Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/29487
Title: Modeling and characterization of surface generation in fast tool servo machining of microlens arrays
Authors: Kong, LB
Cheung, CF 
Keywords: Fast tool servo
Microlens array
Precision metrology
Precision surface measurement
Ultra-precision machining
Issue Date: 2012
Publisher: Pergamon Press
Source: Computers and industrial engineering, 2012, v. 63, no. 4, p. 957-970 How to cite?
Journal: Computers and industrial engineering 
Abstract: A microlens array is composed of a series of microlens distributed in a regular pattern and has been used in a wide range of photonic products. Fast Tool Servo (FTS) machining is an enabling and efficient technology for fabricating high quality microlens arrays with submicrometer form accuracy and nanometric surface finish. Although there have been a number of studies on modeling and characterization of surface generation in Single Point Diamond Turning (SPTD), there is relatively little research on the modeling and characterization of surface generation in FTS machining of microlens arrays, which is radically different from SPTD and has additional process parameters. This paper therefore establishes a theoretical model for the prediction of surface generation in FTS machining of microlens arrays based on the cutting mechanism of FTS, cutting tool geometry, machining parameters, and the workpiece surface contour. A surface matching based method has been developed to characterize the surface quality of the microlens array as a whole instead of a single lens evaluation. A series of cutting experiments have been conducted, the actual results of which were found to largely agree with the predicted results. The successful development of the deterministic models and methods not only make the surface generation in FTS machining of microlens array more predictable, but also allow a better evaluation of the surface quality of the machined microlens array. It also helps to minimize or eliminate the need for conducting trial-and-error cutting experiments to optimize the machining process.
URI: http://hdl.handle.net/10397/29487
ISSN: 0360-8352
EISSN: 1879-0550
DOI: 10.1016/j.cie.2012.06.007
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