Methodology for Measuring the Cutting Inserts Wear

被引:15
作者
Daicu, Raluca [1 ,2 ]
Oancea, Gheorghe [1 ]
机构
[1] Transilvania Univ Brasov, Dept Mfg Engn, B Dul Eroilor 29, Brasov 500036, Romania
[2] SC Siemens Ind Software, B Dul Garii 13A, Brasov 500227, Romania
来源
SYMMETRY-BASEL | 2022年 / 14卷 / 03期
关键词
asymmetry; cutting process; cutting insert; measurement; symmetry; tool condition monitoring; wear; ARTIFICIAL NEURAL-NETWORK; ACOUSTIC-EMISSION SENSOR; MACHINED SURFACE IMAGES; TOOL FLANK WEAR; PREDICTION; ROUGHNESS; STEEL; LIFE; OPTIMIZATION; VIBRATION;
D O I
10.3390/sym14030469
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
In the industrial manufacturing, the wear of the cutting tool represents the main factor that causes machine downtime and it has a negative influence over the machined surface roughness and dimensional and position deviations. For this reason, the accurate measurement of tool wear both on-line (during machining) and off-line (outside of the machining process) is a necessity. Due to the continuous technology innovation, finding new and more effective methods to measure precisely the wear represents a permanent interest for research. In this paper, after a review of recent developed methods in this field, showing the methods of measuring wear and indicating the error sources when measuring the wear of cutting inserts, the necessity to have a unitary methodology for measuring the flank wear is emphasized. Applying it could obtain the same wear-measured values in the same conditions. For this purpose, the measurement errors are determined, and a new methodology for measuring the cutting insert wear is developed. It was tested in the case of six worn cutting inserts used for the turning process of specimens (1C45 steel), of 50 mm diameter and 300 mm length. By testing the developed methodology, it was found that the errors that can be made by various researchers while measuring wear are acceptable, leading to results that can be considered correct from a practical point of view. In the paper is also presented how the principle of symmetry is used to characterize the wear of the cutting inserts.
引用
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页数:26
相关论文
共 89 条
[1]   Vibration-based estimation of tool major flank wear in a turning process using ARMA models [J].
Aghdam, B. H. ;
Vahdati, M. ;
Sadeghi, M. H. .
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2015, 76 (9-12) :1631-1642
[2]   Investigation and FEM-based simulation of tool wear in turning operations with uncoated carbide tools [J].
Attanasio, A. ;
Ceretti, E. ;
Fiorentino, A. ;
Cappellini, C. ;
Giardini, C. .
WEAR, 2010, 269 (5-6) :344-350
[3]   Online monitoring of cutting tool temperature during micro-end milling using infrared thermography [J].
Bagavathiappan, S. ;
Lahiri, B. B. ;
Suresh, S. ;
Philip, J. ;
Jayakumar, T. .
INSIGHT, 2015, 57 (01) :9-17
[4]   Multi sensor signal processing for catastrophic tool failure detection in turning [J].
Balsamo, Vittorio ;
Caggiano, Alessandra ;
Jemielniak, Krzysztof ;
Kossakowska, Joanna ;
Nejman, Miroslaw ;
Teti, Roberto .
RESEARCH AND INNOVATION IN MANUFACTURING: KEY ENABLING TECHNOLOGIES FOR THE FACTORIES OF THE FUTURE - PROCEEDINGS OF THE 48TH CIRP CONFERENCE ON MANUFACTURING SYSTEMS, 2016, 41 :939-944
[5]   Health assessment and life prediction of cutting tools based on support vector regression [J].
Benkedjouh, T. ;
Medjaher, K. ;
Zerhouni, N. ;
Rechak, S. .
JOURNAL OF INTELLIGENT MANUFACTURING, 2015, 26 (02) :213-223
[6]   Tool condition monitoring by SVM classification of machined surface images in turning [J].
Bhat, Nagaraj N. ;
Dutta, Samik ;
Vashisth, Tarun ;
Pal, Srikanta ;
Pal, Surjya K. ;
Sen, Ranjan .
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2016, 83 (9-12) :1487-1502
[7]   Application of acoustic emission sensor to investigate the frequency of tool wear and plastic deformation in tool condition monitoring [J].
Bhuiyan, M. S. H. ;
Choudhury, I. A. ;
Dahari, M. ;
Nukman, Y. ;
Dawal, S. Z. .
MEASUREMENT, 2016, 92 :208-217
[8]   Monitoring the tool wear, surface roughness and chip formation occurrences using multiple sensors in turning [J].
Bhuiyan, M. S. H. ;
Choudhury, I. A. ;
Dahari, M. .
JOURNAL OF MANUFACTURING SYSTEMS, 2014, 33 (04) :476-487
[9]   Tool wear simulation of complex shaped coated cutting tools [J].
Binder, M. ;
Klocke, F. ;
Lung, D. .
WEAR, 2015, 330 :600-607
[10]   Sensor signal segmentation for tool condition monitoring [J].
Bombinski, Sebastian ;
Blazejak, Krzysztof ;
Nejman, Miroslaw ;
Jemielniak, Krzysztof .
7TH HPC 2016 - CIRP CONFERENCE ON HIGH PERFORMANCE CUTTING, 2016, 46 :155-160