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Photopolymer based customized additive manufacturing technologies

Objective

Lithography based additive manufacturing technologies (AMT) are capable of fabricating parts with excellent surface quality, good feature resolution and precision. With recent developments in the field of ultra-short-pulse lasers and light engines based on light emitting diodes, robust and economical light sources have become available. This project aims at developing integrated lithography-based additive manufacturing systems which will, for the first time, facilitate the processing of photopolymer-based materials for the factory of the future. The focus of the project is to unite industrial know-how in the field of supply chain management, software development, photopolymers and ceramics, high-performance light-sources, system integration and end-users in order to provide a fully integrated process chain at the end of the project. The consortium will rely on two core-technologies: (1) Digital light processing (DLP) based processes will be used to process ceramic-filled photopolymers, leading to fully dense ceramic parts at the end of the process chain. (2) Two photon polymerization (2PP) will be used to fabricate high-resolution structures with features in the range of 100-200nm. Both processes will be tuned to reduce system cost, and significantly increase throughput and reliability at the same time. Goal is to deliver 'first-time-right' strategies for the involved end-users. This necessitates the development of supply chains with integrated quality sensors. Targeted applications include thread guides for textile machinery, ceramic moulds for the fabrication of high-performance turbine blades and microstructures for computer tomography equipment.

Call for proposal

FP7-2010-NMP-ICT-FoF
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Coordinator

TECHNISCHE UNIVERSITAET WIEN
EU contribution
€ 667 125,00
Address
KARLSPLATZ 13
1040 Wien
Austria

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Region
Ostösterreich Wien Wien
Activity type
Higher or Secondary Education Establishments
Administrative Contact
Jürgen Stampfl (Prof.)
Links
Total cost
No data

Participants (6)