Experimental Study on Milling Hardened SKD Steel Using Micro CBN Ball-End Mills

2010 ◽  
Vol 126-128 ◽  
pp. 773-778
Author(s):  
Yung Tien Liu ◽  
Neng Hsin Chiu ◽  
Yen Chun Lin ◽  
Chih Liang Lai ◽  
Yu Fu Lin ◽  
...  
Keyword(s):  
Surface Roughness ◽  
End Milling ◽  
Milling Process ◽  
Micro Milling ◽  
Depth Of Cut ◽  
Machining Accuracy ◽  
Machining Parameters ◽  
Machined Surface ◽  
Performance Function ◽  
End Mills

Micro ball-end milling process features the ability of machining complex surfaces, precision machining accuracy, and excellent machined surface roughness. However, because the diameter of a micro milling tool is very small, a rapid progress of tool wear or even tool breakage usually happens when machining a high-strength hardened mold steel using improper machining parameters. As a result, the machining cost would rise due to the quality defect in machined workpiece. In this study, to investigate how the machining parameters affect the cutting behaviors, a series of experiments using micro CBN ball-end mills with a diameter of 0.5 mm were performed to cut the SKD11 mold steel with hardness of HRC 61. The machining parameters are selected as the feeding speed (f) being 840, 960 and 1,080 mm/min, depth of cut (ap) being 30, 45, 60 μm, and spindle speed (vs) being fixed as 30,000 rpm. According to the experimental results, the measured three-axis cutting forces, flank wears, and surface roughness of machined workpiece are highly related to the cutting length. It is expected that the measured results can be used to construct a performance function of a micro ball-end tool. With referring to the performance function, the tool life can be well expected, and thus a progress in machining efficiency without tool failure can be achieved.

Study on the Machined Surface Geometry Generated by Multi-Axis Ball End Milling Process

2013 ◽  
Vol 770 ◽  
pp. 370-375
Author(s):  
Xiao Xiao Chen ◽  
Jun Zhao ◽  
Yong Wang Dong ◽  
Shuai Liu ◽  
Jia Bang Zhao
Keyword(s):  
Surface Roughness ◽  
End Milling ◽  
Cutting Parameters ◽  
Peak Height ◽  
Milling Process ◽  
Depth Of Cut ◽  
Small Range ◽  
Surface Geometry ◽  
Machined Surface ◽  
Two Parameters

This paper investigated the surface generated by single factor experiment under multi-axis finish milling condition, and the effects of cutting parameters on surface textures, 2D and 3D surface topographies and surface roughness characteristics were analyzed. Surface features evaluation indicators of Ra, Rq, Rt, surface heights histogram, maximum valley depth and maximum peak height corresponding to various cutting parameters were presented and discussed. The machining marks are closely related with tool orientation angles. The orderly distributions of concave and convex patterns on the machined surface are produced by the special cutting orientation of the cutting edges. The feed per tooth, spindle speed, tilt angle, and lead angle apparently affect surface roughness, while depth of cut and radial width of cut have no obvious effects on the surface roughness when the two parameters values vary in a small range.

scholarly journals Prediction of Surface Roughness in End Milling Process Using Intelligent Systems: A Comparative Study

2011 ◽  
Vol 2011 ◽  
pp. 1-18 ◽  
Author(s):  
Abdel Badie Sharkawy
Keyword(s):  
Surface Roughness ◽  
Prediction Accuracy ◽  
End Milling ◽  
Milling Process ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Validation Data ◽  
Genetic Tuning ◽  
Inference Systems ◽  
End Milling Process

A study is presented to model surface roughness in end milling process. Three types of intelligent networks have been considered. They are (i) radial basis function neural networks (RBFNs), (ii) adaptive neurofuzzy inference systems (ANFISs), and (iii) genetically evolved fuzzy inference systems (G-FISs). The machining parameters, namely, the spindle speed, feed rate, and depth of cut have been used as inputs to model the workpiece surface roughness. The goal is to get the best prediction accuracy. The procedure is illustrated using experimental data of end milling 6061 aluminum alloy. The three networks have been trained using experimental training data. After training, they have been examined using another set of data, that is, validation data. Results are compared with previously published results. It is concluded that ANFIS networks may suffer the local minima problem, and genetic tuning of fuzzy networks cannot insureperfectoptimality unless suitable parameter setting (population size, number of generations etc.) and tuning range for the FIS, parameters are used which can be hardly satisfied. It is shown that the RBFN model has the best performance (prediction accuracy) in this particular case.

Cutting Parameters Impacting on Tool Wear in Micro End-milling of Tool Steel

2018 ◽  
Author(s):  
Cínthia Soares Manso ◽  
Cleiton Lazaro Fazolo de Assis ◽  
Luciana Wasnievski da Silva de Luca Ramos ◽  
Erik Gustavo Del Conte
Keyword(s):  
Tool Wear ◽  
Tool Steel ◽  
End Milling ◽  
Cutting Parameters ◽  
Milling Process ◽  
Micro Milling ◽  
Depth Of Cut ◽  
Nose Radius ◽  
Machined Surface ◽  
Tool Diameter

In micro milling process, the quick wear and premature breakage of tools configure a problem that affects not only the process costs but also the manufacturing quality. This work investigates the influence of the cutting parameters on tool wear and surface roughness in a dry machining of a tool steel H13 workpiece (X40CrMoV5-1). Spindle speed was kept constant (27200 rpm) and two feeds per tooth were applied (1.5 and 3.0 µm) as depth of cut (25 and 30 µm), and variating cut length as well. The wear of the tool top area, tool diameter and nose radius were monitored during micro milling tests. Roughness was evaluated by using a Laser Confocal Microscope. The lower level of feed per tooth and depth of cut showed lower roughness, but a higher tool wear. A balance between cutting parameters and cutting length must be considered to ensure micromachining without severe tool wear and preserve microchannel features along its machined surface.

Surface Roughness Model for High Speed End Milling of Soda Lime Glass Using Carbide Coated Tools with Compressed Air Blowing

2012 ◽  
Vol 576 ◽  
pp. 107-110
Author(s):  
M.A. Mahmud ◽  
A.K.M. Nurul Amin ◽  
Muammer Din Arif
Keyword(s):  
Mathematical Model ◽  
Surface Roughness ◽  
Gas Turbines ◽  
High Speed ◽  
End Milling ◽  
Soda Lime ◽  
Depth Of Cut ◽  
Soda Lime Glass ◽  
Machining Parameters ◽  
Machined Surface

Glass materials play a vital role in advancement of science and technology. They have found wide spread application in the industry, in laboratory equipment and in micro-gas turbines. Due to their low fracture toughness they are very difficult to machine, moreover there are the chip depositions on the machined surface which affects surface finish under ductile mode cutting conditions. In this research, high speed end milling of soda lime glass is performed on CNC vertical milling machine to investigate the effects of machining parameters i.e. spindle speed, depth of cut, and feed rate on machined surface roughness. Design of experiments was performed following Central Composite Design (CCD) of Response Surface Methodology (RSM). Design Expert Software was used for generating the empirical mathematical model for average surface roughness. The model’s validity was tested to 95% confidence level by Analysis of Variance (ANOVA). Subsequent experimental results showed that the developed mathematical model could successfully describe the performance indicators, i.e. surface roughness, within the controlled limits of the factors that were considered.

Surface Roughness Identification in End Milling Using Vibration Signals and Fuzzy Clustering

2016 ◽  
Author(s):  
Issam Abu-Mahfouz ◽  
Amit Banerjee ◽  
A. H. M. Esfakur Rahman
Keyword(s):  
Surface Roughness ◽  
Fuzzy Clustering ◽  
Wavelet Transforms ◽  
Fourier Transforms ◽  
End Milling ◽  
Cutting Conditions ◽  
Depth Of Cut ◽  
Cutting Condition ◽  
Machined Surface ◽  
Vibration Signals

The study presented involves the identification of surface roughness in Aluminum work pieces in an end milling process using fuzzy clustering of vibration signals. Vibration signals are experimentally acquired using an accelerometer for varying cutting conditions such as spindle speed, feed rate and depth of cut. Features are then extracted by processing the acquired signals in both the time and frequency domain. Techniques based on statistical parameters, Fast Fourier Transforms (FFT) and the Continuous Wavelet Transforms (CWT) are utilized for feature extraction. The surface roughness of the machined surface is also measured. In this study, fuzzy clustering is used to partition the feature sets, followed by a correlation with the experimentally obtained surface roughness measurements. The fuzzifier and the number of clusters are varied and it is found that the partitions produced by fuzzy clustering in the vibration signal feature space are related to the partitions based on cutting conditions with surface roughness as the output parameter. The results based on limited simulations are encouraging and work is underway to develop a larger framework for online cutting condition monitoring system for end milling.

ANALYSIS OF THE CORRELATION BETWEEN FRACTAL STRUCTURE OF CUTTING FORCE SIGNAL AND SURFACE ROUGHNESS OF MACHINED WORKPIECE IN END MILLING OPERATION

Fractals ◽  
2019 ◽  
Vol 27 (02) ◽  
pp. 1950013 ◽  
Author(s):  
AHMAD THUFFAIL THASTHAKEER ◽  
ALI AKHAVAN FARID ◽  
CHANG TECK SENG ◽  
HAMIDREZA NAMAZI
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Surface Quality ◽  
Cutting Forces ◽  
End Milling ◽  
Complex Structure ◽  
Machined Surface ◽  
End Mills ◽  
Machining Operations

Analysis of the machined surface is one of the major issues in machining operations. On the other hand, investigating about the variations of cutting forces in machining operation has great importance. Since variations of cutting forces affect the surface quality of machined workpiece, therefore, analysis of the correlation between cutting forces and surface roughness of machined workpiece is very important. In this paper, we employ fractal analysis in order to investigate about the complex structure of cutting forces and relate them to the surface quality of machined workpiece. The experiments have been conducted in different conditions that were selected based on cutting depths, type of cutting tool (serrated versus. square end mills) and machining conditions (wet and dry machining). The result of analysis showed that among all comparisons, we could only see the correlation between complex structure of cutting force and the surface roughness of machined workpiece in case of using serrated end mill in wet machining condition. The employed methodology in this research can be widely applied to other types of machining operations to analyze the effect of variations of different parameters on variability of cutting forces and surface roughness of machined workpiece and then investigate about their correlation.

Multi Objective Optimization of Cutting Parameters in Machining Cellulose Based Hybrid Composites

2015 ◽  
Vol 761 ◽  
pp. 287-292
Author(s):  
Raja Izamshah ◽  
Zainudin Zuraidah ◽  
Mohd Shahir Kasim ◽  
M. Hadzley ◽  
M. Amran
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Hybrid Composites ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Multi Objective Optimization ◽  
Machining Performance ◽  
Machined Surface ◽  
Multi Objective ◽  
Optimization Of Cutting Parameters

Cellulose based hybrid composites are gaining popularity in the growing green communities. With extensive studies and increasing applications for future advancement, the need for an accurate and reliable guidance in machining this type of composites has increased enormously. Smooth and defect free machined surface are always the ultimate objectives. The present work deals with the study of machining parameters (i.e. spindle speed, feed rate and depth of cut) and their effects on machining performance (i.e. surface roughness and delamination) to establish an optimized setup of machining parameters in achieving multi objective machining performance. Cellulose based hybrid composites consist of jute (a bast fiber) and glass fiber embedded in polyester resins. Response Surface Methodology (RSM) using Box-Behnken Design (BBD) was chosen as the design of experiment approach for this study. Based on that experimental approach, 17 experimental runs were conducted. Mathematical model for each response was developed based on the experimental data. Adequacy of the models were analyzed statistically using Analysis of Variance (ANOVA) in determining the significant input variables and possible interactions. The multi objective optimization was performed through numerical optimization, and the predicted results were validated. The agreement between the experimental and selected solution was found to be strong, between 95% to 96%, thus validating the solution as the optimal machining condition. The findings suggest that feed rate was the main factor affecting surface roughness and delamination .

Optimization of Process Parameters for Cutting Force for Aluminium 7010 in CNC End Milling Process

2018 ◽  
Vol 10 (6) ◽  
Author(s):  
M. Kishanth ◽  
P. Rajkamal ◽  
D. Karthikeyan ◽  
K. Anand
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Process Parameters ◽  
End Milling ◽  
Milling Process ◽  
Machining Process ◽  
Depth Of Cut ◽  
Optimization Of Process Parameters ◽  
Cnc End Milling ◽  
End Milling Process

In this paper CNC end milling process have been optimized in cutting force and surface roughness based on the three process parameters (i.e.) speed, feed rate and depth of cut. Since the end milling process is used for abrading the wear caused is very high, in order to reduce the wear caused by high cutting force and to decrease the surface roughness, the optimization is much needed for this process. Especially for materials like aluminium 7010, this kind of study is important for further improvement in machining process and also it will improve the stability of the machine.

Технологическое обеспечение качества поверхностного слоя стекловолоконных композитов при концевом фрезеровании

2020 ◽  
Vol 22 (4) ◽  
pp. 31-40
Author(s):  
Andrei Markov ◽  
◽  
Vyacheslav Nekrasov ◽  
Jian Su ◽  
Azhar Salman ◽  
...  
Keyword(s):  
Composite Materials ◽  
End Milling ◽  
Experimental Studies ◽  
Milling Process ◽  
Depth Of Cut ◽  
Machined Surface ◽  
Scientific Publications ◽  
Experimental Assembly ◽  
Operation Results

Introduction. Today fiberglass is one of the most common composite materials. Therefore, its mechanical processing continues to be the subject of many studies. In many scientific publications, the influence of cutting modes and structural and geometric parameters of the tool on the roughness of the machined surface, cutting forces and wear of the cutting tool has been established. The purpose of this work is to study the effect of machining modes on delamination and roughness of fiberglass composites during end milling, as well as testing the hypothesis about the effect of torque on the delamination. The relevance of the study is due to the fact that delamination, along with roughness, has a significant impact on the quality of processing and subsequent assembly of the finished product. A criterion is proposed for assessing the magnitude of the delamination of composite materials during its machining. The results of experimental studies of the torque on the cutter, the relative coefficient of delamination and surface roughness from cutting conditions are presented. Methods: factorial experiment using an experimental assembly developed by the authors based on a piezoelectric torque sensor. The installation allows real-time recording of the change in torque during the milling process, depending on the modes of operation. Results and Discussion. A comparative analysis of the obtained dependences showed that the torque is directly related to delamination. To reduce the delamination, the depth of cut should be decreased, and in order to ensure the specified productivity, the feed and the rotational speed of the cutter should be increased. The presented results confirm the prospects of the developed approach aimed at machining new classes of composite materials.

Modeling & Analysis of End Milling Process Parameters Using Artificial Neural Networks

2014 ◽  
Vol 592-594 ◽  
pp. 2733-2737 ◽  
Author(s):  
G. Harinath Gowd ◽  
K. Divya Theja ◽  
Peyyala Rayudu ◽  
M. Venugopal Goud ◽  
M .Subba Roa
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Process Parameters ◽  
End Milling ◽  
Milling Process ◽  
Machining Process ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Artificial Neural ◽  
End Milling Process

For modeling and optimizing the process parameters of manufacturing problems in the present days, numerical and Artificial Neural Networks (ANN) methods are widely using. In manufacturing environments, main focus is given to the finding of Optimum machining parameters. Therefore the present research is aimed at finding the optimal process parameters for End milling process. The End milling process is a widely used machining process because it is used for the rough and finish machining of many features such as slots, pockets, peripheries and faces of components. The present work involves the estimation of optimal values of the process variables like, speed, feed and depth of cut, whereas the metal removal rate (MRR) and tool wear resistance were taken as the output .Experimental design is planned using DOE. Optimum machining parameters for End milling process were found out using ANN and compared to the experimental results. The obtained results provβed the ability of ANN method for End milling process modeling and optimization.

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