Development of PCBN micro ball-end mill with multi-edge and spherical flank face

Du, Yuchao; Liang, Zhiqiang; Ma, Yue; Su, Zhipeng; Chen, Rui; Zhou, Tianfeng; Wang, Xibin

doi:10.1016/j.jmapro.2022.10.008

Cited by 10 publications

(2 citation statements)

References 27 publications

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“…The use of NMMCs in the manufacturing industry has posed several challenges for machinists. 15 Cutting through difficult materials using standard cutting tools leads to high tool wear, increasing the cost of manufacturing. Aluminum alloy 8081 is a wrought aluminum alloy that exhibits good mechanical properties such as high strength, good ductility, and excellent corrosion resistance.…”

Section: Introductionmentioning

confidence: 99%

An experimental approach to characterize the performance of PCD and PCBN tools in milling nano Al-8081-Zr/Mg/TiO2 metal matrix composites using multi-sensor data fusion

Mouli,

Reddy,

Prakash

2024

Proceedings of the Institution of Mechanical Engineers, Part C:

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To prevent the quality of the finished product from declining, precision manufacturing procedures need reliable cutting tool wear detection. Cutting tool material, workpiece attributes, cutting conditions and conditions, and excessive cutting forces creating vibrations causing chatter impacting tool wear finally leading to tool failure all have an impact on tool performance. This paper presents a multisensory data fusion approach that assigns sensors at nearfield sites during the machining process to monitor the tool condition. The study investigates the performance of polycrystalline diamond (PCD) and Polycrystalline Cubic Boron Nitride (PCBN) cutting tools during the machining of nano metal matrix composites reinforced with Zr/Mg/TiO2 (15%). The method correlates signal features with experimental results to provide a reliable empirical approach to monitor the cause of tool flank wear and displacement, leading to failure. The experimental investigation it is found the cutting forces showed significant effect on flank wear affecting surface finish and tool life. Tool performance was successful monitoring and predicted instantly based on the signature analysis of vibrations and forces during machining helped accurately analyzed factors affecting tool wear at uncertain cutting conditions using FDA analysis. The study provides insights into the PCD and PCBN tools’ performance characteristics.

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Section: Introductionmentioning

confidence: 99%

An experimental approach to characterize the performance of PCD and PCBN tools in milling nano Al-8081-Zr/Mg/TiO2 metal matrix composites using multi-sensor data fusion

Mouli,

Reddy,

Prakash

2024

Proceedings of the Institution of Mechanical Engineers, Part C:

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“…It also maintains a high chemical resistance in contact with iron [1]. As a result, CBN is widely used to produce the edges of cutting tools [2]. Milling cutters with CBN edges allow machining of materials in hardened state, replacing traditional, low-efficiency grinding or electrical discharge machining processes by milling or turning [3][4].…”

Section: Introductionmentioning

confidence: 99%

Surface Roughness Prediction in the Hardened Steel Ball-End Milling by Using the Artificial Neural Networks and Taguchi Method

Matras

2024

Adv. Sci. Technol. Res. J.

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The paper provides an analysis of the impact of the values of cutting tool inclination strategies and angles measured in the parallel and perpendicular to feed direction, radial depth of cut and feedrate on the surface roughness. The workpiece was made of the AISI H13 steel, hardness 50 HRC, and was machined using a ball-nosed end mill with CBN edges. The research methodology involved experiments conducted based on the Taguchi orthogonal array, optimization of parameters with the use of Taguchi method and process modelling using neural networks. Thanks to the use of neural networks, the analyses were performed for various levels of machining efficiency, obtained as a result of different radial depths of cut and feedrates. In order to obtain mathematical models welldescribing strongly nonlinear impact of the cutting tool inclination strategies and angles, a separate neural network learned for each tool inclination strategy. The prediction of results was made using a set of neural networks. The analyses and experiments resulted in surfaces with very low Ra parameter of 0.16 mm and mathematical models with a good fit to the experimental data. Values of the cutting tool inclination angle that allow obtaining the surface of specific surface roughness were specified for various levels of machining performance.

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Fabrication of semicircular micro-grooves on Ti6Al4V by through-mask scanning electrochemical machining

Miao

Chen

et al. 2023

Int J Adv Manuf Technol

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Development of PCBN micro ball-end mill with multi-edge and spherical flank face

Cited by 10 publications

References 27 publications

An experimental approach to characterize the performance of PCD and PCBN tools in milling nano Al-8081-Zr/Mg/TiO2 metal matrix composites using multi-sensor data fusion

An experimental approach to characterize the performance of PCD and PCBN tools in milling nano Al-8081-Zr/Mg/TiO2 metal matrix composites using multi-sensor data fusion

Surface Roughness Prediction in the Hardened Steel Ball-End Milling by Using the Artificial Neural Networks and Taguchi Method

Fabrication of semicircular micro-grooves on Ti6Al4V by through-mask scanning electrochemical machining

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