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

Abstract

Lôikeriistade materjalide (LRM) käitumine môjutab nende abil valmistatud toodete kvaliteeti ja eluiga. Tööriistade ootamatu purunemine vöi teised forked toovad kaasa toodete defekte, mis kiirendavad materjalide väsimist ja purunemis-protsesse. Industry 4.0 ja tuleviku tehaste jaoks on oluline, et oleks vöimalik kohapeal jälgida löikeprotsesside kulgu, kus hüperspektraal-pilditehnika vöiks olla vöimas tööriist. Kuubiline boornitriid (cBN) on äärmiselt köva ja vöib teiste LRM-dega segatuna tagada parema kulumiskindluse. Lisaks eelnevale saab selliseid materjale kasutada löiketöötluseks ilma jahutusvedelikuta, mis aitab vähendada terviseriske töökohal. Käesoleva töö eesmärk oli aru saada, kui hästi suu-davad praegused hüperspektraal-pilditehnikad jälgida LRM-de käitumise muutusi cBN-i lisamise puhul. Selles artiklis esitatakse tulemusi, mis on saadud reaalse treipingiga treimisel VNIR hüperspektraalkaameraga tehtud staatiliste piltide (vahetult enne vöi pärast löikamist) analüüsil. LRM-de kulumiskiirus ja toorikute löppkaredus möödeti vastavalt skaneeriva elektronmikroskoobiga ja 3D-optilise profilomeetriga. On näidatud cBN sisalduse ja TiN vöi ZrO2 lisandite möju sädeplasma paagutamise meetodil valmistatud alumiiniumoksiidi sideainega LRM käitumisele.

Alternate abstract:

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.

Headnote

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.

Key words: wear resistance, hyperspectral imaging, cubic boron nitride, cutting test, Industry 4.0, automation.

Lôikeriistade materjalide (LRM) käitumine môjutab nende abil valmistatud toodete kvaliteeti ja eluiga. Tööriistade ootamatu purunemine vöi teised forked toovad kaasa toodete defekte, mis kiirendavad materjalide väsimist ja purunemis-protsesse. Industry 4.0 ja tuleviku tehaste jaoks on oluline, et oleks vöimalik kohapeal jälgida löikeprotsesside kulgu, kus hüperspektraal-pilditehnika vöiks olla vöimas tööriist. Kuubiline boornitriid (cBN) on äärmiselt köva ja vöib teiste LRM-dega segatuna tagada parema kulumiskindluse. Lisaks eelnevale saab selliseid materjale kasutada löiketöötluseks ilma jahutusvedelikuta, mis aitab vähendada terviseriske töökohal. Käesoleva töö eesmärk oli aru saada, kui hästi suu-davad praegused hüperspektraal-pilditehnikad jälgida LRM-de käitumise muutusi cBN-i lisamise puhul. Selles artiklis esitatakse tulemusi, mis on saadud reaalse treipingiga treimisel VNIR hüperspektraalkaameraga tehtud staatiliste piltide (vahetult enne vöi pärast löikamist) analüüsil. LRM-de kulumiskiirus ja toorikute löppkaredus möödeti vastavalt skaneeriva elektronmikroskoobiga ja 3D-optilise profilomeetriga. On näidatud cBN sisalduse ja TiN vöi ZrO2 lisandite möju sädeplasma paagutamise meetodil valmistatud alumiiniumoksiidi sideainega LRM käitumisele.

1.INTRODUCTION

Despite the fact that 3D printing (additive manufacturing) is gaining popularity nowadays, the cutting of materials (subtractive manufacturing) is still the prevailing method for production of components [1]. Usually, cutting fluids are used to reduce the friction and cool down the cutting tools. However, these fluids can cause significant health risks and illnesses such as different types of contact dermatitis, occupational acne, tracheitis, esophagitis, bronchitis, asthma, allergy hypersensitivity pneumonitis and worsening of pre-existing respiratory problems [1,2]. New types of cutting tools have to be developed to reduce such risks.

Cubic boron nitride (cBN) has extreme hardness and can provide improved wear resistance if mixed with other cutting tool materials (CTMs). It is one of the hardest materials and is thermally more stable than tungsten carbide or diamond [3,4]. The previous studies by P. Klimczyk et al. [4-6] demonstrated that it is possible to sinter composites with up to 30 vol% of cBN with alumina matrix (binder) with the help of spark plasma sintering (SPS) equipment. The reason is that with such low concentration of reinforcement the consolidation can be performed with lower pressure (usually not higher than 0.5 GPa) and temperature than usually required for materials with high content of reinforcement [7]. The SPS technology provides significant reduction in cost with respect to the high-pressure and high-temperature devices.

Degradation of cutting tools should be avoided since it can lead to the defects of produced parts and result in reduced service life and/or unexpected failures [8]. That is why any improvement in the monitoring of the tool's and workpiece's performance (especially in-situ) is of high importance, from the point of view of Industry 4.0 and next generations of production factories.

Hyperspectral imaging (HSI) is known for processing the information over the electromagnetic spectrum to identify various materials by obtaining the spectrum of each pixel of the image [9,10]. In other words, HSI combines the power of spectroscopy and digital image processing to identify the materials in a scene. While HSI is a fast-growing area in the remote sensing field for earth observation, emerging mobile hyperspectral cameras have made it possible to use them for material classification and object recognition in the real-world scale [11].

2.MATERIALS AND METHODS

2.1. Materials

Five alumina-based cutting tool materials reinforced by cubic boron nitride without or with TiN or ZrO2 additives were produced by spark plasma sintering technique - see Table 1. Their physical and mechanical properties were measured in the previous work of P. Klimczyk et al. [6]. The workpiece material was hot-rolled normalized unalloyed medium carbon (main constituents: 0.45% C, 0.2% Si, 0.7% Mn, base - Fe) steel C45 according to EN 10083-2.

2.2. Wear rate and roughness measurements

The cutting tests were performed on Sumore SP2138 lathe operated with computer numerical control (CNC). The test samples produced by SPS were cut into the required shape and then the edges were ground by diamond disc with cooling (Fig. 1A). The total number of cuts with a depth of 0.075 mm and a width of 80 mm was 70; feed rate was 0.05 mm per rotation (0.88 mm s-1); average cutting speed was 100 m min-1 (1.67 m s-1); total duration of cutting was 105.66 min (6342 s); total length of the removed chip was 10566 m, Fig. 1B. The linear and volumetric wear rates were measured according to scanning electron microscope (Hitachi TM1000, SEM) images. The SEM images of the worn cutting tools from three sides with at least three magnifications were imported into Aut°CAD 2020 software and analysed. Volumetric wear was approximated by triangular pyramids, Fig. 1C. Roughness and 3D topography were measured with the help of Bruker ContourGT-K0+ optical 3D profiler.

2.3.Hyperspectral investigations during and after the cutting test

The system was comprised mainly of a hyperspectral camera, a light source, the test sample fixed in the lathe, and a frame for fixation of components (Fig. 2). The mobile hyperspectral camera used for conducting these experiments was SPECIM IQ (Spectral Imaging Ltd., Finland), a VNIR (visible-near-infrared) camera which collects the spectrum of each pixel of the image in the range of 400-1000 nm; number of the bands was 204; spectral resolution was 7 nm; spatial sampling was 512 pix; acquisition mode was Pushbroom (line-scan imaging) [12]. The recording of one image took approximately 5 minutes. Similar to other computer vision applications, the light source used during the image acquisition phase plays a vital role in the validity of the results. Incandescent lights were applied as the best illumination source for indoor hyperspectral imaging applications [13]. A frame was assembled to install the incandescent light in an appropriate height above the field of view (FOV).

The spectrum of the insert material (before testing) and steel workpiece (after testing) was extracted in static conditions (without movement), while additionally images of the cutting zone were taken in-situ during machining to study the effect of feed rate (2.5, 5.0 mm/s), rotational speed of the workpiece (500, 1000 rpm / 8.33, 16.66 rps) and depth of cutting (0.1, 0.2 mm).

For acquiring the suitable images for analysis, more than 50 images from the scene from different angles with different scenarios were taken. These images were taken to find the best distance from the illumination source to is clearly visible that the surface after cutting with the A100 material is irregular, and in many places, the cuts are overlapping. The latter is an indication of the dulling of the cutting tool, formation of the build-up and resultant overheating of the workpiece and tool. Extreme local overheating of the tool is critical for ceramic materials and can lead to cracking. The chipping of the A100 cutting tool is indicated in Fig. 5A.

The nose (tip) radius of the cutting tool is usually provided to enable longer life [15]. The tools used in the current work were without radius to make it possible to reduce consumption (waste) of the workpiece material (to reduce depth of cut and feed). We assume that the tool material that works well in such harsh conditions will show good performance with rounded nose as well. It is important to mention that there was a self-organization process during tribological testing that actually led to a more suitable shape of nose - see Fig. 5A and B. The final shape of nose was close to rounded and the radius was about 100 pm.

The same materials were tested by two laboratory test methods (another work that is currently in the publishing process) - reciprocative and surface fatigue. The A20B15Z material had a significantly lower wear rate than the reference A100 material only in the surface fatigue test. This was explained by the fact that the removal of cBN grains by fatigue mechanism was intensified during the reciprocative (direction of friction force is changing) test. This can lead to the possible conclusion that the laboratory surface fatigue test (ball hitting the surface of the test sample) is suitable for the prediction of performance in cutting conditions. However, during the surface fatigue test, the A20B10T material had at least two times higher wear than A20B, which does not correspond to the results of the current cutting tests. The better relative performance ofA20B10T during the cutting test could be explained by the fact that TiN, when added into cutting tools based on WC-Co, contributes to the reduction of build-up (compare Fig. 5C and E), which is favourable for the reduction of friction, temperature in the cutting zone, thermal shocks, cracking, etc. Thus, a careful selection of laboratory test methods mimicking real conditions is required.

The analysis of SEM images of the cutting inserts allows to draw the conclusion that the formation of buildup, removal of alumina matrix between cBN grains, removal of unsupported cBN grains are the main steps of wear of the studied composites. It was detected that these processes are continuous but ongoing in a cyclic manner. The removal of matrix takes some time, then the removed matrix provides better conditions for build-up while a well-developed build-up leads to higher frictional heating of the surface, which will result in thermal damage (microcracks were detected in the alumina matrix) and the removal of build-up and some of cBN grains. Then, the cycle is repeated.

The currently available and applied hyperspectral camera is highly sophisticated, it requires careful handling. One measurement takes approximately 5 minutes and the obtained results require comprehensive analysis. It should be mentioned that another available hyperspectral camera used during the first stages of the research lost the precision of measurement due to minor mechanical shocks even with proper handling. There is great hope that future generations of hyperspectral cameras will be more oriented to industrial cutting applications, and will be more robust. Currently, there is a great boom in using hyperspectral imaging in different areas such as agriculture, forestry, oceanography, medicine, geology, security, archaeology, recycling, but special cameras for cutting applications are not yet available [16,17]. It is expected that future generations suitable for Industry 4.0 factories will have a wider spectrum, be faster and will be able to monitor not only the workpiece material (sufficiently large area) but also the nose (tip) of a cutting insert and be able to work in fully automatic regime.

5.CONCLUSIONS

* It was detected that the wear resistance of alumina during dry cutting can be significantly (up to 3 times according to volumetric wear) improved by the addition of 20% of cBN and 15% of ZrO2 while providing the same roughness for the produced parts. Such material can be used without cooling liquids to mitigate occupational health risks.

* It was detected that unreinforced reference pure alumina exhibits chipping of the cutting edge, which can lead to defects of the parts, contributing to their fatigue and fracture processes.

* It was possible to establish in-situ monitoring of the cutting process by hyperspectral camera.

* Spectral signatures taken during in-situ testing show that doubling of the value of feed rate, rotational speed of the workpiece and depth of cutting resulted in max 0.1%, 1.0% and 1.0 % change of the workpiece reflectance respectively, which was not sufficient for tracking the tool performance. It is advisable to use a near-infrared camera (1000-1700 nm) to achieve more precise identification.

ACKNOWLEDGEMENTS

The authors would like to acknowledge the support from the Estonian Ministry of Education and Research (M-ERA.NET DURACER ETAG18012, PRG643). The publication costs of this article were covered by the Estonian Academy of Sciences and Tallinn University of Technology.

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