Prediction model for single-point diamond tool-tip wear during machining of optical grade silicon

Jumare, Abubakar I.; Abou-El-Hossein, Khaled; Goosen, William E.; Cheng, Yung‐Chen; Abdulkadir, Lukman N.; Odedeyi, Peter Babatunde; Liman, Muhammad Mukhtar

doi:10.1007/s00170-018-2402-2

Cited by 19 publications

(5 citation statements)

References 23 publications

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“…Conventional machining of silicon lenses with low surface roughness and complex profiles was costly and time consuming. Jumare et al 44 investigated the tool wear during diamond turning of optical silicon. They found that the flank wear land had micro-chippings, micro-grooves and notches.…”

Section: Surface Roughness Of Precision-machined Advanced Engineering Materialsmentioning

confidence: 99%

Surface roughness of machined wood and advanced engineering materials and its prediction: A review

Zhong

2021

Advances in Mechanical Engineering

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This article discusses the surface roughness of wood and advanced engineering materials after machining and its prediction. The topics are surface roughness of precision-machined advanced engineering materials, machining of WC and Inconel, rapidly solidified Al alloys, surface roughness of wood materials, and prediction of surface roughness. Findings include that ductile streaks on silicon and glass surfaces ground or lapped with inexpensive machines largely reduced the polishing time to obtain the required surface roughness. Abrasive jet machining could remove the patterns from recycled wafers and improve the surface roughness. The roughness of WC-Co coatings was significantly improved by using the method of fast regime fluidized bed machining. As beryllium is a toxic element, the rapidly solidified Al alloy may be a good insert material to replace BeCu. Higher bonding strengths resulted from rougher surfaces of wood samples. Wood samples had reduced bonding strengths after soaking in water. Optimum artificial neural networks (ANNs) with necessary inputs could accurately predict the roughness values. ANNs trained using particle swarm optimization and genetic algorithms could predict surface roughness better than typical ANNs. Minimum quantity lubrication is a hot research topic to minimize the amount of the fluid for cost and environmental considerations.

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Section: Surface Roughness Of Precision-machined Advanced Engineering Materialsmentioning

confidence: 99%

Surface roughness of machined wood and advanced engineering materials and its prediction: A review

Zhong

2021

Advances in Mechanical Engineering

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“…Ravindra et al reduced the surface roughness of quartz glass after turning by optimizing the processing parameters and surface roughness (Ra) values of less than 45 nm without sub surface damage were obtained [18]. Jumare et al achieved nano metric surface finish quality results with high cutting speed and appropriate feed rate, and the tool wear rate was the minimum in this situation [19]. In addition, after observing the wear area of the tool, Zhou et al proposed that the tool wear was mainly caused by the hard chips [20], Yoshino et al found that when water or kerosene was used as cutting fluid, the tool wear rate could be reduced [21].…”

Section: Introductionmentioning

confidence: 99%

The effect of tool wear on the damaged layer thickness and tool wear rate in ultra-precision turning of quartz glass

Liu

Tong

et al. 2023

J. Micromech. Microeng.

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Quartz glasses have been extensively used for many fields, such as semiconductor technology, optical instruments, inertial navigation and others. Ultra-precision turning with diamond tools can achieve high surface accuracy when processing non-ferrous materials. In recent years, ultra-precision turning has also been tried to be applied to process brittle materials, but there are constraints including small removal amount and tool wear. When diamond tools are used to cut quartz glass, tool wear occurs under the combined action of thermal effect and mechanical friction, which will affect the damaged layer thickness of the processed quartz glass. In this paper, the tool wear factor is led into the calculation of the extrusion volume, and the damaged layer thickness is calculated by the extrusion volume. Combined with the results of quartz glass turning experiments and the calculated results by simulation, the effect of tool wear factor on the damaged layer thickness and the tool wear rate is analyzed. The analysis shows that tool wear will lead to chip fracture thickness decrease and extrusion volume increase. Combined action of these two aspects, the damage layer thickness keeps unchanged at first and then rises with the increase of tool wear. In addition, the experimental results show that the tool wear rate rises with the increase of tool wear.

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“…Heamawatanachai et al presented an analytical, ductile cutting force model of a novel micromachining tool that was based on micro-orbital motion of a SPDT and verified the model experimentally [ 20 ]. In the study of Jumare et al, the influence of various machining parameters on the diamond tool-tip wear during single-point diamond turning (SPDT) of optical grade silicon was examined and proposed a prediction model for single-point diamond tool wear [ 21 ]. Yanbin Zhang et al simplified the grinding process to a single-cone crystal grain and proposed a theoretical force model that considered the mechanism of material removal and plastic accumulation to explore the comprehensive influence of material removal and plastic accumulation on the grinding force model [ 22 ].…”

Section: Introductionmentioning

confidence: 99%

Model of Ploughing Cortical Bone with Single-Point Diamond Tool

Wang

Meng

et al. 2021

Materials

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Generating topological microstructures on the surface of cortical bone to establish a suitable microenvironment can guide bone cells to achieve bone repair. Single-point diamond tools (SPDTs) have advantages in efficiency and flexibility to fabricate surface microstructures. However, the cutting force during ploughing cannot be predicted and controlled due to the special properties of cortical bone. In this paper, a novel cutting model for ploughing cortical bone using an SPDT was established, and we comprehensively considered the shear stress anisotropy of the bone material and the proportional relationship between the normal force and the tangential force. Then, the orthogonal cutting experiment was used to verify the model. The results show that the error of calculated value and the experimental data is less than 5%. The proposed model can be used to assist the fabrication of microstructures on cortical bone surface using an SPDT.

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Prediction model for single-point diamond tool-tip wear during machining of optical grade silicon

Cited by 19 publications

References 23 publications

Surface roughness of machined wood and advanced engineering materials and its prediction: A review

Surface roughness of machined wood and advanced engineering materials and its prediction: A review

The effect of tool wear on the damaged layer thickness and tool wear rate in ultra-precision turning of quartz glass

Model of Ploughing Cortical Bone with Single-Point Diamond Tool

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