Turning Investigations on Machining of Ti64 Alloy with Different Cutting Tool Inserts

2013 ◽  
Vol 763 ◽  
pp. 1-27 ◽  
Author(s):  
S. Ramesh ◽  
L. Karunamoorthy
Keyword(s):  
Manufacturing Industry ◽  
Cutting Tools ◽  
Dimensional Accuracy ◽  
Advanced Materials ◽  
Machining Parameters ◽  
Close Proximity ◽  
Grey Relational Grade ◽  
Cylindrical Parts ◽  
Grey Relational ◽  
Machining Characteristics

Turning operation is fundamental in the manufacturing industry to produce cylindrical parts especially for producing near-nett shape, and aesthetic requirements with good dimensional accuracy. This present research chapter, an attempt has been made to investigate the machining characteristics of titanium alloys. The investigation has been carried out to measure the effect of tool flank wear, surface roughness, cutting force and temperature on different cutting tools by adopting Taguchi’s design of experiment concept. This investigation was set to analyse and develop a mathematical model using response surface methodology, fuzzy logic. The observed responses were optimized using grey relational grade algorithm. Except for a few cases, the experimental results have close proximity (95%) to the predicted value. This validates the model developed in this work. Orthogonal array with grey relational analysis has been successfully implemented for the optimization of the machining parameters. The optimized cutting conditions evolved in this research study will help to achieve better machinability of these advanced materials like titanium alloy.

An Investigation on Machining Power of EN-AC 48000 Aluminum Alloy Used in Automotive and Aerospace Industries

2009 ◽  
Vol 83-86 ◽  
pp. 704-710 ◽  
Author(s):  
H. Shahali ◽  
Hamid Zarepour ◽  
Esmaeil Soltani
Keyword(s):  
Signal To Noise Ratio ◽  
Cutting Tools ◽  
Tool Material ◽  
Polycrystalline Diamond ◽  
Dimensional Accuracy ◽  
Machining Parameters ◽  
Anova Analysis ◽  
Essential Parameter ◽  
Cutting Velocity ◽  
Coated Carbide

In this paper, the effect of machining parameters including cutting velocity, feed rate, and tool material on machining power of EN-AC 48000 aluminium alloy has been studied. A L27 Taguchi's standard orthogonal array has been applied as experimental design to investigate the effect of the factors and their interaction. Twenty seven machining tests have been accomplished with two random repetitions, resulting in fifty four experiments. EN-AC 48000 is an important alloy in automotive and aerospace industries. Machining of this alloy is of vital importance due to build-up edge and tool wear. Machining power is an essential parameter affecting the tool life, dimensional accuracy, and cutting efficiency. Three types of cutting tools including coated carbide (CD 1810), uncoated carbide (H10), and polycrystalline diamond (CD10) have been used in this study. Statistical analysis has been employed to study the effect of factors and their interactions using ANOVA analysis. Moreover, optimal factor levels have been presented using signal to noise ratio (S/N) analysis. Also, regression model have been provided to predict the machining power. Finally, the results of confirmation tests have been presented to verify and compare the adequacy of the predictive models.

Investigation of GFRP Gear Accuracy and Surface Roughness Using Taguchi and Grey Relational Analysis

2020 ◽  
Vol 19 (01) ◽  
pp. 147-165
Author(s):  
Atul Sharma ◽  
M. L. Aggarwal ◽  
Lakhwinder Singh
Keyword(s):  
Surface Roughness ◽  
Cutting Speed ◽  
Root Diameter ◽  
Cutting Fluid ◽  
Thickness Variation ◽  
Machining Parameters ◽  
Glass Fiber Reinforced ◽  
Grey Relational Grade ◽  
Optimum Response ◽  
Grey Relational

Glass fiber reinforced polymer (GFRP) composite gear is used in a number of applications where fine motion transmission and silent rotation is required. In order to increase its usage there is a need to increase the quality of gear. Shrinkage problem is associated with injection molded gear. In present case blank is prepared by injection molding and teeth are cut on gear shaper by which metrology can be controlled by optimizing the machining parameters. An analysis of variance was applied on 27 experiments to validate the process and found out that rotary feed is at rank 1 which is 0.15[Formula: see text]mm/stroke, cutting fluid ratio is at rank 2 which is 12%, cutting speed is at rank 3 which is 240 stroke/min, fluid flow rate is at rank 4 which is 30 ml/min. By using these parameters optimum performance obtained is 0.213[Formula: see text]mm root diameter deviation (RD), 0.165[Formula: see text]mm tooth thickness variation (TT) and 1[Formula: see text][Formula: see text]m roughness average (Ra) with grey relational grade of 0.8318. The optimum response provided the best value of RD, TT and Ra for the range included in experimental results which is 0.138 to 0.416[Formula: see text]mm, 0.012 to 0.187[Formula: see text]mm and 1.2 to 2.43[Formula: see text][Formula: see text]m respectively. Surface roughness improvement in this work is 49.8% higher as compared to result available in literature.

An Evaluation Method Based on Grey Relational Grade for Cutting Tool Performance in the Milling of Titanium Aircraft Components

2016 ◽  
Vol 836-837 ◽  
pp. 270-276 ◽  
Author(s):  
Yu Pei Jia ◽  
Wei Zhao ◽  
Liang Li
Keyword(s):  
Evaluation Method ◽  
Cutting Tool ◽  
Comprehensive Evaluation ◽  
Cutting Tools ◽  
Processing Route ◽  
Comprehensive Evaluation Method ◽  
Tool Performance ◽  
Evaluation Models ◽  
Grey Relational Grade ◽  
Grey Relational

Cutting tools play an important role in the cutting process of titanium aircraft components, but it is difficult to comprehensively evaluate the cutting tool performance, so the selection of appropriate cutting tool becomes extremely important. In this paper, an evaluation method using grey relational analysis for cutting tool performance was proposed. Meanwhile, in this method, a test benchmark with some typical difficult-to-machined features extracted from titanium aircraft components was designed, and the processing route was developed. Grey comprehensive evaluation models of cutting tool performance were established for the rough and finish machining respectively. Finally, the grey comprehensive evaluation models were used to evaluate the cutting tool performance in the milling experiments of the benchmarks. The results show that the grey relational comprehensive evaluation method is convenient and effective to evaluate milling tools performance for titanium aircraft components.

scholarly journals Simultaneous optimization of machine and tool parameters for EDM using WC/Co P/M electrode made with micron and nano sized particles

10.30544/582 ◽  
2021 ◽  
Author(s):  
Nadimpalli Sarada Purnima ◽  
Srinivasa Rao Pujari ◽  
Siva Prasad Dora
Keyword(s):  
Surface Roughness ◽  
Particle Size ◽  
Surface Hardness ◽  
Response Characteristic ◽  
Performance Measure ◽  
Influential Factor ◽  
Simultaneous Optimization ◽  
Machining Parameters ◽  
Grey Relational Grade ◽  
Grey Relational

Multi-response characteristic optimization is the most desired aspect of the components produced from electric discharge machining (EDM). Obtaining the optimal combination of parameters for surface roughness (SR) and micro-hardness (MH) is always a challenging task as the machining parameters favourable to one performance measure adversely affects the other. The present paper deals with the simultaneous optimization of SR and MH of D2 alloy steel during EDM with tungsten carbide (WC)/cobalt (Co) P/M electrode by considering electrode and machine tool parameters. Experimental run order was planned with Taguchi’s orthogonal arrays (OA) and in the present investigation, it is based on L18 OA. The analysis of variance (ANOVA) performed for the grey relational grade (GRG) showed that the tool parameter “particle size” (PS) is the most influential factor (61.43%) for simultaneous improvement of performance measures. The P/M electrode made of fine particle size (i.e., at nano level) has improved the process stability and reduced the arcing and short-circuiting results in reduced surface roughness. Simultaneously, the formation of the hard intermetallic phase’s viz., Fe3C, Cr23C6, W2C, Fe6W6C, and Cr2Fe14C on the EDMed surface has increased the surface hardness. The optimal set of parameters was validated through confirmation experiments.

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.

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 Measurement of Process Parameters in Magneto-Rheological Fluid Assisted Cylindrical Surface Nano Finishing Process using Grey Relational Methods

2019 ◽  
Vol 9 (2) ◽  
pp. 3394-3400
Keyword(s):  
Cylindrical Surface ◽  
Removal Rate ◽  
Work Piece ◽  
Optimum Level ◽  
304L Stainless Steel ◽  
Machining Parameters ◽  
Finishing Process ◽  
Grey Relational Grade ◽  
Magneto Rheological ◽  
Grey Relational

Techniques for the analysis of machining parameters on cylindrical surface finish of 304L stainless steel with multiple response. It depends on quadratic pattern - (GRG) Grey Relational Grade is proposed in this paper. In this work, optimized the machining parameters such as working gap, Work-Piece Speed (WPS), and wheel speed rate and flew value are concluded the various responses such as Material Removal Rate (MRR), Normal Force (F-N), and surface roughness (Ra). Optimal process parameter is determined by Taguchi concept utilizing the GRG the performance index. And value of GRG used to recognize parameters optimum level. A antecedent of Variance (ANOVA) is used to resolve the augmentation of aspect r.

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.

Multi-Objective Optimization of EDM Parameters Using Grey Relational Analysis for Titanium Alloy (Ti–6Al–4V)

2014 ◽  
Vol 592-594 ◽  
pp. 540-544 ◽  
Author(s):  
A. Palanisamy ◽  
R. Rekha ◽  
S. Sivasankaran ◽  
C. Sathiya Narayanan
Keyword(s):  
Grey Relational Analysis ◽  
Removal Rate ◽  
Electrode Wear ◽  
Machining Parameters ◽  
Relational Analysis ◽  
Grey Relational Grade ◽  
Grey Relational ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Edm Process

In this paper optimization of the electrical discharge machining (EDM) process with multiple performance characteristics based on the orthogonal array with the grey relational analysis was studied and investigated. A grey relational grade obtained from the grey relational analysis is used to solve the EDM process. Optimal machining parameters are determined by considering the grey relational grade as the performance index. The input independent parameters of peak current, pulse on time and pulse off time were examined and optimized on multiple response characters (material removal rate, electrode wear ratio and surface roughness). Experimental results have shown that machining performance in the EDM process can be improved effectively through this approach.

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.

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