scholarly journals 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

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. 

Optimization of Cutting Parameters of Multiple Performance Characteristics in End Milling of AlSi/AIN MMC – Taguchi Method and Grey Relational Analysis

2014 ◽  
Vol 68 (4) ◽  
Author(s):  
S. H. Tomadi ◽  
J. A. Ghani ◽  
C. H. Che Haron ◽  
M. S. Kasim ◽  
A. R. Daud
Keyword(s):  
Taguchi Method ◽  
Grey Relational Analysis ◽  
Volume Fraction ◽  
End Milling ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Performance Characteristics ◽  
Depth Of Cut ◽  
Relational Analysis ◽  
Grey Relational

The main objective of this paper is to investigate and optimize the cutting parameters on multiple performance characteristics in end milling of Aluminium Silicon alloy reinforced with Aluminium Nitride (AlSi/AlN MMC) using Taguchi method and Grey relational analysis (GRA). The fabrication of AlSi/AlN MMC was made via stir casting with various volume fraction of particles reinforcement (10%, 15% and 20%). End milling machining was done under dry cutting condition by using two types of cutting tool (uncoated & PVD TiAlN coated carbide). Eighteen experiments (L18) orthogonal array with five factors (type of tool, cutting speed, feed rate, depth of cut, and volume fraction of particles reinforcement) were implemented. The analysis of optimization using GRA concludes that the better results for the combination of lower surface roughness, longer tool life, lower cutting force and higher material removal could be achieved when using uncoated carbide with cutting speed 240m/min, feed 0.4mm/tooth, depth of cut 0.3mm and 15% volume fraction of AlN particles reinforcement. The study confirmed that with a minimum number of experiments, Taguchi method is capable to design the experiments and optimized the cutting parameters for these performance characteristics using GRA for this newly develop material under investigation.

Investigation of Surface Roughness and Material Removal Rate for High Speed Micro End Milling on PMMA

2015 ◽  
Vol 1115 ◽  
pp. 12-15
Author(s):  
Nur Atiqah ◽  
Mohammad Yeakub Ali ◽  
Abdul Rahman Mohamed ◽  
Md. Sazzad Hossein Chowdhury
Keyword(s):  
Surface Roughness ◽  
Material Removal Rate ◽  
Feed Rate ◽  
Material Removal ◽  
High Speed ◽  
End Milling ◽  
Removal Rate ◽  
Spindle Speed ◽  
Depth Of Cut ◽  
Micro End Milling

Micro end milling is one of the most important micromachining process and widely used for producing miniaturized components with high accuracy and surface finish. This paper present the influence of three micro end milling process parameters; spindle speed, feed rate, and depth of cut on surface roughness (Ra) and material removal rate (MRR). The machining was performed using multi-process micro machine tools (DT-110 Mikrotools Inc., Singapore) with poly methyl methacrylate (PMMA) as the workpiece and tungsten carbide as its tool. To develop the mathematical model for the responses in high speed micro end milling machining, Taguchi design has been used to design the experiment by using the orthogonal array of three levels L18 (21×37). The developed models were used for multiple response optimizations by desirability function approach to obtain minimum Ra and maximum MRR. The optimized values of Ra and MRR were 128.24 nm, and 0.0463 mg/min, respectively obtained at spindle speed of 30000 rpm, feed rate of 2.65 mm/min, and depth of cut of 40 μm. The analysis of variance revealed that spindle speeds are the most influential parameters on Ra. The optimization of MRR is mostly influence by feed rate. Keywords:Micromilling,surfaceroughness,MRR,PMMA

EXPERIMENTAL INVESTIGATION OF COCONUT OIL WITH NANOBORIC ACID DURING MILLING OF INCONEL 625 USING TAGUCHI-GREY RELATIONAL ANALYSIS

2020 ◽  
pp. 2150008
Author(s):  
T. MOHANRAJ ◽  
P. RAGAV ◽  
E. S. GOKUL ◽  
P. SENTHIL ◽  
K. S. RAGHUL ANANDH
Keyword(s):  
Surface Roughness ◽  
Grey Relational Analysis ◽  
Flank Wear ◽  
Coconut Oil ◽  
Inconel 625 ◽  
Depth Of Cut ◽  
Individual Response ◽  
Relational Analysis ◽  
Grey Relational ◽  
Taguchi’S Design Of Experiments

This study is based on Taguchi’s design of experiments along with grey relational analysis (GRA) to optimize the milling parameters to minimize surface roughness, tool wear, and vibration during machining of Inconel-625 while using coconut oil as cutting fluid (CF). The experiments were conducted based on Taguchi’s L9 orthogonal array (OA). Taguchi’s S/N was used for identifying the optimal cutting parameter for individual response. Analysis of variance (ANOVA) was employed to analyze the outcome of individual parameters on responses. The surface roughness was mostly influenced by feed. Flank wear was influenced by speed and the vibration was mostly influenced by the depth of cut as well as speed. The multi-response optimization was done through GRA. From GRA, the optimal parameters were identified. Further, nanoboric acid of 0.5 and 0.9[Formula: see text]wt.% was mixed with coconut oil to enhance lubricant properties. Coconut oil with 0.5[Formula: see text]wt.% of nanoboric acid minimizes the surface roughness and flank wear by 3.92% and 6.28% and reduces the vibration in the [Formula: see text]-axis by 4.85%. The coconut oil with 0.5[Formula: see text]wt.% of nanoboric acid performs better than coconut oil with 0.9[Formula: see text]wt.% of nano boric acid and base oil.

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 Optimization of Cutting Parameters for Milling Process of (4032) Al-Alloy using Taguchi-Based Grey Relational Analysis

2021 ◽  
Vol 17 (3) ◽  
pp. 1-12
Author(s):  
Sami Abbas Hammood
Keyword(s):  
Process Parameters ◽  
Grey Relational Analysis ◽  
End Milling ◽  
Cutting Parameters ◽  
Milling Process ◽  
Spindle Speed ◽  
Al Alloy ◽  
Relational Analysis ◽  
Grey Relational ◽  
End Milling Process

The objective of this work is to study the influence of end milling cutting process parameters, tool material and geometry on multi-response outputs for 4032 Al-alloy. This can be done by proposing an approach that combines Taguchi method with grey relational analysis. Three cutting parameters have been selected (spindle speed, feed rate and cut depth) with three levels for each parameter. Three tools with different materials and geometry have been also used to design the experimental tests and runs based on matrix L9. The end milling process with several output characteristics is solved using a grey relational analysis. The results of analysis of variance (ANOVA) showed that the major influencing parameters on multi-objective response were spindle speed and cutting tool with contribution percentage (52.75%, 24%), respectively. In addition, the optimum combination of end milling process parameters was then validated by performing confirmation tests to determine the improvement in multi-response outputs. The confirmation tests obtained a minimum (surface roughness and micro-hardness) and maximum metal removal rate with grey relational grade of 0.784 and improvement percentage of 2.3%.

scholarly journals Optimization of Multiple Roughness Characteristics for Turning of AISI 1040 Steel under Different Cutting Conditions

2017 ◽  
Vol 10 ◽  
pp. 1-10 ◽  
Author(s):  
Tanveer Haque ◽  
Shubham Kumar ◽  
Devjyoti Upadhaya ◽  
Manik Barman ◽  
Arkadeb Mukhopadhyay
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Medium Carbon Steel ◽  
Depth Of Cut ◽  
Cutting Condition ◽  
Medium Carbon ◽  
Relational Analysis ◽  
Optimal Surface ◽  
Grey Relational ◽  
Different Levels

The present work aims to optimize multiple roughness characteristics i.e. centre line average, root mean square and mean line peak spacing roughness parameters for AISI 1040 medium carbon steel for turning operation. The turning parameters considered are feed rate, depth of cut and cutting condition and are varied at three different levels. Since the present investigation considers three process parameters at three different levels, the combinations laid down in Taguchi’s L9orthogonal array is employed to carry out the experiments. Grey relational analysis is used for the optimization. Optimal surface roughness is achieved for a depth of cut of 0.4 mm, feed rate of 0.07 mm/rev and under water cooled cutting condition. Analysis of variance revealed the highest contribution from feed rate in controlling the surface roughness.

Investigation of Vibration and Surface Roughness in Micro Milling of PMMA

2012 ◽  
Vol 217-219 ◽  
pp. 2187-2193 ◽  
Author(s):  
Mohammad Yeakub Ali ◽  
A. R. Mohamed ◽  
Banu Asfana ◽  
Mohamed Lutfi ◽  
M. I. Fahmi
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
End Milling ◽  
Spindle Speed ◽  
Machining Process ◽  
Depth Of Cut ◽  
Average Surface Roughness ◽  
Average Surface ◽  
Micro End Milling ◽  
Optimum Solution

This paper presents the vibration and surface roughness issue of poly methyl methacrylate (PMMA) workpiece produced by micro end milling using integrated multi-process machine tools DT 110 (Mikrotools Inc., Singapore) with control parameter; spindle speed, feed rate, and depth of cut. The vibration was measured using accelerometer, DYTRAN Instrument and the average surface roughness Ra was measured using Wyko NT1100. The optimum solution for minimum average vibration is 64.3 Hz with spindle speed 3000 rpm, feed rate 2 mm/min, and depth of cut 1.5 μm. However, the optimum solution for minimum average surface roughness, Ra is 0.352 μm with spindle speed 2000 rpm, feed rate 2 mm/min, and depth of cut 1.5 μm. The micro end milling parameters are suitable to machine PMMA to get good precision surface roughness. The analysis revealed that the feed rate and depth of cut is the most influential parameter on vibration during machining process meanwhile for average surface roughness, Ra spindle speed is the most influential parameter.

scholarly journals Green Machining Characteristics Study of Al-6063 in CNC Milling Using Taguchi Method and Grey Relational Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
R. Suresh Kumar ◽  
S. Senthil Kumar ◽  
K. Murugan ◽  
Sintayehu Mekuria Hailegiorgis
Keyword(s):  
Grey Relational Analysis ◽  
Removal Rate ◽  
Minimum Quantity Lubrication ◽  
Spindle Speed ◽  
Depth Of Cut ◽  
Minimum Quantity ◽  
Relational Analysis ◽  
Green Machining ◽  
Multiresponse Optimization ◽  
Grey Relational

Green machining strategies in the manufacturing sector help to maintain the product value by considering the environmental impacts. Also, improvisation in the quality contribution of the parts can minimize the environmental consequences by improving resource efficiency, specifically in terms of coolants used in machining. Certain hazardous impacts have been witnessed because of longer exposure to such a machining environment. To address it, many researchers have concentrated on providing a healthy machining environment either by introducing dry machining or by minimum quantity lubrication (MQL). The proposed study addresses this context. The influence of these tactics on the attained surface quality of Al-6063 is quantified in this paper in terms of surface integrity (Ra) and removal rate of material (MRR). The study involves single-response optimization using the Taguchi design and multiresponse optimization using grey relational analysis (GRA). The results reveal that the depth of cut (Dc) and spindle speed (Ss) have the greatest impact on Ra and MRR. The machinability of Al-6063 is examined by considering the key machinability parameters, such as the spindle speed (Ss), feed rate (Fr), and the depth of cut (Dc), to arrive at the best possible surface roughness and removal rate of the material. As a typical Taguchi approach cannot perform multiresponse optimization, grey relational analysis is used. The grey relational analysis combined with Taguchi gives a novel methodology for multioptimization. The entire study is performed in dry condition and under minimum quantity lubrication. The results suggest that the responses are highly influenced by the depth of cut and spindle speed.

Parametric Optimization of CNC End Milling Process on Aluminium 6063 Alloy Using Grey Based Taguchi Method

2017 ◽  
Vol 867 ◽  
pp. 148-156
Author(s):  
Md Ashfaq Hussain ◽  
K.K. Prasad ◽  
Anil S. Jadhav ◽  
Gangadhar Biradar
Keyword(s):  
Taguchi Method ◽  
Grey Relational Analysis ◽  
End Milling ◽  
Removal Rate ◽  
Milling Process ◽  
Depth Of Cut ◽  
Relational Analysis ◽  
Response Optimization ◽  
Grey Relational ◽  
Cnc End Milling

This investigation focused on the multi-response optimization of CNC end milling of Aluminium 6063 Alloy material using Grey relational analysis and Taguchi method. Experiments were designed based on L9 Taguchi Orthogonal array, to arrive at an optimum parameter combination within the experimental domain. The spindle speed (S), feed rate (f) and depth of cut (d) which are known to have considerable effect on the selected responses i.e. surface roughness (Ra) and Material removal rate (MRR) and are considered as control parameters. The single objective optimization using Taguchi method more often results in conflicting requirements on control variables. To overcome this challenge, the Taguchi approach followed by Grey relational analysis was applied to solve this multi response optimization problem. The significance of these factors on overall quality characteristics of the milling process has also been evaluated quantitatively with the Analysis of variance method (ANOVA). Optimal results were verified through confirmation experiments. This shows feasibility of the Grey relation analysis in combination with Taguchi technique for continuous improvement in product quality in manufacturing industry and the suitability of the method to optimize the multi objective problems involved in CNC milling.

Sign in / Sign up

Export Citation Format

Share Document