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Tool Condition Monitoring of Ceramic Inserted Tools in High Speed Machining through Image Processing

Authors: Javier A. Dominguez Caballero, Graeme A. Manson, Matthew B. Marshall

Abstract:

Cutting tools with ceramic inserts are often used in the process of machining many types of superalloy, mainly due to their high strength and thermal resistance. Nevertheless, during the cutting process, the plastic flow wear generated in these inserts enhances and propagates cracks due to high temperature and high mechanical stress. This leads to a very variable failure of the cutting tool. This article explores the relationship between the continuous wear that ceramic SiAlON (solid solutions based on the Si3N4 structure) inserts experience during a high-speed machining process and the evolution of sparks created during the same process. These sparks were analysed through pictures of the cutting process recorded using an SLR camera. Features relating to the intensity and area of the cutting sparks were extracted from the individual pictures using image processing techniques. These features were then related to the ceramic insert’s crater wear area.

Keywords: Ceramic cutting tools, high speed machining, image processing, tool condition monitoring, tool wear.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1125791

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References:


[1] Z. Liu, X. Ai, H. Zhang, Z. Wang, and Y. Wan, “Wear patterns and mechanisms of cutting tools in high-speed face milling,” in The 10th International Manufacturing Conf. in China, Journal of Materials Processing Technology, vol. 129, Fujian, China, 2002, pp. 222-226.
[2] S. Casto, E. Valvo, V. Ruisi, E. Lucchini, and S. Maschio, “Wear mechanism of ceramic tools,” in Wear, vol. 160, 1993, pp. 227-235.
[3] A. Altin, M. Nalbant, and A. Taskesen, “The effects of cutting speed on tool wear and tool life when machining Inconel 718 with ceramic tools,” in Materials & Design, vol. 28, 2007, pp. 2518-2522.
[4] Sandvik Coromant, “Ceramics,” AB Sandvik Coromant, 2010, Available: http://www.sandvik.coromant.com/sitecollectiondocuments/downloads/global/brochures/en-gb/c-2929-61.pdf.
[5] X. Tian, J. Zhao, J. Zhao, Z. Gong, and Y. Dong, “Effect of cutting speed on cutting forces and wear mechanisms in high-speed face milling of Inconel 718 with Sialon ceramic tools,” in The International Journal of Advanced Manufacturing Technology, vol. 69, London: Springer, 2013, pp. 2669-2678.
[6] G. Byrne, D. Dornfeld, I. Inasaki, G. Ketteler, W. König, and R. Teti, “Tool Condition Monitoring (TCM) — The Status of Research and Industrial Application,” in CIRP Annals - Manufacturing Technology, vol. 44, 1995, pp. 541–567.
[7] S. Kurada and C. Bradley, “A machine vision system for tool wear assessment,” in Tribology International, vol. 30, 1997, pp. 295–304.
[8] R. C. Gonzalez and R. E. Woods, Digital Image Processing: International Edition, 3rd ed. New Jersey: Pearson Prentice Hall, 2010, pp. 23.
[9] D.M. D’Addona and R. Teti, “Image Data Processing via Neural Networks for Tool Wear Prediction,” in 8th CIRP Conf. on Electro Physical and Chemical Machining (ISEM XVIII), vol. 12, 2013, pp. 252–257.
[10] S. Kurada and C. Bradley, “A review of machine vision sensors for tool condition monitoring,” in Computers in Industry, vol. 34, 1997, pp. 55-72.
[11] T. Pfeifer and L. Wiegers, “Reliable tool wear monitoring by optimized image and illumination control in machine vision,” in Measurement, vol. 28, 2000, pp. 209-218.
[12] T. Teshima, T. Shibasaka, M. Takuma, A. Yamamoto, and K. Iwata “Estimation of Cutting Tool Life by Processing Tool Image Data with Neural Network,” in CIRP Annals - Manufacturing Technology, vol. 42, 1993, pp. 59-62.
[13] J. A. Dominguez Caballero, G. A. Manson, and M. B. Marshall, “Optimal image processing acquisition parameters for a tool condition monitoring system of ceramic inserted tools,” unpublished.
[14] JP. Davim, Machining of Hard Materials, New York: Springer Science & Business Media, 2011, pp. 38.
[15] W. Grzesik, Advanced Machining Processes of Metallic Materials: Theory, Modelling and Applications, Elsevier, 2008, pp. 163-166.