Laser Assisted Mechanical Micromachining of Hard-to-Machine Materials

by Singh, Ramesh K

Abstract (Summary)
There is growing demand for micro and meso scale devices with applications in the field of optics, semiconductor and bio-medical fields. In response to this demand, mechanical micro-cutting (e.g. micro-milling) is emerging as a viable alternative to lithography based micromachining techniques. Mechanical micromachining methods are capable of generating three-dimensional free-form surfaces to sub-micron level precision and micron level accuracies in a wide range of materials including common engineering alloys. However, certain factors limit the types of workpiece materials that can be processed using mechanical micromachining methods. For difficult-to-machine materials such as tool and die steels, limited machine-tool system stiffness and low tool flexural strength are major impediments to the use of mechanical micromachining methods. This thesis presents the design, fabrication and analysis of a novel Laser-assisted Mechanical Micromachining (LAMM) process that has the potential to overcome these limitations. The basic concept involves creating localized thermal softening of the hard material by focusing a solid-state continuous wave laser beam of diameter ranging from 70-120 microns directly in front of a miniature (300 microns-1 mm wide) cutting tool. By suitably controlling the laser power, spot size and speed, it is possible to produce a sufficiently large decrease in flow stress of the work material and, consequently, the cutting forces. This in turn will reduce machine/tool deflection and chances of catastrophic tool failure. The reduced machine/tool deflection yields improved accuracy in the machined feature. In order to use this process effectively, adequate thermal softening needs to be produced while keeping the heat affected zone in the machined surface to a minimum. This has been accomplished in the thesis via a detailed process characterization, modeling of process mechanics and optimization of process variables.
Bibliographical Information:

Advisor:Graham, Samuel; Johnson, Steven; Liang, Steven; Vengazhiyil, Roshan; Melkote, Shreyes

School:Georgia Institute of Technology

School Location:USA - Georgia

Source Type:Master's Thesis

Keywords:mechanical engineering


Date of Publication:11/14/2007

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