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.

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 Multi-response Optimization of Surface Roughness Roundness and MRR in Precision Turn-Boring of 15-5PH Stainless Steel Using Taguchi-Grey Approach

2017 ◽  
Author(s):  
Shen-Jenn Hwang ◽  
Yi-Hung Tsai
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Feed Rate ◽  
Cutting Speed ◽  
Performance Characteristics ◽  
Experimental Results ◽  
Cutting Fluid ◽  
Depth Of Cut ◽  
Fluid Temperature ◽  
Grey Relational

The present study propose an innovative turn-boring operation method and focuses on finding optimal turn-boring process parameters for 15-5PH Stainless steel by considering multiple performance characteristics using Taguchi orthogonal array with the grey relational analysis, the effect of machining variables such as concentration of cutting fluid , temperature of cutting fluid , feed rate, depth of cut and cutting speed are optimized with considerations of multiple performance characteristics namely surface roughness, roundness error and material removal rate, 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, concentration of cutting fluid, radial depth of cut and temperature of cutting fluid. Finally, confirmation tests were carried out to make a comparison between the experimental results and developed model. Experimental results have shown that machining performance in the turn-boring process can be improved effectively through this approach.

OPTIMIZATION OF TURNING PARAMETERS FOR SURFACE INTEGRITY PROPERTIES ON INCOLOY 800H SUPERALLOY USING CRYOGENICALLY TREATED MULTI-LAYER CVD COATED TOOL

2019 ◽  
Vol 26 (02) ◽  
pp. 1850139 ◽  
Author(s):  
A. PALANISAMY ◽  
T. SELVARAJ
Keyword(s):  
Process Parameters ◽  
Feed Rate ◽  
Removal Rate ◽  
Cryogenic Treatment ◽  
Cutting Speed ◽  
Dry Sliding Wear ◽  
Depth Of Cut ◽  
Cutting Condition ◽  
Machining Performance ◽  
Incoloy 800H

In this work, an attempt has been made to optimize the process parameters on turning operation of INCOLOY 800H, with the aid of cryogenically treated (24[Formula: see text]h, 12[Formula: see text]h and untreated) multi-layer chemical vapor deposition (CVD) coated tools. The influencing factors like cutting speed, feed rate, depth of cut and cryogenic treatment were selected as input parameters. Surface roughness, microhardness and material removal rate (MRR) were considered as output responses. The experimentation was planned and conducted based on Taguchi L27 standard orthogonal array (OA) with three levels and four factors. Multi-criteria decision making (MCDM) methods like grey relational analysis (GRA) and technique for order preference by similarity to ideal solution (TOPSIS) have been used to optimize the turning parameters in this work. Similar results were obtained from these MCDM techniques. Analysis of variance (ANOVA) was employed to identify the significance of the process parameters on the responses. Experimental research proved that machining performance could be improved efficiently at cutting speed is 55[Formula: see text]m/min, feed rate is 0.06[Formula: see text]mm/rev, depth of cut is 1[Formula: see text]mm and 24[Formula: see text]h cryogenically treated tool. Tool wear was analyzed for the cutting tool machined at the optimum cutting condition with the help of scanning electron microscope (SEM) and energy dispersion spectroscopy (EDS). Dry sliding wear test was also conducted for the optimal condition. The percentage improvement in machining performances is 12.70%.

scholarly journals Multiobjective Optimization of Surface Integrity in Milling TB6 Alloy Based on Taguchi-Grey Relational Analysis

2014 ◽  
Vol 6 ◽  
pp. 280313 ◽  
Author(s):  
Kaining Shi ◽  
Dinghua Zhang ◽  
Junxue Ren ◽  
Changfeng Yao ◽  
Yuan Yuan
Keyword(s):  
Surface Integrity ◽  
Grey Relational Analysis ◽  
Cutting Speed ◽  
Performance Characteristics ◽  
Depth Of Cut ◽  
Test Results ◽  
Relational Analysis ◽  
Optimum Cutting ◽  
Grey Relational Grade ◽  
Grey Relational

This paper studied an effective method based on Taguchi's method with the grey relational analysis, focusing on the optimization of milling parameters on surface integrity in milling TB6 alloy. The grey relational grade that is derived from the grey relational analysis is mainly used to determine the optimum cutting process operations with multiple performance characteristics. Specifically, surface roughness (Ra), hardness, and residual stress were important characteristics in surface integrity of milling TB6 alloy. Based on the combination of these multiple performance characteristics, the feed per tooth, cutting speed, and depth of cut were optimized in this study. Additionally, the analysis of variance (ANOVA) was also applied to determine the most significant factor for the surface integrity of milling TB6 alloy according to the contribution of the ANOVA, and the most significant factor is the cutting speed in this paper. Based on the analysis, the experimental test results have been improved prominently through the grey relational analysis. Hence this method can be an effective approach to enhance the surface integrity of milling TB6 alloy.

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 CNC Milling of Medical-Grade PMMA

2022 ◽  
Vol 12 (1) ◽  
pp. 0-0
Keyword(s):  
Feed Rate ◽  
Removal Rate ◽  
Spindle Speed ◽  
Depth Of Cut ◽  
Cnc Milling ◽  
Grey Relational Grade ◽  
Optimal Surface ◽  
Optimal Material ◽  
Grey Relational ◽  
Medical Grade

This study evaluates CNC milling parameters (spindle speed, depth of cut, and feed rate) on medical-grade PMMA. A single objective analysis conducted showed that the optimal material removal rate (MRR) occurs at a spindle speed of 1250 rpm, a depth of cut of 1.2 mm, and a feed rate of 350 mm/min. The ANOVA showed that feed rate is the most significant factor towards the MRR, and spindle speed (11.83%) is the least contributing. The optimal surface roughness (Ra) occurred at spindle speed of 500 rpm, depth of cut of 1.2 mm, and feed rate of 200 mm/min. The milling factors were insignificant. A regression analysis for prediction was also conducted. Further, a multi-objective optimization was conducted using the Grey Relational Analysis. It showed that the best trade-off between the MRR and the Ra could be obtained from a combination of 1250 rpm (spindle speed), 1.2 mm (depth of cut), and 350 mm/min (feed rate). The depth of cut was the largest contributor towards the grey relational grade (54.48%), followed by the feed rate (10.36%), and finally, the spindle speed (4.28%).

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.

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.

Performance Analysis of Trihexyltetradecylphosphonium Chloride Ionic Fluid under MQL Condition in Hard turning

2020 ◽  
Vol 17 (1) ◽  
pp. 7629-7647
Author(s):  
A. Pandey ◽  
R. Kumar ◽  
A. K. Sahoo ◽  
A. Paul ◽  
A. Panda
Keyword(s):  
Material Removal Rate ◽  
Feed Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Cutting Speed ◽  
Coconut Oil ◽  
Chip Morphology ◽  
Weight Fraction ◽  
Cutting Fluid ◽  
Depth Of Cut

The current research presents an overall performance-based analysis of Trihexyltetradecylphosphonium Chloride [[CH3(CH2)5]P(Cl)(CH2)13CH3] ionic fluid mixed with organic coconut oil (OCO) during turning of hardened D2 steel. The application of cutting fluid on the cutting interface was performed through Minimum Quantity Lubrication (MQL) approach keeping an eye on the detrimental consequences of conventional flood cooling. PVD coated (TiN/TiCN/TiN) cermet tool was employed in the current experimental work. Taguchi’s L9 orthogonal array and TOPSIS are executed to analysis the influences, significance and optimum parameter settings for predefined process parameters. The prime objective of the current work is to analyze the influence of OCO based Trihexyltetradecylphosphonium Chloride ionic fluid on flank wear, surface roughness, material removal rate, and chip morphology. Better quality of finish (Ra = 0.2 to 1.82 µm) was found with 1% weight fraction but it is not sufficient to control the wear growth. Abrasion, chipping, groove wear, and catastrophic tool tip breakage are recognized as foremost tool failure mechanisms. The significance of responses have been studied with the help of probability plots, main effect plots, contour plots, and surface plots and the correlation between the input and output parameters have been analyzed using regression model. Feed rate and depth of cut are equally influenced (48.98%) the surface finish while cutting speed attributed the strongest influence (90.1%). The material removal rate is strongly prejudiced by cutting speed (69.39 %) followed by feed rate (28.94%) whereas chip reduction coefficient is strongly influenced through the depth of cut (63.4%) succeeded by feed (28.8%). TOPSIS significantly optimized the responses with 67.1 % gain in closeness coefficient.

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