Interactive Feature Extraction From Multivariate Production Data

S Rezvani, G Prasad, J Muir, K McCraken

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

As part of a research programme between the University of Ulsterand a polymeric manufacturing company, the interrelationships andperformance attributes of polymeric components used in adhesivesmanufactured for medical packaging are being studied. To understand theinteractions between the parameters, to select the optimal manufacturingprocesses and to improve economic factors within this investigation, a series ofmultidimensional data processing and visualisation methods such as PrincipalComponent Mapping (PCM), Curvilinear Component Mapping (CCM) andSammon Mapping have been examined. As a novel approach to multivariatedata visualisation and analysis, these techniques were employed in such a waythat interactive multi-layer maps could be generated. Each layer within thisfeature extraction technique corresponds to a specific attribute andcharacteristic of the dataset. Activation and superimpositions of individuallayers allow studying manufacturing attributes, parameter interactions andproduct formulations,
Original languageEnglish
Title of host publicationUnknown Host Publication
Publisher3rd International Workshop on Pattern Recognition in Information Systems, PRIS 2003
Pages122-133
Number of pages12
Publication statusPublished - Apr 2003
Event3rd International Workshop on Pattern Recognition in Information Systems, PRIS 2003 -
Duration: 1 Apr 2003 → …

Conference

Conference3rd International Workshop on Pattern Recognition in Information Systems, PRIS 2003
Period1/04/03 → …

Fingerprint Dive into the research topics of 'Interactive Feature Extraction From Multivariate Production Data'. Together they form a unique fingerprint.

  • Cite this

    Rezvani, S., Prasad, G., Muir, J., & McCraken, K. (2003). Interactive Feature Extraction From Multivariate Production Data. In Unknown Host Publication (pp. 122-133). 3rd International Workshop on Pattern Recognition in Information Systems, PRIS 2003. http://uir.ulster.ac.uk/18497/1/Prasad03_c_8.pdf