Optimal Cutting Parameters for Desired Surface Roughness in End Milling Inconel 718

2010 ◽  
Vol 126-128 ◽  
pp. 911-916 ◽  
Author(s):  
Yuan Wei Wang ◽  
Song Zhang ◽  
Jian Feng Li ◽  
Tong Chao Ding

In this paper, Taguchi method was applied to design the cutting experiments when end milling Inconel 718 with the TiAlN-TiN coated carbide inserts. The signal-to-noise (S/N) ratio are employed to study the effects of cutting parameters (cutting speed, feed per tooth, radial depth of cut, and axial depth of cut) on surface roughness, and the optimal combination of the cutting parameters for the desired surface roughness is obtained. An exponential regression model for the surface roughness is formulated based on the experimental results. Finally, the verification tests show that surface roughness generated by the optimal cutting parameters is really the minimum value, and there is a good agreement between the predictive results and experimental measurements.

2011 ◽  
Vol 188 ◽  
pp. 410-415 ◽  
Author(s):  
Yuan Wei Wang ◽  
Jian Feng Li ◽  
Z.M. Li ◽  
Tong Chao Ding ◽  
Song Zhang

In this paper, some experiments were conducted to investigate tool wear when end-milling Inconel 718 with the TiAlN-TiN PVD coated carbide inserts. The worn tools were examined thoroughly under scanning electron microscope (SEM) with Energy Dispersive X-ray Spectroscopy and 3D digital microscope to expatiate tool wear morphologies and relevant mechanisms. The flank wear was uniformity in finishing milling process, and the average flank wear were selected as the criterion to study the effects of cutting parameters (cutting speed, feed per tooth, radial depth of cut, and axial depth of cut) on tool wear. Finally, the optimal combination of the cutting parameters for the desired tool life is obtained.


2012 ◽  
Vol 576 ◽  
pp. 60-63 ◽  
Author(s):  
N.A.H. Jasni ◽  
Mohd Amri Lajis

Hard milling of hardened steel has wide application in mould and die industries. However, milling induced surface finish has received little attention. An experimental investigation is conducted to comprehensively characterize the surface roughness of AISI D2 hardened steel (58-62 HRC) in end milling operation using TiAlN/AlCrN multilayer coated carbide. Surface roughness (Ra) was examined at different cutting speed (v) and radial depth of cut (dr) while the measurement was taken in feed speed, Vf and cutting speed, Vc directions. The experimental results show that the milled surface is anisotropic in nature. Surface roughness values in feed speed direction do not appear to correspond to any definite pattern in relation to cutting speed, while it increases with radial depth-of-cut within the range 0.13-0.24 µm. In cutting speed direction, surface roughness value decreases in the high speed range, while it increases in the high radial depth of cut. Radial depth of cut is the most influencing parameter in surface roughness followed by cutting speed.


2013 ◽  
Vol 589-590 ◽  
pp. 76-81
Author(s):  
Fu Zeng Wang ◽  
Jun Zhao ◽  
An Hai Li ◽  
Jia Bang Zhao

In this paper, high speed milling experiments on Ti6Al4V were conducted with coated carbide inserts under a wide range of cutting conditions. The effects of cutting speed, feed rate and radial depth of cut on the cutting forces, chip morphologies as well as surface roughness were investigated. The results indicated that the cutting speed 200m/min could be considered as a critical value at which both relatively low cutting forces and good surface quality can be obtained at the same time. When the cutting speed exceeds 200m/min, the cutting forces increase rapidly and the surface quality degrades. There exist obvious correlations between cutting forces and surface roughness.


2011 ◽  
Vol 325 ◽  
pp. 418-423 ◽  
Author(s):  
Song Zhang ◽  
Jian Feng Li

Surface roughness plays a significant role in machining industry for proper planning of process system and optimizing the cutting conditions. In this paper, a back-propagation neural network (BPNN) model has been developed for the prediction of surface roughness in end milling process. A large number of milling experiments were conducted on Ti-6Al-4V alloy using the uncoated carbide tools. Four cutting parameters including cutting speed, feed per tooth, radial depth of cut, and axial depth of cut are used as the inputs to develop the BPNN model, while surface roughness corresponding to these combinations of different cutting parameters is the output of the neural network model. The performance of the trained BPNN model has been verified with the experimental results, and it is found that the BPNN predicted and the experimental values are very close to each other.


2011 ◽  
Vol 264-265 ◽  
pp. 1193-1198
Author(s):  
Mokhtar Suhaily ◽  
A.K.M. Nurul Amin ◽  
Anayet Ullah Patwari

Surface finish and dimensional accuracy is one of the most important requirements in machining process. Inconel 718 has been widely used in the aerospace industries. High speed machining (HSM) is capable of producing parts that require little or no grinding/lapping operations within the required machining tolerances. In this study small diameter tools are used to achieve high rpm to facilitate the application of low values of feed and depths of cut to investigate better surface finish in high speed machining of Inconel 718. This paper describes mathematically the effect of cutting parameters on Surface roughness in high speed end milling of Inconel 718. The mathematical model for the surface roughness has been developed in terms of cutting speed, feed rate, and axial depth of cut using design of experiments and the response surface methodology (RSM). Central composite design was employed in developing the surface roughness models in relation to primary cutting parameters. Machining were performed using CNC Vertical Machining Center (VMC) with a HES510 high speed machining attachment in which using a 4mm solid carbide fluted flat end mill tool. Wyko NT1100 optical profiler was used to measure the definite machined surface for obtaining the surface roughness data. The predicted results are in good agreement with the experimental one and hence the model can be efficiently used to predict the surface roughness value with in the specified cutting conditions limit.


2014 ◽  
Vol 800-801 ◽  
pp. 590-595
Author(s):  
Qing Zhang ◽  
Song Zhang ◽  
Jia Man ◽  
Bin Zhao

Surface roughness has a significant effect on the performance of machined components. In the present study, a total of 49 end milling experiments on AISI H13 steel are conducted. Based on the experimental results, the signal-to-noise (S/N) ratio is employed to study the effects of cutting parameters (axial depth of cut, cutting speed, feed per tooth and radial depth of cut) on surface roughness. An ANN predicting model for surface roughness versus cutting parameters is developed based on the experimental results. The testing results show that the proposed model can be used as a satisfactory prediction for surface roughness.


2010 ◽  
Vol 135 ◽  
pp. 96-101 ◽  
Author(s):  
Xiao Li Zhu ◽  
Song Zhang ◽  
Tong Chao Ding ◽  
Yuan Wei Wang

The experimental study presented in this paper aims to investigate the effects of cutting parameters on cutting forces, and search the optimal cutting parameters for the minimum cutting forces during turning Inconel 718 under dry cutting conditions. Based on Taguchi method, a L25 (53) array was designed to conduct the turning experiments. The experimental results indicate that the best condition for the minimum cutting force components is the combination of 45m/min cutting speed, 0.08mm/r feed rate, and 0.2mm depth of cut. The effects of the cutting parameters on cutting forces are investigated while employing the analysis of variance (ANOVA). Finally, the quadratic regression equations for cutting forces were formulated, which can well describe the relationship between cutting parameters and cutting forces.


2011 ◽  
Vol 264-265 ◽  
pp. 888-893
Author(s):  
Mokhtar Suhaily ◽  
A.K.M. Nurul Amin ◽  
Anayet Ullah Patwari

Surface finish and dimensional accuracy is one of the most important requirements in machining process. Inconel 718 has been widely used in the aerospace industries. High speed machining (HSM) is capable of producing parts that require little or no grinding/lapping operations within the required machining tolerances. In this study small diameter tools are used to achieve high rpm to facilitate the application of low values of feed and depths of cut to investigate better surface finish in high speed machining of Inconel 718. This paper describes mathematically the effect of cutting parameters on Surface roughness in high speed end milling of Inconel 718. The mathematical model for the surface roughness has been developed in terms of cutting speed, feed rate, and axial depth of cut using design of experiments and the response surface methodology (RSM). Central composite design was employed in developing the surface roughness models in relation to primary cutting parameters. Machining were performed using CNC Vertical Machining Center (VMC) with a HES510 high speed machining attachment in which using a 4mm solid carbide fluted flat end mill tool. Wyko NT1100 optical profiler was used to measure the definite machined surface for obtaining the surface roughness data. The predicted results are in good agreement with the experimental one and hence the model can be efficiently used to predict the surface roughness value with in the specified cutting conditions limit.


2013 ◽  
Vol 690-693 ◽  
pp. 2403-2407
Author(s):  
Tong Chao Ding

In the present study, an attempt has been made to experimentally investigate the effects of the cutting parameters on cutting forces in hard milling of AISI H13 steel with coated carbide tools. Designed based on Taguchi method, four factor (cutting speed, feed, radial depth of cut and axial depth of cut) four level orthogonal experiments were conducted. Three components of cutting forces were measured during hard milling experiments and then variance analysis was performed. Finally, the linear regression model was established.


2011 ◽  
Vol 264-265 ◽  
pp. 1154-1159
Author(s):  
Anayet Ullah Patwari ◽  
A.K.M. Nurul Amin ◽  
S. Alam

Titanium alloys are being widely used in the aerospace, biomedical and automotive industries because of their good strength-to-weight ratio and superior corrosion resistance. Surface roughness is one of the most important requirements in machining of Titanium alloys. This paper describes mathematically the effect of cutting parameters on Surface roughness in end milling of Ti6Al4V. The mathematical model for the surface roughness has been developed in terms of cutting speed, feed rate, and axial depth of cut using design of experiments and the response surface methodology (RSM). Central composite design was employed in developing the surface roughness models in relation to primary cutting parameters. The experimental results indicate that the proposed mathematical models suggested could adequately describe the performance indicators within the limits of the factors that are being investigated. The developed RSM is coupled as a fitness function with genetic algorithm to predict the optimum cutting conditions leading to the least surface roughness value. MATLAB 7.0 toolbox for GA is used to develop GA program. The predicted results are in good agreement with the experimental one and hence the model can be efficiently used to achieve the minimum surface roughness value.


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