The Performance of ARTMAP in Pattern Recognition for a Flexible Vibratory Bowl Feeder System

The Performance of ARTMAP in Pattern Recognition for a Flexible Vibratory Bowl Feeder System

Neural networks have been shown to exhibit good pattern recognition capability. By incorporating this capability using an ARTMAP neural network within a flexible vibratory bowl feeder system, the feeder can orientate parts of a part family with short changeover time from one part to the next; this i...

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Bibliographische Detailangaben
Hauptverfasser: Siang Kok Sim, Chua, P.S.K., Meng Leong Tay, Gao Yun
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Batch production systems
Cameras
Group technology
Image sensors
Mass production
Neural networks
Pattern recognition
Production engineering
Sampling methods
Testing
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Beschreibung
Zusammenfassung:Neural networks have been shown to exhibit good pattern recognition capability. By incorporating this capability using an ARTMAP neural network within a flexible vibratory bowl feeder system, the feeder can orientate parts of a part family with short changeover time from one part to the next; this is highly sought after in batch production. This paper investigates the influence of a set of parameters that characterised ARTMAP and the sampling rate on the pattern recognition capability of the system. The results show that the optimal performance can be achieved by selecting appropriate values for these parameters.
DOI:10.1109/ICCA.2003.1595017