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.

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.

scholarly journals The Milling Process Monitoring Using 3D Envelope Method

2011 ◽  
Vol 423 ◽  
pp. 77-88 ◽  
Author(s):  
Claudiu Bisu ◽  
Alain Gerard ◽  
Miron Zapciu ◽  
Olivier Cahuc
Keyword(s):  
Three Dimensional ◽  
Cutting Parameters ◽  
Milling Process ◽  
Quantitative Characterization ◽  
Envelope Analysis ◽  
Milling Tool ◽  
Envelope Method ◽  
On Line ◽  
Cutting Capacity

This paper proposes a method to vibration analysis in order to on-line monitoring of milling process quality. Adapting envelope analysis to characterize the milling tool materials is an important contribution to the qualitative and quantitative characterization of milling capacity and a step by modeling the three-dimensional cutting process. An experimental protocol was designed and developed for the acquisition, processing and analyzing three-dimensional signal. The vibration envelope analysis is proposed to detect the cutting capacity of the tool with the optimization application of cutting parameters. The research is focused on Hilbert transform optimization to evaluate the dynamic behavior of the machine/ tool/workpiece.

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.

Tool Wear Monitoring of High Speed Milling Based on Vibratory Signal Processing

2014 ◽  
Vol 565 ◽  
pp. 36-45
Author(s):  
Hadjadj Abdechafik ◽  
Kious Mecheri ◽  
Ameur Aissa
Keyword(s):  
Signal Processing ◽  
Tool Wear ◽  
Monitoring System ◽  
High Speed ◽  
Milling Process ◽  
Machining Performance ◽  
High Speed Milling ◽  
Tool Wear Estimation ◽  
On Line ◽  
Wear Monitoring

The objective of this study is to develop a process of treatment of the vibratory signals generated during a horizontal high speed milling process without applying any coolant in order to establish a monitoring system able to improve the machining performance. Thus, many tests were carried out on the horizontal high speed centre (PCI Météor 10), in given cutting conditions, by using a milling cutter with only one insert and measured its frontal wear from its new state that is considered as a reference state until a worn state that is considered as unsuitable for the tool to be used. The results obtained show that the first harmonic follow well the evolution of frontal wear, on another hand a wavelet transform is used for signal processing and is found to be useful for observing the evolution of the wavelet approximations through the cutting tool life. The power and the root mean square (RMS) values of the wavelet transformed signal gave the best results and can be used for tool wear estimation. All this features can constitute the suitable indicators for an effective detection of tool wear and then used for the input parameters of an on-line monitoring system. Nevertheless we noted the remarkable influence of the machining cycle on the quality of measurements by the introduction of a bias on the signal; this phenomenon appears in particular in horizontal milling and in the majority of studies is ignored

Tool Wear Characters in Micro-Milling of Fully Sintered ZrO2 Ceramics by Diamond Coated End Mills

2012 ◽  
Vol 723 ◽  
pp. 365-370 ◽  
Author(s):  
Rong Bian ◽  
Eleonora Ferraris ◽  
Jun Qian ◽  
Dominiek Reynaerts ◽  
Liang Li ◽  
...  
Keyword(s):  
Tool Wear ◽  
Cutting Tools ◽  
Chemical Vapour ◽  
Cutting Parameters ◽  
Micro Milling ◽  
Machined Surface ◽  
Coated Tools ◽  
Machined Surface Quality ◽  
Coating Delamination ◽  
End Mills

This work presents an experimental investigation on micro-milling of fully sintered Zirconia (ZrO2) by diamond coated tools. The experiments were conducted on a Kern MMP 2522 micro-milling centre and WC micro end mills, diamond coated by chemical vapour deposition (CVD) and of stiff geometry were employed as cutting tools. The effects of cutting parameters and milling time on tool wear were investigated. The results revealed that the tool wear characters included diamond coating delamination and wear of substrate WC. Both cutting forces and machined surface quality were affected by tool wear with the progress of milling.

Research on Cutting Stability of High-Efficiency Micro Turn-Milling Compound Machine Tool Based on Lobes

2019 ◽  
Vol 295 ◽  
pp. 59-65
Author(s):  
Zhong Peng Zheng ◽  
Xin Jin ◽  
Ye Wang Sun ◽  
Xin Yang Jiang ◽  
Zhi Jing Zhang ◽  
...  
Keyword(s):  
Machine Tool ◽  
High Efficiency ◽  
Cutting Parameters ◽  
Milling Process ◽  
Test Method ◽  
Cutting Process ◽  
Milling Machine ◽  
Cutting Stability ◽  
Milling Chatter ◽  
Turn Milling

In order to improve the cutting stability of high-efficiency micro turn-milling machine tools, avoid the chattering problem during the cutting process. In this paper, the chatter problem in the cutting process is studied based on the stable lobes. By analyzing the high-efficiency turn-milling machine tool mechanism and the turn-milling model, the micro turn-milling dynamic dynamic vibration model and the mathematical model of turn-milling chatter are obtained. Then, based on the hammer test method, the transfer function of the tool-workpiece system is obtained, and the turn-milling stable lobes of the high-efficiency micro turn-milling machine tool is constructed. Finally, the research on the stable zone of the turning main spindle parts, the turning back spindle parts and the high-frequency milling part are completed. The experimental research results guide and optimize the selection of cutting parameters for turn-milling process.

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.

Experimental Study on Ball End Mill in Glass Machining at High Speed

2011 ◽  
Vol 314-316 ◽  
pp. 1167-1170
Author(s):  
Zhi Wei ◽  
Ji Hong Jia ◽  
Mei Lin Gu ◽  
Chao Zuo ◽  
Xing Zhen Jin
Keyword(s):  
High Speed ◽  
Experimental System ◽  
Milling Process ◽  
End Mill ◽  
Ball End Mill ◽  
Milling Force ◽  
Milling Tool ◽  
Explicit Analysis ◽  
Stress And Deformation ◽  
The Relationship

This paper describes the experimental system of milling force, the tool geometrical feature and the certain experimental condition in the section of experimental case, which also makes an explanation about the designing of experimental case and the analysis of the experimental data. It also represents the relationship between coefficients associated with the milling process and the milling force applied on the tool in detail. A finite element method is used to make an explicit analysis on the stress and deformation of the milling tool under the application of certain milling force. Finally, a summary is made to conclude the study and its results.

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