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.

Optimization of WEDM Process Parameters of Hybrid Composites (A413 / B4C / Fly Ash) Using Grey Relational Analysis

2014 ◽  
Vol 592-594 ◽  
pp. 658-662 ◽  
Author(s):  
J. Milton Peter ◽  
J. Udaya Prakash ◽  
T.V. Moorthy
Keyword(s):  
Surface Roughness ◽  
Fly Ash ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Grey Relational Analysis ◽  
Material Removal ◽  
Hybrid Composites ◽  
Removal Rate ◽  
Relational Analysis ◽  
Grey Relational

This paper presents an optimum method to find the significant parameters affecting Wire Electrical Discharge machining (WEDM) performance using Grey relational analysis. A413 Aluminium Alloy reinforced with 20 microns of Boron Carbide and 75 microns of Fly Ash, hybrid composites was fabricated using stir casting technique. Experiments have been conducted with the process parameters like pulse on time, pulse off time, wire feed, gap voltage and weight percentage reinforcement with three different levels. The influence of each parameter on the responses material removal rate and surface roughness is established using analysis of variances (ANOVA). The optimal machining-parameters setting for minimum surface roughness and maximum material removal rate was obtained by applying Grey relational analysis.

Optimization Design for Gun-Receiver Materials Belt Grinding Based on Orthogonal Experimental Method and Grey Relational Analysis

2013 ◽  
Vol 797 ◽  
pp. 55-60
Author(s):  
Yu Hui Chen ◽  
Yun Huang ◽  
Yao Huang
Keyword(s):  
Surface Roughness ◽  
Material Removal Rate ◽  
Grey Relational Analysis ◽  
Material Removal ◽  
Optimization Design ◽  
Removal Rate ◽  
Belt Grinding ◽  
Abrasive Belt ◽  
Relational Analysis ◽  
Grey Relational

In order to change the current situation of gun-receiver manual polishing, the paper presents a new process for abrasive belt grinding of gun-receiver material (C50 steel). Orthogonal test were conducted with abrasive belt grinding of C50 steel to do research on material removal rate and surface roughness. The best parameter combination to the optimization design which can guarantee high material removal rate and low surface roughness was obtained by using grey relational analysis method and verified by experiments. The above mentioned research not only can improve the removal rate of C50 steel, but also do help to prolong the service life of the belt. Whats more, it can guide a theoretical significance and practical value to the production practice.

Modelling and Optimization of Machining parameters for Turning Automotive Shafts using RSM and Grey Relational Analysis

2020 ◽  
Vol 12 (4) ◽  
Author(s):  
S. Dinesh ◽  
K. Rajaguru ◽  
K. Saravanan ◽  
R. Yokeswaran ◽  
V. Vijayan
Keyword(s):  
Surface Roughness ◽  
Grey Relational Analysis ◽  
Removal Rate ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Relational Analysis ◽  
Input Parameters ◽  
Grey Relational ◽  
Central Composite ◽  
Modelling And Optimization

Automotive shafts require maximum strength with regard to axial, bending and torsional loading to transmit power to various parts of a vehicle. Hence, it is very critical to analyse the manufacturing process and its governing parameters to exercise control over the surface properties of the shaft as it needs to be precisely manufactured in terms of dimensions and the surface roughness. The effect of three input parameters over two responses are considered as two major criteria's for production of shaft. The input parameters are speed, feed and depth of cut whereas the responses are material removal rate and surface roughness. Central Composite design was used and experimental results were analysed with Response Surface Methodology. ANOVA analysis was carried out to identify the most contributing parameter for MRR and SR. Grey Relational Analysis was adopted to identify the most feasible combination of machining parameters for turning process. The optimized parameter is identified as speed of 1000 rpm, 0.15 mm of feed and 0.35 mm of depth of cut using Grey Relational Analysis.

scholarly journals Multi-objective optimization of drilling parameters for orthopaedic implants

2020 ◽  
pp. 002029402094712
Author(s):  
Parvesh Antil ◽  
Sundeep Kumar Antil ◽  
Chander Prakash ◽  
Grzegorz Królczyk ◽  
Catalin Pruncu
Keyword(s):  
Experimental Study ◽  
Material Removal Rate ◽  
Surface Finish ◽  
Grey Relational Analysis ◽  
Material Removal ◽  
Removal Rate ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Relational Analysis ◽  
Grey Relational

Titanium (Ti) and its alloys have gained immense popularity as biomaterials in recent years. Their excellent specific strength makes them outstanding materials for orthopaedic applications. However, in the orthopaedic application, precise micro-drilling (i.e. implants inserts) is required, which is very challenging for these materials. To overcome this issue, the present research proposes an experimental study corroborated with a multi-objective optimization by simulating the drilling under electric discharge machining of Ti-6Al-4V. Taguchi’s methodology–based L9 orthogonal array was used for the experimental study. Voltage, current, pulse on and pulse off were used as the input parameters for the experimental investigation. In order to achieve suitable precise drilling, the material removal rate and surface finish were used as response parameters. Here, by optimizing parameters of the precise drilling, it is possible to obtain high material removal rate and better surface finish simultaneously. The Grey relational analysis was adopted to analyse the output quality characteristics. The optimized results generated through the Grey relational analysis are highly accurate with respect to the experimental outcomes.

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