Performance of Al2O3-cBN materials and the perspective of using hyperspectral imaging during cutting tests

Abstract

The performance of cutting tool materials (CTMs) influences the quality and lifetime of the parts produced using these tools. Unexpected fracturing or other failures of the tools lead to defects of the parts, which accelerates material fatigue and fracture processes. For the purpose of Industry 4.0 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. Moreover, such materials can be used without cutting fluids, which helps to mitigate health risks in the workplace. The aim of the current work was to understand how well the current hyperspectral imaging technologies can track the changes in the performance of CTMs with the addition of cBN. This paper presents the results of multiple in-situ (obtained during cutting with a real lathe) and static (before or after cutting) tests performed with hyperspectral camera. The wear rate of CTMs and the roughness of workpieces were measured with the help of a scanning electron microscope and a 3D optical profiler respectively. The effect of cBN content and the effect of TiN or ZrO2 additives on the performance of alumina-based CTMs produced by spark plasma sintering technique is presented.

Keywords

• wear resistance
• hyperspectral imaging
• cubic boron nitride
• cutting test
• industry 4.0
• automation.