NDLI: Modelling the enamelled wire manufacturing process to improve on-line quality control

Content Provider	IEEE Xplore Digital Library
Author	Mort, N. Bridges, L.W.
Copyright Year	1999
Description	Author affiliation: Dept. of Autom. Control & Syst. Eng., Sheffield Univ., UK (Mort, N.)
Abstract	This paper examines the potential for using empirical models derived from real plant data for online quality control for an enamelled wire production process. Existing procedures are based around a well-established offline technique known as Tangent Delta. Using data recorded from normal production operations, models representing parameter input/output relationships are fast developed using standard linear regression. The linear models do not capture the behaviour of the process sufficiently well so other methods based on nonlinear and fuzzy methods and artificial neural networks are developed. The ability of each of these methods to capture the process characteristics are compared using test set data. The results indicate that the nonlinear models derived using the group method of data handling (GMDH) approach offer considerable promise for online quality control in this industrial application.
Starting Page	4097
Ending Page	4100
File Size	354339
Page Count	4
File Format	PDF
ISBN	0780349903
ISSN	07431619
DOI	10.1109/ACC.1999.786314
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1999-06-02
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	American Automatic Control Council(AACC)
Subject Keyword	Wire Manufacturing processes Quality control Production Standards development Linear regression Fuzzy neural networks Artificial neural networks Testing Data handling
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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