Open AccessPerformance of Al2O3-CBN materials and perspective of using hyperspectral imaging during cutting tests
Author(s) -
Maksim Antonov,
Ali Zahavi,
Rajesh Kumar,
Mart Tamre,
Piotr Klimczyk
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1140/1/012029
Subject(s) - hyperspectral imaging , materials science , boron nitride , characterization (materials science) , plasma cutting , tin , metallurgy , composite material , computer science , nanotechnology , artificial intelligence
The performance of cutting tool materials (CTMs) influences the quality and lifetime of parts produced with their help. Unexpected fracturing or other failures of the tools lead to defects of parts that exaggerate materials fatigue and fracture processes. For the purpose of Industry 4 and future generations of factories it is important to enable in-situ monitoring of cutting processes while hyperspectral imaging can serve as a powerful tool. Cubic boron nitride (cBN) has extreme hardness and can provide improved wear resistance if mixed with other CTMs. Besides, such materials can be used without cooling liquids that helps to mitigate workplace health risks. The aim of the current work was to understand how well current hyperspectral imaging technologies can track the changes in performance of CTMs with addition of cBN. The paper presents the results of multiple in-situ (obtained during cutting with real lathe) and static (before or after cutting) tests performed with hyperspectral camera. The wear rate of CTMs and roughness of workpieces were measured with the help of scanning electron microscope and 3D optical profiler respectively. The effect of cBN content and effect of TiN or ZrO2 additives on performance of alumina-based CTMs produced by spark plasma sintering technique is presented.