Investigation on the Micro Cutting Mechanism and Surface Topography Generation in Ultraprecision Diamond Turning

Wu, Quanhui; Chen, Guoda; Liu, Qinglin; Pan, B.; Chen, Wanqun

doi:10.3390/mi13030381

Cited by 5 publications

(3 citation statements)

References 30 publications

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“…Surface quality expressed through surface roughness is a significant factor in machining. Speaking product quality through surface quality also indirectly indicates the condition of the cutting tool [8,16,17]. In which the cutting mode parameters have a significant influence on the surface quality and tool wear.…”

Section: Engineeringmentioning

confidence: 99%

Combined analysis of acoustic emission and vibration signals in monitoring tool wear, surface quality and chip formation when turning SCM440 steel using MQL

Dung¹,

Thien²,

Pham³

et al. 2023

Eureka: PE

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With modern production, Minimum Quantity Lubricant (MQL) technology has emerged as an alternative to conventional liquid cooling. The MQLs is an environmentally friendly lubricant method with low cost while meeting the requirements of machining conditions. In this study, the experimental and analytical results show that the obtained acoustic emission (AE) and vibration signal components can effectively monitor various circumstances in the SCM440 steel turning process with MQL, such as surface quality and chip formation as cutting tool conditions. The AE signals showed a significant response to the tool wear processes. In contrast, the vibration signal showed an excellent ability to reflect the surface roughness during turning with MQL. The chip formation process through the cutting mode parameters (cutting speed, feed and depth of cut) was detected through analysis amplitude of the vibration components Ax, Ay and Az and the AE signal. Finally, Gaussian process regression and adaptive neuro-fuzzy inference systems (GPR-ANFIS) algorithms were combined to predict the surface quality and tool wear parameters of the MQL turning process. Tool condition monitoring devices assist the operator in monitoring tool wear and surface quality limits, stopping the machine in case of imminent tool breakage or lower surface quality. With the unique combination of AE and vibration analysis model and the training and testing samples established by the experimental data, the corresponding average prediction accuracy is 97.57 %. The highest prediction error is not more than 3.8 %, with a confidence percentage of 98 %. The proposed model can be used in industry to predict surface roughness and wear of the tools directly during turning

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Section: Engineeringmentioning

confidence: 99%

Combined analysis of acoustic emission and vibration signals in monitoring tool wear, surface quality and chip formation when turning SCM440 steel using MQL

Dung¹,

Thien²,

Pham³

et al. 2023

Eureka: PE

View full text Add to dashboard Cite

show abstract

“…The growing prevalence of engineered textured surfaces can be attributed to their ability to enhance the performance of component surfaces in various application areas, such as tribology [ 1 ], wettability [ 2 ], optics [ 3 ], bioengineering, and thermal properties [ 4 , 5 ]. The widespread incorporation of surface texturing across various industries has motivated the pursuit of sophisticated manufacturing techniques that can effectively create intricate surface morphologies.…”

Section: Introductionmentioning

confidence: 99%

Theoretical and Experimental Investigation of Surface Textures in Vibration-Assisted Micro Milling

Song,

Zhang,

Jing

et al. 2024

Micromachines

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Vibration-assisted micro milling is a promising technique for fabricating engineered mi-cro-scaled surface textures. This paper presents a novel approach for theoretical modeling of three-dimensional (3D) surface textures produced by vibration-assisted micro milling. The proposed model considers the effects of tool edge geometry, minimum uncut chip thickness (MUCT), and material elastic recovery. The surface texture formation under different machining parameters is simulated and analyzed through mathematical modeling. Two typical surface morphologies can be generated: wave-type and fish scale-type textures, depending on the phase difference between tool paths. A 2-degrees-of-freedom (2-DOF) vibration stage is also developed to provide vibration along the feed and cross-feed directions during micro-milling process. Micro-milling experiments on copper were carried out to verify the ability to fabricate controlled surface textures using the vibration stage. The simulated and experimentally generated surfaces show good agreement in geometry and dimensions. This work provides an accurate analytical model for vibration-assisted micro-milling surface generation and demonstrates its feasibility for efficient, flexible texturing.

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“…Methods such as micro-grinding, micro-milling, and micropolishing are employed to modify surface structure of the tools to achieve a well-defined cutting edge, and reduce any defects that can significantly affect performance [12,13]. Within the cutting tool industry, a variety of surface treatment methods with suitable machining parameters have been developed and implemented over an extended period of time [14][15][16][17]. The aforementioned processes can be categorised into three distinct approaches: mechanical, chemical, and electrochemical.…”

Section: Introductionmentioning

confidence: 99%

An Investigation into the Surface Integrity of Micro-Machined High-Speed Steel and Tungsten Carbide Cutting Tools

Dang,

Singh,

Navarro-Devia

et al. 2023

Micromachines

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The performance and lifespan of cutting tools are significantly influenced by their surface quality. The present report highlights recent advances in enhancing the surface characteristics of tungsten carbide and high-speed steel cutting tools using a novel micro-machining technique for polishing and edge-honing. Notably, the main aim was to reduce the surface roughness while maintaining the hardness of the materials at an optimal level. By conducting a thorough analysis of surfaces obtained using different techniques, it was found that the micro-machining method effectively decreased the surface roughness of the cutting tools the most effectively out of the techniques investigated. Significantly, the surface roughness was reduced from an initial measurement of 400 nm to an impressive value of 60 nm. No significant change in hardness was observed, which guarantees the maintenance of the mechanical properties of the cutting tools. This analysis enhances the comprehension of surface enhancement methodologies for cutting tools through the presentation of these findings. The observed decrease in surface roughness, along with the consistent hardness, exhibits potential for improving tool performance. These enhancements possess the capacity to optimise manufacturing processes, increase tool reliability, and minimise waste generation.

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Investigation on the Micro Cutting Mechanism and Surface Topography Generation in Ultraprecision Diamond Turning

Cited by 5 publications

References 30 publications

Combined analysis of acoustic emission and vibration signals in monitoring tool wear, surface quality and chip formation when turning SCM440 steel using MQL

Combined analysis of acoustic emission and vibration signals in monitoring tool wear, surface quality and chip formation when turning SCM440 steel using MQL

Theoretical and Experimental Investigation of Surface Textures in Vibration-Assisted Micro Milling

An Investigation into the Surface Integrity of Micro-Machined High-Speed Steel and Tungsten Carbide Cutting Tools

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