Tool condition and machined surface monitoring for micro-lens array fabrication in mechanical machining

The monitoring technology of machining process is very important to improve the productivity and reliability of products in the recent manufacturing field. There are still several attempts in order to apply the monitoring technology in machining condition. Because of signal processing and reliability problem, the direct monitoring is limited in small-scale parts machining. This paper represents an indirect monitoring technique for micro-lens machining process, which is performed with 200 mu m diameter ball end mill. The acoustic emission (AE) signals, which are acquired from workpiece jig, are found to have the parametric features in 400-600 kHz frequency domain as a different level for variable machining conditions. The root mean square value of the AE signal can be used effectively for tool condition and machined surface texture monitoring in micro-lens array machining. (C) 2008 Elsevier B.V. All rights reserved.