Weightless neural network based monitoring of screw fastenings in automated assembly

L. D. Seneviratne, P. Visuwan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

Screw fastenings account for over a quarter of all assembly operations, and the intelligent automation of this process is of interest. This paper presents a new weightless neural network-based intelligent monitoring strategy for automated self-tapping screw insertions. A weightless neural network is designed and trained to monitor automated screw fastenings. The network is first trained and tested using computer simulations. The network is then tested on an experimental test setup, using both seen and unseen cases. Experimental results are presented to confirm the effectiveness of the approach. It is shown that the weightless neural network is relatively easy to train and is an efficient tool for monitoring automated screw fastenings.

Original languageBritish English
Title of host publicationICONIP 1999, 6th International Conference on Neural Information Processing - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages353-358
Number of pages6
ISBN (Electronic)0780358716, 9780780358713
DOIs
StatePublished - 1999
Event6th International Conference on Neural Information Processing, ICONIP 1999 - Perth, Australia
Duration: 16 Nov 199920 Nov 1999

Publication series

NameICONIP 1999, 6th International Conference on Neural Information Processing - Proceedings
Volume1

Conference

Conference6th International Conference on Neural Information Processing, ICONIP 1999
Country/TerritoryAustralia
CityPerth
Period16/11/9920/11/99

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