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Proceedings Paper

Laser material micro-processing of shape memory alloys
Author(s): M. Fargas; A. von Busse; J. Bunte
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Paper Abstract

Due to their precise focusing properties and the possibility of an excellent non-tactile energy coupling, lasers represent a suitable machining process for miniaturised components of shape memory alloys (SMAs) in micro-system and biomedical technology. SMAs find increasing application in these fields because of their special properties such as super-elasticity and shape memory effect. Current research is concentrated on the development of suitable and economic process strategies for machining micro-components and -actuators using ultra-short-pulse lasers. The application of this laser type enables the realisation of miniaturised components made of SMAs without damaging the grain structure and therefore maintaining the shape memory effect. The processed miniaturised components are characterised with respect to the achieved geometrical resolution, the surface quality of the processed areas and their mechanical functionality. For real production, a reduction of the processing time is necessary. Therefore, different process strategies consisting in different numbers of process cycles (simultaneous material removal and smoothing, material removal and subsequent smoothing) are investigated machining NiTi-components. In this paper, results of the laser based method regarding processing time and surface quality will be presented. In addition, the application of these strategies for the realisation of exemplary actuator or component geometries (e.g. for minimal invasive surgery) will be demonstrated.

Paper Details

Date Published: 1 July 2005
PDF: 9 pages
Proc. SPIE 5836, Smart Sensors, Actuators, and MEMS II, (1 July 2005); doi: 10.1117/12.608695
Show Author Affiliations
M. Fargas, Laser Zentrum Hannover e.V. (Germany)
A. von Busse, Laser Zentrum Hannover e.V. (Germany)
J. Bunte, Laser Zentrum Hannover e.V. (Germany)

Published in SPIE Proceedings Vol. 5836:
Smart Sensors, Actuators, and MEMS II
Carles Cane; Jung-Chih Chiao; Fernando Vidal Verdu, Editor(s)

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