Optimization of Surface Roughness and Metal Removal Rate in End Milling using Taguchi Grey Relational Analysis

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.

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Optimum combination of process parameters to optimize Surface Roughness and Chip Thickness during End Milling of Aluminium 6351-T6 Alloy Using Taguchi Grey Relational Analysis

Independent Journal of Management & Production ◽

10.14807/ijmp.v8i2.546 ◽

2017 ◽

Vol 8 (2) ◽

pp. 287

Author(s):

Reddy Sreenivasulu

Keyword(s):

Surface Roughness ◽

Grey Relational Analysis ◽

Feed Rate ◽

End Milling ◽

Chip Thickness ◽

Optimum Combination ◽

Spindle Speed ◽

Depth Of Cut ◽

Relational Analysis ◽

Grey Relational

In any machining operations, quality is the important conflicting objective. In order to give assurance for high productivity, some extent of quality has to be compromised. Similarly productivity will be decreased while the efforts are channelized to enhance quality. In this study, the experiments were carried out on a CNC vertical machining center (KENT and INDIA Co. Ltd, Taiwan make) to perform 10mm slots on Al 6351-T6 alloy work piece by K10 carbide, four flute end milling cutter as per taguchi design of experiments plan by L9 orthogonal array was choosen to determine experimental trials. Furthermore the spindle speed (rpm), the feed rate (mm/min) and depth of cut (mm) are regulated in these experiments. Surface roughness and chip thickness was measured by a surface analyser of Surf Test-211 series (Mitutoyo) and Digital Micrometer (Mitutoyo) with least count 0.001 mm respectively. Grey relational analysis was employed to minimize surface roughness and chip thickness by setting of optimum combination of machining parameters. Minimum surface roughness and chip thickness obtained with 1000 rpm of spindle speed, 50 mm/min feed rate and 0.7 mm depth of cut respectively. Confirmation experiments showed that Gray relational analysis precisely optimized the drilling parameters in drilling of Al 6351-T6 alloy.

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

International Journal of Vehicle Structures and Systems ◽

10.4273/ijvss.12.4.04 ◽

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.

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

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.799-800.388 ◽

2015 ◽

Vol 799-800 ◽

pp. 388-392 ◽

Cited By ~ 1

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.

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

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.852.198 ◽

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.

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Multi objective Optimization of Turning Process Parameters at Different Conditions of Coolant Flow Rate

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.k1583.1081219 ◽

2019 ◽

Vol 8 (12) ◽

pp. 3109-3113

Keyword(s):

Surface Roughness ◽

Metal Removal ◽

Removal Rate ◽

Cutting Speed ◽

Material Strength ◽

Metal Removal Rate ◽

Good Creep Resistance ◽

Grey Relational ◽

Parameter Values ◽

Super Alloy

AA6064 is the most used nickel based super alloy. It is having high material strength, hardness and resistance to corrosion with good creep resistance. These properties in AA6064 is an attractive material and it is most commonly used in aerospace, gas turbine, marine and oil industries In this project machining of AA6064 is considered for the study. In these works three factors, cutting Speed (N), DOC (d), feed rate (f) are considered as parameters and their effect on metal removal rate (MRR) and surface roughness (SR) is studied through experimental investigation. The search for the optimal limited number of experimental runs, Taguchi’s orthogonal array L9 is used. In this three factors with three levels are considered to conduct the experiments and these experiments are conducted with three different conditions of coolant. Totally 27 experiments are conducted. Grey relational analysis employed to identify optimal combinational of process parameter values that minimize the surface roughness and maximize the metal removal rate..

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Optimization of Cutting Parameters for Desirable Surface Roughness in End-Milling Hardened AISI H13 Steel under a Certain Metal Removal Rate

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.188.307 ◽

2011 ◽

Vol 188 ◽

pp. 307-313 ◽

Cited By ~ 2

Author(s):

Tong Chao Ding ◽

Song Zhang ◽

Z.M. Li ◽

Yuan Wei Wang

Keyword(s):

Surface Roughness ◽

Metal Removal ◽

End Milling ◽

Removal Rate ◽

Cutting Parameters ◽

Depth Of Cut ◽

Metal Removal Rate ◽

H13 Steel ◽

Orthogonal Experiments ◽

Aisi H13

In this paper, the orthogonal experiments and the optimization experiments with the same metal removal rate are designed to investigate the main effects and primary interaction of cutting parameters on surface roughness and to search the optimal cutting parameter under a certain removal rate when end-milling hardened AISI H13 steel with the PVD coated carbide insert. The empirical model for surface roughness based on the orthogonal experiments and the optimization experiments with the same metal removal rate and the optimal cutting parameter were all verified. Under a certain metal removal rate, the combination of high cutting speed, small axial depth of cut and high feed, small radial depth of cut generates the best surface roughness in hard milling of AISI H13.

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