Precise measurement of worn-out tool diameter using cutting edge features during progressive wear analysis in micro-milling

Wear ◽  
2021 ◽  
pp. 204169
Author(s):  
Suman Saha ◽  
Sankha Deb ◽  
Partha Pratim Bandyopadhyay
2015 ◽  
Vol 105 (11-12) ◽  
pp. 805-811
Author(s):  
E. Uhlmann ◽  
D. Oberschmidt ◽  
A. Löwenstein ◽  
M. Polte ◽  
I. Winker

Die Prozesssicherheit beim Mikrofräsen lässt sich mit einer gezielten Schneidkantenverrundung erheblich steigern. Dabei werden durch verschiedene Präparationstechnologien unterschiedliche Geometrien und Einflüsse auf den Fräsprozess erzeugt. Der Fachbeitrag behandelt den Einsatz präparierter Mikrowerkzeuge in Zerspanversuchen, in denen auf die Zerspankräfte, den Verschleiß sowie die Oberflächengüten eingegangen wird.   Process reliability in micro milling can be increased by a defined cutting edge preparation. Different cutting edge preparations cause different effects on tool behavior in the downstream micro milling process. In this paper, the process forces, the tool wear and the surface quality of prepared micro milling tools are characterized in cutting tests.


Micromachines ◽  
2018 ◽  
Vol 9 (11) ◽  
pp. 568 ◽  
Author(s):  
Zhiqiang Liang ◽  
Peng Gao ◽  
Xibin Wang ◽  
Shidi Li ◽  
Tianfeng Zhou ◽  
...  

Tool wear is a significant issue for the application of micro end mills. This can be significantly improved by coating materials on tool surfaces. This paper investigates the effects of different coating materials on tool wear in the micro milling of Ti-6Al-4V. A series of cutting experiments were conducted. The tool wear and workpiece surface morphology were investigated by analyzing the wear of the end flank surface and the total cutting edge. It was found that, without coating, serious tool wear and breakage occurred easily during milling. However, AlTiN-based and AlCrN-based coatings could highly reduce cutting edge chipping and flank wear. Specifically, The AlCrN-based coated mill presented less fracture resistance. For TiN coated micro end mill, only slight cutting edge chipping occurred. Compared with other types of tools, the AlTiN-based coated micro end mill could maximize tool life, bringing about an integrated cutting edges with the smallest surface roughness. In short, the AlTiN-based coating material is recommended for the micro end mill in the machining of Ti-6Al-4V.


Procedia CIRP ◽  
2016 ◽  
Vol 46 ◽  
pp. 214-217 ◽  
Author(s):  
E. Uhlmann ◽  
D. Oberschmidt ◽  
A. Löwenstein ◽  
Y. Kuche

Procedia CIRP ◽  
2014 ◽  
Vol 14 ◽  
pp. 349-354 ◽  
Author(s):  
E. Uhlmann ◽  
D. Oberschmidt ◽  
Y. Kuche ◽  
A. Löwenstein

Author(s):  
Said Jahanmir ◽  
Michael J. Tomaszewski ◽  
Hooshang Heshmat

Small precision parts with miniaturized features are increasingly used in components such as sensors, micro-medical devices, micro-fuel cells, and others. Mechanical micromachining processes, e.g., turning, drilling, milling and grinding are often used for fabrication of miniaturized components. The small micro-tools (50 μm to 500 μm diameter) used in micromachining limit the surface speeds achieved at the cutting point, unless the rotational speeds are substantially increased. Although the cutting speeds increase to 240 m/min with larger diameter tools (e.g., 500 μm) when using the highest available spindle speed of 150,000 rpm, the cutting speed with the smaller 50 μm tools is limited to 24 m/min. This low cutting speed at the tool tip is much smaller than the speeds required for efficient cutting. For example, in macro-milling of aluminum alloys the recommended speed is on the order of 60–200 m/min. The use of low cutting speeds limits the production rate, increases tool wear and tendency for burr formation, and limits the degree of dimensional tolerance and precision that can be achieved. The purpose of the present paper is to provide preliminary results that show the feasibility of ultra high-speed micro-milling of an aluminum alloy with respect to surface quality and burr formation. A new ultra high-speed spindle was used for micro-milling of an aluminum alloy with micro-end-mills ranging in diameter from 51 μm to 305 μm. Straight channels were machined to obtain an array of square patterns on the surface. High surface cutting speeds up to 340 m/min were achieved at 350,000 rpm. Inspection of the machined surfaces indicated that edge quality and burr formation tendency are related to the undeformed chip thickness, and therefore the cutting speed and feed rate. The quantity of burrs observed on the cut surfaces was generally small, and therefore, the burr types were not systematically determined. Cutting with the 305 μm tool at a cutting speed of 150 m/min produced an excellent cut quality using a chip thickness of 0.13 μm. However, the cut quality deteriorated as the chip thickness was decreased to 0.06 μm by increasing the cutting speed to 340 mm/min. This result is consistent with published data that show the dependence of bur formation on ratio of chip thickness to tool tip radius. The channel widths were also measured and the width of channels cut with the small diameter tools became larger than the tool diameter at higher speeds. The dependence of the channel widths on rotational speed and the fact that a similar variation was not observed for larger diameter tools, suggested that this phenomena is related to dynamic run-out of the tool tip, which increases the channel width at higher speeds.


2004 ◽  
Vol 70 (700) ◽  
pp. 3556-3563 ◽  
Author(s):  
Panart KHAJORNRUNGRUANG ◽  
Takashi MIYOSHI ◽  
Yasuhiro TAKAYA ◽  
Takashi HARADA ◽  
Soichiro ISAGO

2020 ◽  
Vol 8 (2) ◽  
Author(s):  
Gusri Akhyar Ibrahim ◽  
Endra Saputra ◽  
Suryadiwansa Harun ◽  
Eko Agus Supriyanto ◽  
Armulani Patihawa

One of the ingredients that are popular now is titanium, but titanium is a material that is difficult to process using conventional milling machining because of the poor thermal conductivity of the material so that the high-temperature machining process produced in the cutting zone causes plastic deformation in cutting tools and increased chemical reactivity in titanium. High-speed micro-milling machining can be used for micro machining of hard metals or alloys that are difficult to achieve at low speeds. Micro milling machining in titanium material 6Al-4V ELI with variations in milling tool diameter 1 and 2 mm, spindle speed 10.000 and 15.000 rpm, feed 0,001 and 0,005 mm/rev, depth of cut 100 and 150 μm, which then do data processing using the method taguchi full factorial and theoretical analysis. The results showed that the diameter of the tool and into the depth of cut the most effect on surface roughness, the greater the tool diameter of the milling produced a smaller roughness value, this is inversely proportional to the depth of the cut. The lowest roughness value is 0,26 and the highest roughness value is 0,9. Keywords: Micro milling machining, titanium 6Al-4V ELI, surface roughness.


Procedia CIRP ◽  
2021 ◽  
Vol 102 ◽  
pp. 109-114
Author(s):  
Katja Klauer ◽  
Nicolas Altherr ◽  
Matthias Eifler ◽  
Benjamin Kirsch ◽  
Volker Böß ◽  
...  

2020 ◽  
Vol 143 (5) ◽  
Author(s):  
Alwin Varghese ◽  
Vinay Kulkarni ◽  
Suhas S. Joshi

Abstract Tool condition monitoring is difficult in micro-milling due to irregular wear and chipping of the cutting edges, which lead to unexpected tool breakage. This study demonstrates the use of force data to reliably predict different tool life stages until tool breakage, while micro-milling hard materials like stainless steel (SS304) using tungsten carbide tools of 500 μm diameter. Extensive experiments involving machining of 465 slots over 62 min of machining time were performed in this study. The resulting voluminous force data were analyzed to divide the tool life into three stages based on the variation in the forces and other related features. The first stage is the initial 12.5% of the tool life, second stage consists of 12.5–70% of tool life, and the third stage is from 70% to 100% tool life. The analysis of the tool wear and cutting forces shows that the average tool diameter reduces by 32 μm, 67 μm and 108 μm, and the average resultant cutting force were 2.45 N, 4.17 N, and 4.93 N in stage 1, 2, and 3, respectively. To avoid catastrophic breakage of the tool, the tool life stages are predicted from the force data using machine learning models. Among the machine learning models, random forest method gave a better prediction accuracy of 88.5%. The model was further improved by incorporating the initial cutting edge radius as an additional feature, and the variance in the prediction was seen to drop by 48.76%.


Procedia CIRP ◽  
2018 ◽  
Vol 77 ◽  
pp. 662-665 ◽  
Author(s):  
E. Uhlmann ◽  
Y. Kuche ◽  
J. Polte ◽  
M. Polte

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