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MASMICRO micro-/nano-materials processing, analysis, inspection and materials knowledge management
RISE - Research Institutes of Sweden, Materials and Production, IVF.
ANTER Ltd, Greece.
Upper Austrian Research GmbH, Austria.
Upper Austrian Research GmbH, Austria.
Show others and affiliations
2010 (English)In: The International Journal of Advanced Manufacturing Technology, ISSN 0268-3768, E-ISSN 1433-3015, Vol. 47, p. 963-971Article in journal (Refereed) Published
Abstract [en]

The main goals of the 'Material Innovation and Testing' within MASMICRO are the identification of the miniature/micro-materials which are formable, development of new materials for forming and machining, development of an integrated material-testing system and study of material properties for design/analysis applications. Examples of collaborative work and results are presented regarding the processing of functional electrospun polymer micro-/nano-fibre structures and the characterization of their interface properties with tribological testing. By means of optical coherence tomography, a non-destructive inspection approach for these micro-/nano-structured webs was developed and it is also documented in the paper. Further, an application example of artificial neural networks (ANNs) is given, concerning the modelling of nano-fibres material behaviour under tensile testing. It is shown how artificial intelligence approaches (knowledge-based systems-KBS and ANNs) can support, significantly, the representation and processing of materials' knowledge of both, symbolic type, in the case of KBS, and algorithmic type, in the case of ANNs, for the cases dealt within the MASMICRO. © Springer-Verlag London Limited 2009.

Place, publisher, year, edition, pages
2010. Vol. 47, p. 963-971
Keywords [en]
Artificial neural networks, Electrospun micro- and nano-structures, Friction and wear resistance, Knowledge-based systems, Optical coherencetomography
National Category
Materials Engineering
Identifiers
URN: urn:nbn:se:ri:diva-13370DOI: 10.1007/s00170-009-2126-4Scopus ID: 2-s2.0-84860629320OAI: oai:DiVA.org:ri-13370DiVA, id: diva2:973576
Available from: 2016-09-22 Created: 2016-09-22 Last updated: 2019-07-31Bibliographically approved

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