Commenced in January 2007
Paper Count: 31100
New Regression Model and I-Kaz Method for Online Cutting Tool Wear Monitoring
Abstract:This study presents a new method for detecting the cutting tool wear based on the measured cutting force signals using the regression model and I-kaz method. The detection of tool wear was done automatically using the in-house developed regression model and 3D graphic presentation of I-kaz 3D coefficient during machining process. The machining tests were carried out on a CNC turning machine Colchester Master Tornado T4 in dry cutting condition, and Kistler 9255B dynamometer was used to measure the cutting force signals, which then stored and displayed in the DasyLab software. The progression of the cutting tool flank wear land (VB) was indicated by the amount of the cutting force generated. Later, the I-kaz was used to analyze all the cutting force signals from beginning of the cut until the rejection stage of the cutting tool. Results of the IKaz analysis were represented by various characteristic of I-kaz 3D coefficient and 3D graphic presentation. The I-kaz 3D coefficient number decreases when the tool wear increases. This method can be used for real time tool wear monitoring.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1086277Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2057
 Qiang Liu, Y. Altintas, "On-line monitoring of flank wear in turning with multilayered feed-forward neural network," International Journal of Machine Tools and Manufacture, 39, 1999, pp. 1945-1959.
 Nuawi M. Z., Lamin F., Nor M. J. M., Jamaluddin N., Abdullah S., Nizwan C. K. E., "Integration of I-kaz Coefficient and Taylor Tool Life Curve for Tool Wear Progression Monitoring in Machining Process, " International Journal of Mechanics, 3 (1), 2007, pp. 45-50.
 Kurada, S. and C. Bradley, "A review of machine vision sensors for tool condition monitoring," Computers in Industry, 34(1), 1997, pp. 55 - 72.
 W. H. Wang, G. S. Hong, Y. S. Wong and K. P. Zhu, "Sensor fusion for on-line tool condition monitoring in milling," International Journal of Production Research, In Press, 45 (21), 2007, pp. 5095-5116.
 Z. Kunpeng, W. Y. San, H. G. Soon, "Wavelet analysis of sensor signals for tool condition monitoring: A review and some new results," International Journal of Machine Tools and Manufacture, 2009.
 Lin S.C and Lin R.J., "Tool wear monitoring in face milling using force signals," Journal of material processing and technology, 1996, pp. 136-142.
 D.E. Dimla Snr., "Tool wear monitoring using cutting force measurements," 15th NCMR: Advances in Manufacturing Technology XIII, University of Bath, 6-8 Sep. 1999, pp. 33-37.
 E. Kuljanic, M. Sortino, "TWEM : A method based on cutting forcesmonitoring tool wear in face milling," International Journal of Machine Tools & Manufacture, 45, 2005, pp. 29-34.
 K.J. Lee, T.M. Lee, M.Y. Yang, "Tool wear monitoring system for CNC end milling using a hybrid approach to cutting force regulation," International Journal Advance Manufacturing Technology, 32, 2007, pp. 8-17.
 Oraby SE, Hayhurst DR., "Tool life determination based on the measurement of wear and tool force ratio variation," International Journal Machine Tools Manufacturing, 44, 2004, pp. 1261-1269.
 Srinivas J., Rama Kotaiah K., "Tool wear monitoring with indirect methods," Manufacturing Technology Today, India 4, 2005, pp. 7-9.
 Nuawi M. Z., Lamin F., Nor M. J. M., Jamaluddin N., Abdullah S., Nizwan C. K. E., "Development of Integrated Kurtosis-Based Algorithm for Z-Filter Technique," Journal of Applied Science, 8 (8), 2008, pp. 1541-1547.
 Che Haron, C. H., Ginting, A., Goh, J. H., "Tool life and surface integrity in turning titanium alloy," Journal of Materials and Processing Technology, 118 (1-3), 2001, pp. 231-237.
 ISO (International Organization for Standardization) (ed.), "Tool-life Testing with Single-Point Turning Tools (ISO 3685)," 2nd edition, Reference Number ISO 3685: (1993)(E).