguchi’s L9 orthogonal array design. Grey relational analysis was used as the multi-criteria optimization tool. The significance of each individual process parameter on the overall characteristics of the turned specimen was estimated using analysis of variance (ANOVA). Regression equations were generated using the input factors with the selected output parameters. In addition, a morphological study of the chips produced by the turning process was carried out using SEM images in order to relate the chip geometry with the output responses.

Optimization of EDM Process with Magnetic Field Using Grey Relational Analysis Coupled with Principal Component Analysis

2015 ◽  
Vol 799-800 ◽  
pp. 388-392 ◽  
Author(s):  
G. Anand ◽  
M. Manzoor Hussian ◽  
S. Satyanarayana
Keyword(s):  
Principal Component Analysis ◽  
Grey Relational Analysis ◽  
Metal Removal ◽  
Removal Rate ◽  
Principal Component ◽  
Component Analysis ◽  
Optimal Combination ◽  
Relational Analysis ◽  
Grey Relational ◽  
Edm Process

This paper investigates optimized design of Electro Discharge Machining process parameters on HCHCr i.e. DIN 17350-1.2080 Die steel. This process is one of the most widely applied non-traditional machining processes. To determine the optimal EDM conditions in several industrial fields. Taguchi method has been utilized to optimize only a single performance characteristic. To overcome this limitation, the Grey Relational Analysis theory has been used to determine grey relational grade as performance index to determine the optimal combination of the parameters such as peak current (I), pulse duration (Ton), voltage (V) to evaluate multiple performance characteristic such as metal removal rate and surface roughness simultaneously. Moreover, the Principal Component Analysis is applied to evaluate the weighting values corresponding to metal removal rate and surface roughness performance characteristics so that their relative importance can be properly defined. The analysis reveal that Grey Relational Analysis coupled with Principal Component Analysis can effectively be used to obtain the optimal combination of EDM process parameters. The obtained optimal machining conditions were Peak current at 15A, pulse on time at 250μs, Voltage at 85V. It is also observed that magnetic field in spark zone have improved metal removed rate and surface finish.

Optimization by Grey Relational Analysis of EDM Parameters on Machining Ti-6Al-4V

2010 ◽  
Vol 139-141 ◽  
pp. 540-544 ◽  
Author(s):  
Zhi Ping Xie ◽  
Ji Ming Zheng ◽  
Bian Li Quan
Keyword(s):  
Taguchi Method ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Grey Relational Analysis ◽  
Material Removal ◽  
Removal Rate ◽  
Electrode Wear ◽  
Relational Analysis ◽  
Wear Ratio ◽  
Grey Relational

In this paper, parameter optimization of the electrical discharge machining process to Ti–6Al–4V alloy considering the multiple responses using the Taguchi method and grey relational analysis is reported. The multi-response optimization of the process parameters are material removal rate (MRR) and electrode wear rate (EWR). The machining parameters including discharge current, voltage, pulse on time and duty factor. Experiment based on the orthogonal array, The optimized process parameters simultaneously leading to a lower electrode wear ratio and higher material removal rate are then verified through a confirmation experiment. The experimental result for the optimal setting shows that there is considerable improvement in the process. The validation experiments show an improved electrode wear ratio of 2.8%, material removal rate of 45.8% when the Taguchi method and grey relational analysis are used.

Optimization of laser-assisted jet electrochemical machining parameters by grey relational analysis and fuzzy logic

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Anup Malik ◽  
Neel Sanghvi
Keyword(s):  
Fuzzy Logic ◽  
Grey Relational Analysis ◽  
Removal Rate ◽  
Electrochemical Machining ◽  
Machining Parameters ◽  
Taper Angle ◽  
Content Type ◽  
Relational Analysis ◽  
Grey Relational ◽  
Jet Electrochemical Machining

Purpose The purpose of this paper is to optimize the laser-assisted jet electrochemical machining parameters, namely, supply voltage, inter-electrode gap, duty cycle and electrolyte concentration during machining of WC-Co composite using grey relational analysis and fuzzy logic. Design/methodology/approach In this work, experiments were carried out as per the Taguchi methodology and an L16 orthogonal array was used to study the influence of various combinations of process parameters on material removal rate, hole taper angle and surface roughness height. As a dynamic approach, the multiple response optimization was carried out using grey relational analysis and fuzzy logic. Findings The process parameters were optimized using grey relational analysis and fuzzy logic for different machining conditions such as balanced manufacturing, high-speed manufacturing and high-quality manufacturing. The research documented in this paper can be scaled up for case studies regarding industrial applications to compare optimization methods for manufacturing processes that are already being carried out. Originality/value An attempt to optimize material removal rate, hole taper angle and surface roughness height together by a combined approach of grey relational analysis and fuzzy logic has not been previously done.

Application of Taguchi-Grey Relational Methodology for Multiple Optimal Performance Measures in WEDM Process

2015 ◽  
Vol 766-767 ◽  
pp. 861-866 ◽  
Author(s):  
A. Ramamurthy ◽  
R. Sivaramakrishnan ◽  
S. Venugopal ◽  
T. Muthuramalingam
Keyword(s):  
Performance Measures ◽  
Process Parameters ◽  
Grey Relational Analysis ◽  
Removal Rate ◽  
Optimum Process ◽  
Relational Analysis ◽  
Grey Relational ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Wedm Process

It is very tedious process to find the optimum multiple performance measures of wire EDM process parameters and role of each parameter to attain the better performance characteristics. Since the WEDM process involves more one than machining characteristics, it is important to carry out the multi-response optimization methodology. In the present study, an attempt has been made to find the optimum process parameters using Taguchi-Grey relational analysis. The machining experiments have been conducted with different levels of input factors such as voltage, peak current, pulse on time, and pulse off time and wire material based on Taguchi L18 orthogonal table. Experimental results have indicated that the multi-response characteristic such material removal rate and surface roughness can be enhanced by 1.2% effectively through grey relational analysis.

Sign in / Sign up

Export Citation Format

Share Document