Parameter Optimization of Milling Ti6Al4V Using GA Approach

2010 ◽  
Vol 426-427 ◽  
pp. 1-4 ◽  
Author(s):  
Feng Xu ◽  
Jian Jun Zhu ◽  
Xin Wu ◽  
Xiao Jun Zang ◽  
Dun Wen Zuo
Keyword(s):  
Genetic Algorithm ◽  
Titanium Alloy ◽  
Parameter Optimization ◽  
Cutting Tool ◽  
Metal Removal ◽  
Removal Rate ◽  
Metal Removal Rate ◽  
Machined Surface ◽  
Milling Parameters ◽  
Machined Surface Roughness

The research was carried out on the parameter optimization of milling titanium alloy in this paper. The cutting models including cutting force, tool life and machined surface roughness are obtained by orthogonal array experiments. The maximum metal removal rate, MRR is selected as objective function. The constraints related to machine tool, workpiece, cutting tool and other machining situations are presented in details. Genetic algorithm is used to search for the optimum milling parameters for the maximum metal removal rate of titanium alloy. The optimization results show the optimization system can improve the productivity of milling Ti6Al4V obviously.

Study on Machining Dental Implants by Whirling Approach

2011 ◽  
Vol 117-119 ◽  
pp. 1506-1513
Author(s):  
E. Hsung Cheng ◽  
Ming Jer Lin ◽  
Tung Lin Tsai ◽  
Nan Ming Yeh
Keyword(s):  
Titanium Alloy ◽  
Theoretical Analysis ◽  
Dental Implants ◽  
Dental Implant ◽  
Metal Removal ◽  
Removal Rate ◽  
Tooth Root ◽  
Metal Removal Rate ◽  
High Metal ◽  
Final Profile

A dental implant is an artificial tooth root replacement. The making of titanium alloy dental implants requires a combination of processes such as turning, milling, boring, broaching, and threading. Threading is important since the outer profile of an implant consists mostly of thread. Thread whirling is the chosen process instead of conventional threading. The procedure contains the following advantages: (1)high metal removal rate, (2)good quality, (3)obtaining final profile in one lapse, and (4)long tool life. The research focuses on all aspects of applying thread whirling on the making of dental implant, including theoretical analysis, whirling tool design, and finally cutting procedure. The machining is performed in a Swiss-type lathe, Star SR-20R.

Use of artificial neural network and multi-objective genetic algorithm approach to predict and ascertain stable cutting zone in conventional turning process

2018 ◽  
Vol 49 (5) ◽  
pp. 191-214 ◽  
Author(s):  
Shailendra Kumar ◽  
Bhagat Singh
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Artificial Neural Network ◽  
Metal Removal ◽  
Removal Rate ◽  
Metal Removal Rate ◽  
Multi Objective Genetic Algorithm ◽  
Cutting Zone ◽  
Artificial Neural ◽  
Chatter Index

This article is focused on the investigation of stable cutting zone in turning operation. Experiments have been conducted to acquire raw chatter signals. Generally, raw chatter signals are contaminated with ambient noise. Wavelet transform has been used for pre-processing and denoising these signals. In order to predict the severity of tool chatter, a new parameter denoted as chatter index has been evaluated considering the aforesaid denoised signals. In the present work, mathematical models have been developed for chatter index and metal removal rate using feedforward backpropagation–based artificial neural network considering three activation functions: TANSIG, LOGSIG and PURELIN. Furthermore, multi-objective genetic algorithm technique has been applied to evaluate stable cutting zones with maximized metal removal rate. TANSIG activation function found to be best option to achieve the aforesaid objectives. Good correlation between the artificial neural network predicted results and experimental ones validate the developed technique.

scholarly journals Experimental Investigation of Drilling Small Hole on Duplex Stainless Steel (SS2205) Using EDM

2020 ◽  
Vol 22 (1) ◽  
pp. 285-294
Author(s):  
S. Rajaram ◽  
G. RajKumar ◽  
R. Balasundaram ◽  
D. Srinivasan
Keyword(s):  
Genetic Algorithm ◽  
Stainless Steel ◽  
Duplex Stainless Steel ◽  
Metal Removal ◽  
Removal Rate ◽  
Electrical Discharge Machine ◽  
Operating Parameter ◽  
Metal Removal Rate ◽  
Spark Gap ◽  
Electric Pressure

AbstractThis work investigates drilling of small holes of Ø 3 mm on duplex Stainless Steel. Its machinability index is very low (0.66) as compared to other steels, hence Electrical Discharge Machine is used. The input parameters are Current, Spark Gap & Di electric Pressure. Each input parameter is considered for 3 levels. Therefore total number of experiments is 3×3×3 – 27. To reduce the number of runs, Taguchi L9 orthogonal array is used, which is having advantage of maximum and minimum trial runs in its design. The output response is metal removal rate. To find the best operating parameter, the regression model of ANOVA is given to input of MAT Lab-Genetic Algorithm. The experimental results indicated that models are significant. The test result indicated that the contributions of current is 42.42%, Di electric pressure is 35.36% and Spark gap is 1.93% on metal removal rate. From Genetic Algorithm it is observed among three levels of factors, lower value of current and Di electric pressure produced maximum metal removal rate. The SS 2205 has wide variety of applications such as high pressure components, control valves etc., which are having large number of components to it. Hence performing micro holes on such high hardness alloy is useful.

Ensembled local mean decomposition and genetic algorithm approach to investigate tool chatter features at higher metal removal rate

2020 ◽  
pp. 107754632097115
Author(s):  
Pankaj Gupta ◽  
Bhagat Singh
Keyword(s):  
Genetic Algorithm ◽  
Prediction Models ◽  
Metal Removal ◽  
Removal Rate ◽  
Cutting Parameters ◽  
Metal Removal Rate ◽  
Local Mean Decomposition ◽  
Local Mean ◽  
Chatter Index ◽  
Selection Of

Improper selection of cutting parameters leads to regenerative chatter and loss in productivity. In the present work, a methodology has been proposed to select a proper combination of input cutting parameters for stable turning with improved metal removal rate. Chatter signals generated during the turning of Al6061-T6 have been acquired using a microphone. Stability lobes diagram has been plotted to access the stability regime. Further, to study the effect of feed rate on stability, the recorded signals have been processed using local mean decomposition signal processing technique, followed by the selection of dominating product functions using Fourier transform. The decomposed signals have been used to evaluate the new output parameter, that is, chatter index. Prediction models of chatter index and metal removal rate have been developed. Moreover, these prediction models have been optimized using multi-objective genetic algorithm for ascertaining the optimal range of cutting parameters for stable turning with higher metal removal rate. Finally, obtained stable range has been validated by performing more experiments.

Design of a slender turning cutting tool via a vibration absorber equipped with piezoelectric ceramic

2021 ◽  
pp. 107754632110144
Author(s):  
Yiqing Yang ◽  
Haoyang Gao ◽  
Qiang Liu
Keyword(s):  
Piezoelectric Ceramic ◽  
Cutting Tool ◽  
Vibration Suppression ◽  
Equations Of Motion ◽  
Electrical Energy ◽  
Diameter Ratio ◽  
Vibration Absorber ◽  
Machined Surface ◽  
Structural Part ◽  
Machined Surface Roughness

Turning cutting tool with large length–diameter ratio has been essential when machining structural part with deep cavity and in-depth hole features. However, chatter vibration is apt to occur with the increase of tool overhang. A slender turning cutting tool with a length–diameter ratio of 7 is developed by using a vibration absorber equipped with piezoelectric ceramic. The vibration absorber has dual functions of vibration transfer to the absorber mass and vibration conversion to the electrical energy via the piezoelectric effect. Equations of motion are established considering the dual damping from the piezoelectric ceramic and rubber gasket. The equivalent damping of piezoelectric ceramic is derived, and the geometries are optimized to achieve optimal vibration suppression. The modal analysis demonstrates that the cutting tool with the vibration absorber can reach 80.1% magnitude reduction. Machining tests are carried out in the end. The machining acceleration and machined surface roughness validate the vibration suppression of the VA, and the output voltage by the piezoelectric ceramic demonstrates the ability of vibration sensing.

Quantification of tool chatter and metal removal rate using wavelet denoising and statistical approach

2018 ◽  
Vol 49 (2) ◽  
pp. 62-81 ◽  
Author(s):  
Shailendra Kumar ◽  
Bhagat Singh
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Metal Removal ◽  
Removal Rate ◽  
Statistical Significance ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Metal Removal Rate ◽  
Chatter Index ◽  
Tool Chatter

Tool chatter is an unavoidable phenomenon encountered in machining processes. Acquired raw chatter signals are contaminated with various types of ambient noises. Signal processing is an efficient technique to explore chatter as it eliminates unwanted background noise present in the raw signal. In this study, experimentally recorded raw chatter signals have been denoised using wavelet transform in order to eliminate the unwanted noise inclusions. Moreover, effect of machining parameters such as depth of cut ( d), feed rate ( f) and spindle speed ( N) on chatter severity and metal removal rate has been ascertained experimentally. Furthermore, in order to quantify the chatter severity, a new parameter called chatter index has been evaluated considering aforesaid denoised signals. A set of 15 experimental runs have been performed using Box–Behnken design of experiment. These experimental observations have been used to develop mathematical models for chatter index and metal removal rate considering response surface methodology. In order to check the statistical significance of control parameters, analysis of variance has been performed. Furthermore, more experiments are conducted and these results are compared with the theoretical ones in order to validate the developed response surface methodology model.

Multiresponse Optimization of Al Alloy-SiC Composite Machining Parameters for Minimum Tool Wear and Maximum Metal Removal Rate

2013 ◽  
Vol 135 (2) ◽  
Author(s):  
Rajesh Kumar Bhushan
Keyword(s):  
Tool Wear ◽  
Metal Removal ◽  
Removal Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Al Alloy ◽  
Machining Parameters ◽  
Metal Removal Rate ◽  
Nose Radius ◽  
Multiresponse Optimization

Optimization in turning means determination of the optimal set of the machining parameters to satisfy the objectives within the operational constraints. These objectives may be the minimum tool wear, the maximum metal removal rate (MRR), or any weighted combination of both. The main machining parameters which are considered as variables of the optimization are the cutting speed, feed rate, depth of cut, and nose radius. The optimum set of these four input parameters is determined for a particular job-tool combination of 7075Al alloy-15 wt. % SiC (20–40 μm) composite and tungsten carbide tool during a single-pass turning which minimizes the tool wear and maximizes the metal removal rate. The regression models, developed for the minimum tool wear and the maximum MRR were used for finding the multiresponse optimization solutions. To obtain a trade-off between the tool wear and MRR the, a method for simultaneous optimization of the multiple responses based on an overall desirability function was used. The research deals with the optimization of multiple surface roughness parameters along with MRR in search of an optimal parametric combination (favorable process environment) capable of producing desired surface quality of the turned product in a relatively lesser time (enhancement in productivity). The multi-objective optimization resulted in a cutting speed of 210 m/min, a feed of 0.16 mm/rev, a depth of cut of 0.42 mm, and a nose radius of 0.40 mm. These machining conditions are expected to respond with the minimum tool wear and maximum the MRR, which correspond to a satisfactory overall desirability.

scholarly journals Flow Field Simulation And Experimental Investigation On Macro Electrolyte Jet Electrochemical Turning of TB6 Titanium Alloy

2021 ◽  
Author(s):  
Yang Liu ◽  
Ningsong Qu ◽  
Zhi Qiu
Keyword(s):  
Titanium Alloy ◽  
Flow Field ◽  
Contour Error ◽  
Tool Electrode ◽  
Machined Surface ◽  
Tb6 Titanium Alloy ◽  
Machined Surface Roughness ◽  
Application Potential ◽  
Electrochemical Turning ◽  
Electrolyte Jet

Abstract Electrolyte jet electrochemical turning is an effective method to realize high-quality machining of titanium alloy rotating components; however, minimal research has been carried out in this field. This is because it is difficult to control the machining flow field, which leads to poor machining surface quality. In this work, numerical simulations were used to optimize the machining flow field and reduce the proportion of gas that mixed into the machining area. This can promote participation of the tool electrode tip in the electrochemical reaction and improve the machining efficiency. The effectiveness of the optimized machining flow field for jet electrochemical turning was verified experimentally. The results showed that all three kinds of revolving TB6 titanium alloy samples with different structures could maintain the original contour shape, with a contour error <1% and a machined surface roughness reaching Ra 2.414 μm. The results demonstrate the application potential of the jet electrochemical turning process.

Optimization of MRR and Surface Roughness of AlMg3 (AA5754) Alloy in CNC Lathe Machine by Using Taguchi Method

2018 ◽  
Vol 877 ◽  
pp. 110-117 ◽  
Author(s):  
Poornesh Kumar Chaturvedi ◽  
Harendra Kumar Narang ◽  
Atul Kumar Sahu
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
Metal Removal ◽  
Removal Rate ◽  
Surface Condition ◽  
Point Of View ◽  
Depth Of Cut ◽  
Metal Removal Rate ◽  
Cnc Lathe ◽  
Lathe Machine

Quality of the product is the major concern in manufacturing industries from customers as well as producers point of view. There are number of factors in the product such as surface condition, height, weight, length, width etc., which may be consider for the measurement of the quality. Surface roughness and Metal Removal Rate (MRR) are the two main outcomes on which numerous researchers have applied different approaches for several years to get optimum results. In this study, Taguchi Method is applied for getting optimum parameters settings for Surface roughness and Metal Removal Rate (MRR) in case of turning AlMg3 (AA5754) in CNC Lathe machine, which is an aluminum alloy having diameter 20 mm and length 100 mm. The three parameters i.e. spindle speed, feed rate and depth of cut with 3 levels are taken as the process variables and the working ranges of these parameters for conducting experiments are selected based on Taguchi’s L9 Orthogonal Array (OA) design. To analyze the significant process parameters; main effect plots for data means and for S/N ratio are generated using Minitab statistical software.

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