Influence of Tool Nose Radius and Cutting Performance during Face Milling of Magnesium Alloy for Output Responses by Taguchi based Grey Relation Analysis

2021 ◽  
Vol 13 (2) ◽  
Author(s):  
Durai Kumaran ◽  
S.P. Sundar Singh Sivam ◽  
Harshavardhana Natarajan ◽  
P.R. Shobana Swarna Ratna
Keyword(s):  
Removal Rate ◽  
Cutting Speed ◽  
Face Milling ◽  
Machining Process ◽  
Tool Geometry ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
New Approach ◽  
Grey Relational Grade ◽  
Grey Relational

In order to take advantage of the machining characteristics of magnesium, it is useful to consider recommended tool design and angles. The geometry of the tool can have a large influence on the machining process. Tool geometry can be used to aid with chip flow and clearance, reduce excessive heat generation, reduce tool build up, enable greater feed rates to be employed and improved tool life. This paper presents a new approach for the optimization of machining parameters on face milling of ZE41 with multiple responses based on orthogonal array with grey relational analysis. Machining tests are carried out by inserting 12 mm diameter of insert having 1 flute under dry condition. In this study, machining parameters namely cutting speed, feed and depth of cut and tool node radius are optimized with the considerations of multi responses such as surface roughness, material removal rate, tool wear and thrust force. A grey relational grade is obtained from the grey analysis. Based on the grey relational grade, optimum levels of parameters have been identified and significant contribution of parameters is determined by ANOVA. Confirmation test is conducted to validate the test result. Experimental results have shown that the responses in Machining process can be improved effectively through the new approach.

The Use of the Taguchi-Grey Based to Optimize High Speed End Milling with Multiple Performance Characteristics

2006 ◽  
Vol 505-507 ◽  
pp. 835-840 ◽  
Author(s):  
Shen Jenn Hwang ◽  
Yunn Lin Hwang ◽  
B.Y. Lee
Keyword(s):  
High Speed ◽  
End Milling ◽  
Removal Rate ◽  
Cutting Speed ◽  
Performance Characteristics ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Machining Performance ◽  
Grey Relational Grade ◽  
Grey Relational

This paper presents a new approach for the optimization of the high speed machining (HSM) process with multiple performance characteristics based on the orthogonal array with the grey relational analysis has been studied. Optimal machining parameters can then be determined by the grey relational grade as the performance index. In this study, the machining parameters such as cutting speed, feed rate and axial depth of cut are optimized under the multiple performance characteristics including, tool life, surface roughness, and material removal rate(MMR). As shown experimental results, machining performance in the HSM process can be improved effectively through this approach.

scholarly journals Multiple Response Optimization of machining parameters on turning of AA 6063 T6 aluminum alloy which established on Taguchi L9 orthogonal array coupled with Grey relational analysis

2021 ◽  
pp. 974-982
Author(s):  
D. S. Sai Ravi Kiran ◽  
Sanapala Sri Ram ◽  
Tangeti Bhaskararao ◽  
Boddu Eswar Venkat Sai ◽  
Kari Suraj Kumar ◽  
...  
Keyword(s):  
Aluminum Alloy ◽  
Orthogonal Array ◽  
Removal Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Dry Cutting ◽  
Grey Relational Grade ◽  
Grey Relational

With numerous responses established on Taguchi L9, orthogonal array coupled with current work proposes a novel methodology for optimizing machining parameters on turning of AA 6063 T6 aluminum alloy. Experimental assessments are accomplished on AA 6063 T6 aluminum alloy. Turning trails are carried out under dry cutting conditions using an uncoated carbide insert. Cutting parameters such as cutting speed, feed rate, and depth of cut are optimized in this effort while numerous responses such as surface roughness(Ra) and material removal rate are taken into consideration (MRR). From the grey analysis, a grey relational grade(GRG) is calculated. The optimal amounts of parameters have been identified based on the values of grey relational grade, and then ANOVA is used to determine the significant influence of parameters. To authenticate the test result, a confirmation test is executed. The result of the experiments shows that by using this method. the turning process responses can be significantly improved.

scholarly journals Multi-Response Optimization of Face Milling Performance Considering Tool Path Strategies in Machining of Al-2024

Materials ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 1013 ◽  
Author(s):  
Raneen Ali ◽  
Mozammel Mia ◽  
Aqib Khan ◽  
Wenliang Chen ◽  
Munish Gupta ◽  
...  
Keyword(s):  
Tool Path ◽  
Removal Rate ◽  
Cutting Speed ◽  
Milling Process ◽  
Face Milling ◽  
Depth Of Cut ◽  
Cutter Path ◽  
Response Optimization ◽  
Grey Relational ◽  
Al 2024

It is hypothesized that the orientation of tool maneuvering in the milling process defines the quality of machining. In that respect, here, the influence of different path strategies of the tool in face milling is investigated, and subsequently, the best strategy is identified following systematic optimization. The surface roughness, material removal rate and cutting time are considered as key responses, whereas the cutting speed, feed rate and depth of cut were considered as inputs (quantitative factors) beside the tool path strategy (qualitative factor) for the material Al 2024 with a torus end mill. The experimental plan, i.e., 27 runs were determined by using the Taguchi design approach. In addition, the analysis of variance is conducted to statistically identify the effects of parameters. The optimal values of process parameters have been evaluated based on Taguchi-grey relational analysis, and the reliability of this analysis has been verified with the confirmation test. It was found that the tool path strategy has a significant influence on the end outcomes of face milling. As such, the surface topography respective to different cutter path strategies and the optimal cutting strategy is discussed in detail.

Analysis and optimisation of machinability behaviour of CFRP composites using fuzzy logic

2015 ◽  
Vol 44 (1) ◽  
pp. 48-55 ◽  
Author(s):  
M.P. Jenarthanan ◽  
R. Jeyapaul
Keyword(s):  
Fuzzy Logic ◽  
Taguchi Method ◽  
Removal Rate ◽  
Performance Characteristics ◽  
Machining Process ◽  
Tool Geometry ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Content Type ◽  
Cfrp Composites

Purpose – The purpose of this paper is to analyse and optimise the machinability behaviour of Carbon Fibre Reinforced Polymer (CFRP) composites with multiple performance characteristics using the Taguchi method with fuzzy logic. Design/methodology/approach – A multi-response performance index (MRPI) was used for optimisation. The machining parameters, viz., tool geometry (helix angle of the endmill cutter), spindle speed, feed rate and depth of cut, were optimised with consideration of multiple performance characteristics, viz., machining force and material removal rate. Findings – The results from confirmation runs indicated that the determined optimal combination of machining parameters improved the performance of the machining process. Originality/value – The machinability behaviour of CFRP composites during milling of CFRP composites using Taguchi method with fuzzy logic has not been previously analysed.

Optimisation of Machining Parameters for High Feed End Milling on Inconel 718 Super Alloy

2014 ◽  
Vol 592-594 ◽  
pp. 584-590 ◽  
Author(s):  
Vinay Varghese ◽  
K. Annamalai ◽  
K. Santhosh Kumar
Keyword(s):  
Inconel 718 ◽  
End Milling ◽  
Removal Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Milling Operation ◽  
High Feed ◽  
Grey Relational ◽  
Super Alloy

This study investigates about machining practices used worldwide for machining of Inconel 718 super alloy. The effect of machining parameters like cutting speed, feed and depth of cut on machining responses like surface roughness and material removal rate when end milling Inconel 718 is studied using nine trials carried out based on L9 orthogonal array. A Taguchi based grey relational analysis was used for optimisation of machining parameters for high feed end milling operation on Inconel 718. An analysis of variance (ANOVA) was used to find the most significant factor. Validation of results through confirmation tests was performed and experimental results show that surface quality and productivity can be improved efficiently with this approach.

Selecting Significant Process Parameters of ECG Process Using Fuzzy-MCDM Technique

2015 ◽  
Vol 2 (1) ◽  
pp. 38-53 ◽  
Author(s):  
Goutam Kumar Bose
Keyword(s):  
Surface Roughness ◽  
Removal Rate ◽  
Multiple Criteria Decision Making ◽  
Lower Surface ◽  
Substantial Improvement ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Machining Performance ◽  
Grey Relational Grade ◽  
Grey Relational

The present paper highlights selection of significant machining parameters during Electrochemical grinding while machining alumina-aluminum interpenetrating phase composites by MCDM techniques. The conflicting responses like higher material removal rate, lower surface roughness, lower overcut and lower cutting force are ensured simultaneously by a single parametric combination. Control parameters like electrolyte concentration, voltage, depth of cut and electrolyte flow rate have been considered for experimentation. VIKOR is one of the multiple criteria decision making (MCDM) models to determine the reference ranking from a set of alternatives in the presence of conflicting criteria. Finally Grey Relational Analysis is performed to optimize multiple performances in which different levels combinations of the factors are ranked based on grey relational grade. Surface roughness is given more importance than other responses, using Fuzzy Set Theory considering basic objective of the process. It is observed that substantial improvement in machining performance takes place following this technique. The study highlights the effects of different process variables on multiple performances for complex process like ECG.

scholarly journals Optimal Machining Parameters for Achieving the Desired Surface Roughness in Turning of Steel

2012 ◽  
Vol 9 (1) ◽  
pp. 37 ◽  
Author(s):  
LB Abhang ◽  
M Hameedullah
Keyword(s):  
Surface Roughness ◽  
Surface Finish ◽  
Metal Cutting ◽  
Cutting Speed ◽  
Cutting Conditions ◽  
Machining Process ◽  
Tool Geometry ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Engineering Sciences

 Due to the widespread use of highly automated machine tools in the metal cutting industry, manufacturing requires highly reliable models and methods for the prediction of output performance in the machining process. The prediction of optimal manufacturing conditions for good surface finish and dimensional accuracy plays a very important role in process planning. In the steel turning process the tool geometry and cutting conditions determine the time and cost of production which ultimately affect the quality of the final product. In the present work, experimental investigations have been conducted to determine the effect of the tool geometry (effective tool nose radius) and metal cutting conditions (cutting speed, feed rate and depth of cut) on surface finish during the turning of EN-31 steel. First and second order mathematical models are developed in terms of machining parameters by using the response surface methodology on the basis of the experimental results. The surface roughness prediction model has been optimized to obtain the surface roughness values by using LINGO solver programs. LINGO is a mathematical modeling language which is used in linear and nonlinear optimization to formulate large problems concisely, solve them, and analyze the solution in engineering sciences, operation research etc. The LINGO solver program is global optimization software. It gives minimum values of surface roughness and their respective optimal conditions. 

Multi-Objective Optimization using Grey Relational Taguchi Analysis in Machining

2016 ◽  
Vol 6 (4) ◽  
pp. 45-64 ◽  
Author(s):  
Nirmal S. Kalsi ◽  
Rakesh Sehgal ◽  
Vishal S. Sharma
Keyword(s):  
Metal Cutting ◽  
Removal Rate ◽  
Cutting Tools ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Recent Approach ◽  
Grey Relational

Multi-objective optimization is becoming important day by day due to increase in complexity of the processes and expectations of more reliable solutions. In view of the complexity of the process, controlling the machining parameters without compromising on the response parameters is a tedious process. In the recent approach, researchers have used many combinations of available techniques to solve multi performance characteristic problems depending upon the situation and accuracy desired in the results, to make the results more reliable. In this paper, the authors have pronounced and used a combination of grey relational and Taguchi based analysis to optimize a multi-objective metal cutting process to yield maximum performance of cutting tools in turning. Main cutting force, power consumption, tool wear and material removal rate were evaluated used L18 orthogonal array considering cutting speed, feed rate and depth of cut, using cryogenically treated and untreated tungsten carbide cutting tool inserts.

scholarly journals Multi-Objective Optimization of in Precision Turn-Boring Parameters for AA7050-T7451 with Multiple Performance Characteristics

2017 ◽  
Author(s):  
Shen Jenn Hwang ◽  
Yi-Hung Tsai
Keyword(s):  
Feed Rate ◽  
Removal Rate ◽  
Cutting Speed ◽  
Performance Characteristics ◽  
Experimental Results ◽  
Depth Of Cut ◽  
Machining Performance ◽  
Radial Depth ◽  
Grey Relational Grade ◽  
Grey Relational

The present study propose an innovative turn-boring operation method and focuses on finding optimal turn-boring process parameters for AA7050-T7451 by considering multiple performance characteristics using Taguchi orthogonal array with the grey relational analysis, the effect of cutting variables such as, feed rate, depth of cut and cutting speed are optimized with considerations of multiple performance characteristics namely surface roughness, roundness error, material removal rate and power consumption the optimal values were found out from the Grey relational grade. The result of the Analysis of Variances (ANOVA) is proved that the most significant factor is cutting speed, followed by feed rate, radial depth of cut. Finally, confirmation tests were performed to make a comparison between the experimental results. Experimental results have shown that machining performance in precision turn-boring process can be improved effectively through this approach

scholarly journals Multi-Optimization of Performance Parameters in Turn-Boring for Difficult-to-Cut Ti-6Al-4V

2017 ◽  
Author(s):  
Shen-Jenn Hwang ◽  
Xin-Tang Li
Keyword(s):  
Feed Rate ◽  
Removal Rate ◽  
Cutting Speed ◽  
Performance Characteristics ◽  
Experimental Results ◽  
Depth Of Cut ◽  
Machining Performance ◽  
Radial Depth ◽  
Grey Relational Grade ◽  
Grey Relational

The present study propose an innovative turn-boring operation method and focuses on finding optimal turn-boring process parameters for Ti-6Al-4V by considering multiple performance characteristics using Taguchi orthogonal array with the grey relational analysis, the effect of machining variables such as, feed rate, depth of cut and cutting speed are optimized with considerations of multiple performance characteristics namely surface roughness, roundness error, material removal rate and power consumption the optimal values were found out from the Grey relational grade. The result of the Analysis of Variances (ANOVA) is shown that the most significant factor is cutting speed, followed by feed rate, radial depth of cut. Finally, confirmation tests were carried out to make a comparison between the experimental results. Experimental results have shown that machining performance in the turn-boring process can be improved effectively through this approach.

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