IJAT Vol.5 No.1 pp. 21-29
doi: 10.20965/ijat.2011.p0021


A System Development Approach for Electrolytic In-Process Dressing (ELID) Grinding

Tanveer Saleh* and Mustafizur Rahman**

*Research Chair for Advanced Manufacturing Technology, King Saud University, Riyadh 11421, Saudi Arabia

**Department of Mechanical Engineering, National University of Singapore, Singapore 119260

September 8, 2010
December 11, 2010
January 5, 2011
ELID grinding, grinding wheel monitoring, wheel truing

This study aims to present the development and performance evaluation of an ultra-precision ELID grinding machine. The machine is a 3-axis machine, including three conventional linear axes (X, Y, and Z). On top, another rotational axis has been included to assist aspheric/spherical lens grinding. In order to introduce intelligence to the machine, several on-machine measuring systems have been developed and incorporated. In ELID grinding, pulsed DC voltage is applied to the metal-bonded diamond wheels to ensure the constant protrusion of sharp cutting grit throughout the grinding cycle. The peak dressing voltage is kept constant irrespective of the wheel sharpness in conventional ELID grinding, which may lead to over dressing of the grinding wheel. The grinding force ratio, also known as K value, is an indicator of grit sharpness. In this study, a new approach to wheel dressing is proposed: the peak dressing voltage is varied according to the change in the K value during grinding. In conventional ELID grinding, the duty ratio of the dressing power supply is kept constant throughout the grinding cycle. However, this method does not achieve grinding wheel truing, which is very important to maintaining the stability of the grinding. This research work proposes a novel approach to wheel truing by controlling the dressing voltage duty ratio for ELID grinding.

Cite this article as:
T. Saleh and M. Rahman, “A System Development Approach for Electrolytic In-Process Dressing (ELID) Grinding,” Int. J. Automation Technol., Vol.5, No.1, pp. 21-29, 2011.
Data files:
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Last updated on Nov. 08, 2019