Statistical Monitoring of Injection Moulds

Authors:
Xavier Berjaga;Joaquim Melendez;Alvaro Pallares
Affiliations:
Institut d'Informàtica i Aplicacions, Universitat de Girona, Av. Lluís Santalo. s/n, 17071, Girona, Spain and Plastiasite S.A., Parc Tecnologic Valles, 08290, Barcelona, Spain;Institut d'Informàtica i Aplicacions, Universitat de Girona, Av. Lluís Santalo. s/n, 17071, Girona, Spain;Plastiasite S.A., Parc Tecnologic Valles, 08290, Barcelona, Spain
Venue:
Proceedings of the 2008 conference on Artificial Intelligence Research and Development: Proceedings of the 11th International Conference of the Catalan Association for Artificial Intelligence
Year:
2008

Citing 3
Cited 0

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Abstract

In this paper a statistical based methodology to work over the principal component space on injection moulds is presented. The Multiway Principal Component Analysis is applied as a dimensionality reduction step, and fault detection assessment. This methodology allowed to analyse the behaviour of injections with the information directly received from sensors, what ended in a better process understanding. Results concluded that with a low number of variables (some principal components and two control statistics) is enough to detect abnormalities (too short injections, injections with low variability, etc.).