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Using geometric shape variations to create an inverse model for a sheet metal process

journal contribution
posted on 2003-01-01, 00:00 authored by Bernard RolfeBernard Rolfe, M Cardew-Hall, S Abdallah, G West
The output of the sheet metal forming process is subject to much variation. This paper develops a method to measure shape variation in channel forming and relate this back to the corresponding process parameter levels of the manufacturing set-up to create an inverse model. The shape variation in the channels is measured using a modified form of the point distribution model (also known as the active shape model). This means that channels can be represented by a weighting vector of minimal linear dimension that contains all the shape variation information from the average formed channel.

The inverse models were created using classifiers that related the weighting vectors to the process parameter levels for the blank holder force (BHF), die radii (DR) and tool gap (TG) of the parameters. Several classifiers were tested: linear, quadratic Gaussian and artificial neural networks. The quadratic Gaussian classifiers were the most accurate and the most consistent type of classifier over all the parameters.

History

Journal

Proceedings of the Institution of Mechanical Engineers. Part B, Journal of engineering manufacture

Volume

217

Issue

12

Pagination

1665 - 1675

Publisher

Mechanical Engineering Publications Ltd.

Location

London, England

ISSN

0954-4054

eISSN

2041-2975

Language

eng

Publication classification

C1 Refereed article in a scholarly journal