An intelligent controller for improving the quality of deep drawn components

S. Hinduja; J. Atkinson; D. Lau; Ashraf Labib; P. Agirrezabal

doi:10.1016/S0007-8506(07)62933-3

An intelligent controller for improving the quality of deep drawn components

S. Hinduja, J. Atkinson, D. Lau, Ashraf Labib, P. Agirrezabal

Research output: Contribution to journal › Article › peer-review

Abstract

A prototype system, which detects wrinkling and tearing in sheet metal parts, has been developed. A spatial variation of the blankholding force (BHF) is achieved by hydraulic adjustment of the force in the BHF pins which are subdivided into groups. Neural networks predict the presence of wrinkles. Tears are predicted from the punch force signals using feature extraction techniques. A fuzzy logic controller (FLC) recommends changes to the BHF and lubrication to improve the quality of the next part. The results obtained when drawing the back panel of a washing machine are discussed.

Original language	English
Pages (from-to)	221-224
Number of pages	4
Journal	CIRP Annals - Manufacturing Technology
Volume	49
Issue number	1
DOIs	https://doi.org/10.1016/S0007-8506(07)62933-3
Publication status	Published - 2000

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title = "An intelligent controller for improving the quality of deep drawn components",

abstract = "A prototype system, which detects wrinkling and tearing in sheet metal parts, has been developed. A spatial variation of the blankholding force (BHF) is achieved by hydraulic adjustment of the force in the BHF pins which are subdivided into groups. Neural networks predict the presence of wrinkles. Tears are predicted from the punch force signals using feature extraction techniques. A fuzzy logic controller (FLC) recommends changes to the BHF and lubrication to improve the quality of the next part. The results obtained when drawing the back panel of a washing machine are discussed.",

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AU - Labib, Ashraf

AU - Agirrezabal, P.

PY - 2000

Y1 - 2000

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AB - A prototype system, which detects wrinkling and tearing in sheet metal parts, has been developed. A spatial variation of the blankholding force (BHF) is achieved by hydraulic adjustment of the force in the BHF pins which are subdivided into groups. Neural networks predict the presence of wrinkles. Tears are predicted from the punch force signals using feature extraction techniques. A fuzzy logic controller (FLC) recommends changes to the BHF and lubrication to improve the quality of the next part. The results obtained when drawing the back panel of a washing machine are discussed.

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DO - 10.1016/S0007-8506(07)62933-3

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An intelligent controller for improving the quality of deep drawn components

Abstract

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