Research on Tool Wear Form in Micro Turn-Milling Process

2012 ◽  
Vol 184-185 ◽  
pp. 663-667 ◽  
Author(s):  
Lin Hui Zhao ◽  
Jian Cheng Zhang ◽  
Wei Su
Keyword(s):  
Tool Wear ◽  
Small Diameter ◽  
Milling Process ◽  
Milling Tool ◽  
Key Factor ◽  
Part Surface ◽  
End Mills ◽  
Series Of Experiments ◽  
Turn Milling ◽  
Wear Condition

In micro machining, turn-milling tool wear is a key factor for part surface quality. This paper carries on experiments on end mills wear in micro turn-milling machining, aiming to research the wear form and provide some reference data for developing wear standard of small diameter end mills. To measure wear condition of end mills, machine vision technique is utilized. This paper designs and sets up an online end mill wear measurement system for a micro turn-milling process center. With a series of experiments on small diameter end mills, wear conditions of different cutting positions are researched. Based on analysis of experiment data, wear characteristics and wear rule for micro turn-milling process are summarized in this paper.

Modeling and Prediction Research on End Mills Wear in Micro Turn-Milling Process

2013 ◽  
Vol 423-426 ◽  
pp. 741-745
Author(s):  
Xiao Yang Su ◽  
Zhi Jing Zhang ◽  
Xin Jin ◽  
Yong Jun Deng
Keyword(s):  
Tool Wear ◽  
Cutting Parameters ◽  
Milling Process ◽  
Visual Measurement ◽  
Modeling And Prediction ◽  
Milling Tool ◽  
End Mills ◽  
On Line ◽  
The Relationship ◽  
Turn Milling

An end mills wear experiment was designed to model and predict the end mills wear in micro turn-milling process. Based on the on-line visual measurement system, the tool wear was measured, then micro turn-milling tool wear regression models were established according to Response surface Method (RSM). The relationship between cutting parameters and tool wear was discussed in detail. The results indicate that the regression model can predict the value and regularity of end mills wear accurately, which can provide guidance on improving machining precision and quality in micro turn-milling process.

An Investigation of the Vibration Testing Method for Small Diameter Endmills

2014 ◽  
Vol 625 ◽  
pp. 134-139
Author(s):  
Takenori Ono
Keyword(s):  
Small Diameter ◽  
Milling Process ◽  
Modal Parameters ◽  
Vibration Testing ◽  
Function Generator ◽  
Testing Method ◽  
Milling Tool ◽  
Compliance Curve ◽  
Vibration Tests ◽  
The Impact

This paper introduced about the in-process vibration testing method for small diameter endmill. By this method, the natural frequency and modal parameters such as mass, damping, and stiffness of the milling tool can be determined in the milling process. An oscillation of the vibrator is controlled by the function generator to apply the impact force at the appropriate cutting period. The measurement setup can determine the compliance curve by the measurement signals of the exiting force and tool deformation. To evaluate the feasibility of the new method, vibration tests were performed on a square endmill which has the diameter of 4 mm in the milling on brass material. Results of vibration tests show that modal parameters of the specific vibration mode can be determined by the new developed method.

Monitoring of End-Mill Behavior with Its Projection Image

2006 ◽  
Vol 315-316 ◽  
pp. 474-480
Author(s):  
Dun Wen Zuo ◽  
Yoshihiro Kawano
Keyword(s):  
High Speed ◽  
Small Diameter ◽  
Milling Process ◽  
Measuring System ◽  
End Mill ◽  
Static State ◽  
High Speed Cutting ◽  
Projection Image ◽  
Image Width ◽  
End Mills

End mills with small diameter have found their wide application with the development of high-speed cutting. It becomes more and more important to develop effective methods to monitor and control the milling process with small end mills. In this paper, a measuring system of projection image for small end mills is introduced, and the application of the projection image to monitor the behavior of the end mill is discussed. It is found that for static state of the end mill, the measurement accuracy can be easily controlled within 1 μm. When the end mill rotates, it is not so difficult to control the accuracy within 3 μm. By using of the change in image width, the radial wear of end mill can be predicted. On the other hand, if the centre shift of the image is pre-measured, the deflection of the end mill during cutting can be predicted.

Face Milling Tool Wear Condition Monitoring Based on Wavelet Transform and Shannon Entropy

2014 ◽  
Vol 541-542 ◽  
pp. 1419-1423 ◽  
Author(s):  
Min Zhang ◽  
Hong Qi Liu ◽  
Bin Li
Keyword(s):  
Wavelet Transform ◽  
Tool Wear ◽  
Condition Monitoring ◽  
Shannon Entropy ◽  
Spindle Motor ◽  
Face Milling ◽  
Motor Current ◽  
Milling Tool ◽  
Spindle Motor Current ◽  
Wear Condition

Tool condition monitoring is an important issue in the advanced machining process. Existing methods of tool wear monitoring is hardly suitable for mass production of cutting parameters fluctuation. In this paper, a new method for milling tool wear condition monitoring base on tunable Q-factor wavelet transform and Shannon entropy is presented. Spindle motor current signals were recorded during the face milling process. The wavelet energy entropy of the current signals carries information about the change of energy distribution associated with different tool wear conditions. Experiment results showed that the new method could successfully extract significant signature from the spindle-motor current signals to effectively estimate tool wear condition during face milling.

scholarly journals Milling Tool Wear State Recognition by Vibration Signal Using a Stacked Generalization Ensemble Model

2019 ◽  
Vol 2019 ◽  
pp. 1-16
Author(s):  
Yang Hui ◽  
Xuesong Mei ◽  
Gedong Jiang ◽  
Tao Tao ◽  
Changyu Pei ◽  
...  
Keyword(s):  
Tool Wear ◽  
Frequency Domain ◽  
Recognition Accuracy ◽  
Milling Process ◽  
Ensemble Model ◽  
Vibration Signals ◽  
State Recognition ◽  
Model Based ◽  
Milling Tool ◽  
Accuracy And Stability

Milling tool wear state recognition plays an important role in controlling the quality of milled parts and reducing machine tool downtime. However, the characteristics of milling process limit the accuracy and stability of tool condition monitoring (TCM) employing vibration signals. To improve this problem, this paper explores the use of vibration signals as sensing approach for recognizing tool wear states during milling operation by using the stacked generalization (SG) ensemble model. In this study, vibration signals collected during the milling process are analyzed through the time domain, frequency domain, and time-frequency domain to extract signal features. The support vector machine recursive feature elimination (SVM-RFE) algorithm is used to select the main features which are most relevant to tool wear states. The SG ensemble model based on SVM, decision tree (DT), naive Bayes (NB), and SG ensemble strategy is constructed to recognize tool wear states. The proposed method is experimental verified, and the results show that the recognition accuracy of the established SG ensemble model is 98.74% and the overall G-mean and AUC evaluation value of the model is 0.98 and 0.98, respectively. In addition, compared with other ensemble models and single models, the SG ensemble model based on vibration signals has better recognition accuracy and stability than other models.

High Precise Milling Process by cBN End Mills

2012 ◽  
Vol 6 (4) ◽  
pp. 542-545 ◽  
Author(s):  
Katsumi Naganuma ◽  
◽  
Masato Mori
Keyword(s):  
Research And Development ◽  
Tool Life ◽  
Small Diameter ◽  
Milling Process ◽  
Machining Accuracy ◽  
End Mill ◽  
Hard Materials ◽  
Machining Quality ◽  
Machining Test ◽  
End Mills

Molding technology is one way of producing the micro-precision parts required by various industries. To Advance this molding technology, various elemental technologies related to materials, construction and machiningmethods are evolving together. One of these elemental technologies is milling by end mill. Further research and development of end mill is underway in response to improvement and requirement of molding technologies. There are various demands for end mills such as improvement of tool life and stable machining quality. Here we report the small diameter cBN end mill, developed as a tool to provide with stable machining accuracy with long tool life for high hard materials. We report the investigations and characteristics at the time of development and show the machining test.

Influence of Coating in Square End Mill Using In-Process Tool Wear Detection Based on Electrical Contact Resistance

2019 ◽  
Vol 13 (1) ◽  
pp. 125-132
Author(s):  
Amine Gouarir ◽  
Syuhei Kurokawa ◽  
Takao Sajima ◽  
Mitsuaki Murata ◽  
◽  
...  
Keyword(s):  
Tool Wear ◽  
Contact Resistance ◽  
High Speed ◽  
End Milling ◽  
Detection System ◽  
Electrical Contact ◽  
Milling Process ◽  
Electrical Contact Resistance ◽  
End Mills ◽  
End Milling Process

In this paper, a method using electrical contact resistance to monitor in-process tool wear is proposed. The high-speed tool wear detection system uses the contact resistance between the tool and workpiece as an indicator to monitor the progression of tool wear during cutting operations. The electrical resistance decreases with an increase in contact area on the tool flank. In our previous study, the objective was an end milling process using uncoated square end mills. In this experiment, our targets are solid and throw away coated square end mills. The experiment shows the present method to also be effective as an in-process tool wear detection system for coated square end mills.

Experimental Research of Workpiece Temperature in Orthogonal Turn-Milling Compound Machining

2014 ◽  
Vol 887-888 ◽  
pp. 1184-1190 ◽  
Author(s):  
Yi Zhi Liu ◽  
Fang Yu Peng ◽  
Sen Lin ◽  
Rong Yan ◽  
Sheng Yang
Keyword(s):  
Experimental Method ◽  
Experimental Research ◽  
Cylindrical Surface ◽  
Cutting Parameters ◽  
Milling Process ◽  
Workpiece Temperature ◽  
Temperature Variance ◽  
Milling Tool ◽  
Five Axis ◽  
Turn Milling

Workpiece temperature in orthogonal turn-milling compound machining was studied with experimental method in this paper. The orthogonal turn-milling process was simulated through engagement of a milling tool and cylindrical surface on a five-axis milling center. The cutting parameters were designed into an orthogonal parameter table of seven factors three levels based on factors having effects on workpiece temperature. Variance analysis of data achieved from this experiment was carried out and conclusion about the order of effects each factor has on workpiece temperature was drawn.

Experimental Study of Sound Signal for Tool Condition Monitoring in Micro Milling Processes

2008 ◽  
Author(s):  
Chia-Liang Yen ◽  
Ming-Chyuan Lu ◽  
Ching-Yuan Lin ◽  
Tin-Hong Chen
Keyword(s):  
Tool Wear ◽  
Frequency Domain ◽  
High Speed ◽  
Wear Test ◽  
Milling Process ◽  
Micro Milling ◽  
Tool Condition ◽  
Audible Sound ◽  
End Mills ◽  
Speed Up

The audible sound signals obtained in micro-milling processes are analyzed in the time and frequency domain for the tool wear and breakage monitoring. Micro end-mills of φ 700 μm are implemented in the tool wear test, along with a high speed spindle with speed up to 60000 rpm. The audible sound signals and vibration signals for different tool conditions were collected simultaneously in the cutting. After transferring data from time domain to the frequency domain, as well as the Wavelet coefficients, the capability of audible sound signals in detecting the tool condition for the micro milling process was evaluated.

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