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Formulating polyurethanes using case based reasoning
journal contribution
posted on 2009-02-13, 14:37 authored by Diana M. Segura-Velandia, Richard HeathRichard Heath, Andrew WestAndrew WestA large amount of historical knowledge exists in the form of ‘formulation experiences’ across
polyurethane manufacturing companies. This knowledge is difficult to formalise, share and use in
new formulations. As a part of an effort to support the polyurethane formulating problem, the use
of case based reasoning (CBR) has been assessed. Two basic problems in the development of
the proposed hybrid tool that uses past formulations to solve new problems are studied. The
problems investigated are related to the retrieval of former formulations that are similar to a new
problem description by the CBR module, and the adaptation of the retrieved case to meet the
problem constraints using an artificial neural network (ANN). Results indicated that the CBR-ANN
system is useful for reusing historical data. Although the obtained ANN is unable to generalise
well when presented with more data independent from the original data set, results proved that
real formulation data can be used as a ‘knowledge repository’ that can guide CBR adaptation
without human expert intervention.
History
School
- Aeronautical, Automotive, Chemical and Materials Engineering
Department
- Materials
Citation
SEGURA-VELANDIA, D.M., HEATH, R.J. and WEST, A.A., 2007. Formulating polyurethanes using case based reasoning. Plastics, Rubber and Composites, 36 (6), pp.241-247Publisher
© ManeyVersion
- VoR (Version of Record)
Publication date
2007Notes
This article was published in the journal, Plastics, Rubber and Composites [© Maney Publishing] and is available at: http://www.maney.co.uk/search?fwaction=show&fwid=199ISSN
1465-8011Language
- en