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

Xu, Meng; Nakamoto, Keiichi; Takeuchi, Yoshimi

doi:10.3390/jmmp5010011

Cited by 2 publications

(2 citation statements)

References 14 publications

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“…In this study, a workpiece is scanned with a scanning type on-machine measurement device to detect the actual workpiece position and orientation (Xu et al, 2021). Three specific spheres located on a workpiece face as shown in Fig.…”

Section: Identification Of Workpiece Setting Errorsmentioning

confidence: 99%

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Automated workpiece setting operation by on-machine measurement for efficient ultraprecision cutting of micro-shapes

Riemer

Nakamoto

et al. 2022

JAMDSM

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Micro-shapes with sub-micron form accuracy are widely applied in many frontier fields such as optics, information technology, medical devices, and so on (Brinksmeier et al., 2012;Fang et al., 2013;Jiang et al., 2007). Ultraprecision cutting is a promising way to precisely create such micro-shapes, for the benefits of high flexibility, low cost, and low environmental burden (Zhang et al., 2019). Various methods for creating micro-shapes by ultraprecision cutting have been proposed. Yan et al. proposed a fabrication method of micro-pyramid arrays on NiP molds by using a sharpened single-crystalline diamond tool and achieved the depth range of the elements at the micron level (Yan et al., 2009). Additionally, Tan et al. developed a novel method to create blazed gratings with high curvature on freeform surfaces (Tan Abstract Ultraprecision cutting used for creating highly precise components and particularly micro-shapes requires ultraprecision machine tools. However, these machine tools are operated under restricted cutting conditions such as feed rate and depth of cut, resulting in low productivity. Therefore, this study deals with this problem by devising a novel ultraprecision cutting system with automation of the workpiece setting operation. In the devised system, the workpiece is roughly machined by an ordinary machine tool. After that, an industrial robot transfers the workpiece to an ultraprecision machine tool to complete the rest of the machining process. The proposed machining system overcomes two types of errors. The first is the shape error due to rough machining on the ordinary machine tool. It is practically difficult to create the expected shape exactly in rough machining, and therefore the shape error of the roughly machined workpiece is affecting the finish machining directly. The other is the setting errors due to the transfer of the workpiece to the ultraprecision machine tool from the ordinary machine tool. The differences from the ideal workpiece position and orientation are detected to identify the setting errors. Thus, the roughly machined workpiece is scanned to derive an error map by on-machine measurement. Additional tool paths are generated for semi-finish machining, and the error map helps to eliminate the form errors induced by rough machining. The NC program for finish machining is modified to compensate the identified workpiece setting errors. Finally, finish machining can be conducted on the roughly machined workpiece. Hence, the removal volume in finish machining on an ultraprecision machine tool is reduced, and the time required for the whole machining process is expected to be shorter. The experimental results confirm that the developed ultraprecision cutting system contributes to the automated workpiece setting operation to create micro-shapes with high accuracy.

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Section: Identification Of Workpiece Setting Errorsmentioning

confidence: 99%

“…However, workpiece setting errors have been ignored in this area. Thus, the differences from the ideal workpiece position and orientation are proposed to be detected with a scanning type on-machine measurement device in the previous study (Xu et al, 2021).…”

mentioning

confidence: 99%