Fabrication of microinducer by 5-axis control ultraprecision micromilling

Nakamoto, Keiichi; Ishida, Toru; Kitamura, Norikazu; Takeuchi, Yoshimi

doi:10.1016/j.cirp.2011.03.021

Cited by 15 publications

(6 citation statements)

References 5 publications

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“…Fanuc has applied this work to its NURBS interpolator [41] . Cheng et al [12] worked out the second order approximation for improved accuracy and applied it to their NURBS command generator [34] Farouki and Tsai [42] compared the accuracy of the Taylor′s expansion method with the PH curve arc length parametrization method. A quintic PH curve with strong curvature variation and uneven parameterization was used in the experiment.…”

Section: Recursive Taylor′s Expansionmentioning

confidence: 99%

Toolpath Interpolation and Smoothing for Computer Numerical Control Machining of Freeform Surfaces: A Review

Zhong

Luo

Chang

et al. 2019

Int. J. Autom. Comput.

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Driven by the ever increasing demand in function integration, more and more next generation high value-added products, such as head-up displays, solar concentrators and intra-ocular-lens, etc., are designed to possess freeform (i.e., non-rotational symmetric) surfaces. The toolpath, composed of high density of short linear and circular segments, is generally used in computer numerical control (CNC) systems to machine those products. However, the discontinuity between toolpath segments leads to high-frequency fluctuation of feedrate and acceleration, which will decrease the machining efficiency and product surface finish. Driven by the ever-increasing need for high-speed high-precision machining of those products, many novel toolpath interpolation and smoothing approaches have been proposed in both academia and industry, aiming to alleviate the issues caused by the conventional toolpath representation and interpolation methods. This paper provides a comprehensive review of the state-of-the-art toolpath interpolation and smoothing approaches with systematic classifications. The advantages and disadvantages of these approaches are discussed. Possible future research directions are also offered.

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Section: Recursive Taylor′s Expansionmentioning

confidence: 99%

Toolpath Interpolation and Smoothing for Computer Numerical Control Machining of Freeform Surfaces: A Review

Zhong

Luo

Chang

et al. 2019

Int. J. Autom. Comput.

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“…This is because the sharp edge of superhard diamond tool may deburr during mechanical machining. For example, a rotational single-crystal diamond tool of radius À0.2 mm was validly used to perform a CNC end milling of micro-inducer with the depth of cut of 20 mm and the spindle rotation of 35,000 rpm [8]. However, these approaches were only able to machine easy-cut metallic materials.…”

Section: Introductionmentioning

confidence: 99%

Dry electro-contact discharge mutual-wear truing of micro diamond wheel V-tip for precision micro-grinding

Xie

Luo

et al. 2012

International Journal of Machine Tools and Manufacture

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“…Furthermore, Dutterer et al investigated the suitable parameters for freeform milling of germanium and fabricated alvarez lens with the roughness of 9 nm Ra [7]. The authors also have developed a computer-aided manufacturing (CAM) system for creating a microinducer by five-axis control ultraprecision machining [8].…”

Section: Introductionmentioning

confidence: 99%

An Efficient Ultraprecision Machining System Automating Setting Operations of Roughly Machined Workpiece

Nakamoto

Takeuchi

2021

JMMP

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Ultraprecision machining is required in many advanced fields. To create precise parts for realizing their high performance, the whole machining process is usually conducted on the same ultraprecision machine tool to avoid setting errors by reducing setting operations. However, feed rate is relatively slow and machining efficiency is not so high compared to ordinary machine tools. Thus, the study aims to develop an efficient ultraprecision machining system including an industrial robot to avoid manual setting and to automate the setting operations. In this system, ultraprecision machining is conducted for the workpiece having a shape near the target shape, which is beforehand prepared by ordinary machine tools and is located on the machine table by means of an industrial robot. Since the setting errors of the roughly machined workpiece deteriorate machining accuracy, the differences from the ideal position and attitude are detected with a contact type of on-machine measurement device. Numerical control (NC) data is finally modified to compensate the identified workpiece setting errors to machine the target shape on an ultraprecision machine tool. From the experimental results, it is confirmed that the proposed system has the possibility to reduce time required in ultraprecision machining to create precise parts with high efficiency.

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Fabrication of microinducer by 5-axis control ultraprecision micromilling

Cited by 15 publications

References 5 publications

Toolpath Interpolation and Smoothing for Computer Numerical Control Machining of Freeform Surfaces: A Review

Toolpath Interpolation and Smoothing for Computer Numerical Control Machining of Freeform Surfaces: A Review

Dry electro-contact discharge mutual-wear truing of micro diamond wheel V-tip for precision micro-grinding

An Efficient Ultraprecision Machining System Automating Setting Operations of Roughly Machined Workpiece

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