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IJAT Vol.13 No.2 pp. 185-190
doi: 10.20965/ijat.2019.p0185
(2019)

Paper:

Machining of Smooth Optical Surfaces by Ultraprecision Milling with Compensated Feeding Mechanisms

Hideo Takino*,† and Yoshimi Takeuchi**

*Chiba Institute of Technology
2-17-1 Tsudanuma, Narashino, Chiba 275-0016, Japan

Corresponding author

**Chubu University, Kasugai, Japan

Received:
August 17, 2018
Accepted:
January 14, 2019
Published:
March 5, 2019
Keywords:
milling, ultraprecision, waviness, surface, diamond cutting
Abstract

Waviness tends to be generated on cut surfaces even when an ultraprecision milling machine with a single-crystal diamond tool is used. The present study deals with the reduction of waviness by controlling the feeding mechanisms of the milling machine. A machining experiment on a spherical surface of a mirror element in a mirror array showed that the machined surface exhibited periodic waviness with a height of 30 nm and a wavelength of 300 μm. To investigate the reason for such waviness, a slope was machined under simultaneous multiaxis motion control of the feeding mechanisms of the milling machine. This proved that the interpolation errors of the encoders used in the milling machine produce the waviness on the machined surface when machining is carried out under simultaneous multiaxis motion control. To reduce such interpolation errors, the positioning accuracy of the machine stages was measured using a laser interferometer. On the basis of the measured results, the feeding mechanisms were compensated such that the positioning errors including the interpolation errors were corrected. Using the machine with the compensated feeding system, a mirror element was shaped. Consequently, waviness was reduced and the surface smoothness was less than 10 nm, demonstrating that such compensation can produce superior optical surfaces.

Cite this article as:
H. Takino and Y. Takeuchi, “Machining of Smooth Optical Surfaces by Ultraprecision Milling with Compensated Feeding Mechanisms,” Int. J. Automation Technol., Vol.13 No.2, pp. 185-190, 2019.
Data files:
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