Inverse identification of process variations for thin steel sheet bending

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

1 Citation (Scopus)
33 Downloads (Pure)

Abstract

The stability of a metal forming production process is influenced by several sources of scatter such as variation of material and lubrication properties. Identification of the sources of variation is needed to optimize the process settings or to design a control strategy for the process. Many engineers point out sources of variation by experience, but in complex cases a computational identification algorithm may be used to investigate the process. When using parameter estimation in a control system, process forces can be used for the estimation. However, many parameters may influence the process forces. Therefore extensive models are needed to be able to identify the process parameters, including parameters such as tooling misalignment. In the current work, a thin steel flap bending process is studied. Measurements from an industrial press are used to identify the process parameters. A metamodel based inverse analysis procedure is used. The procedure is extended with proper orthogonal decomposition (POD) of the force curves to increase its convergence rate.
Original languageEnglish
Title of host publicationMaterial Forming ESAFORM 2015
PublisherTrans Tech Publications Ltd
Pages1363-1368
DOIs
Publication statusPublished - 15 Apr 2015
EventESAFORM 2015: 18th International ESAFORM Conference on Material Forming - Graz, Austria
Duration: 15 Apr 201517 Apr 2015
Conference number: 18

Publication series

Name
PublisherTrans Tech Publications
Volume651-653
ISSN (Print)1013-9826

Conference

ConferenceESAFORM 2015
Abbreviated titleESAFORM 2015
CountryAustria
CityGraz
Period15/04/1517/04/15

Fingerprint

Metal forming
Steel sheet
Parameter estimation
Lubrication
Decomposition
Control systems
Engineers
Steel

Keywords

  • IR-96306
  • METIS-310900

Cite this

Havinga, Gosse Tjipke ; van den Boogaard, Antonius H. / Inverse identification of process variations for thin steel sheet bending. Material Forming ESAFORM 2015. Trans Tech Publications Ltd, 2015. pp. 1363-1368
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title = "Inverse identification of process variations for thin steel sheet bending",
abstract = "The stability of a metal forming production process is influenced by several sources of scatter such as variation of material and lubrication properties. Identification of the sources of variation is needed to optimize the process settings or to design a control strategy for the process. Many engineers point out sources of variation by experience, but in complex cases a computational identification algorithm may be used to investigate the process. When using parameter estimation in a control system, process forces can be used for the estimation. However, many parameters may influence the process forces. Therefore extensive models are needed to be able to identify the process parameters, including parameters such as tooling misalignment. In the current work, a thin steel flap bending process is studied. Measurements from an industrial press are used to identify the process parameters. A metamodel based inverse analysis procedure is used. The procedure is extended with proper orthogonal decomposition (POD) of the force curves to increase its convergence rate.",
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Havinga, GT & van den Boogaard, AH 2015, Inverse identification of process variations for thin steel sheet bending. in Material Forming ESAFORM 2015. Trans Tech Publications Ltd, pp. 1363-1368, ESAFORM 2015, Graz, Austria, 15/04/15. https://doi.org/10.4028/www.scientific.net/KEM.651-653.1363

Inverse identification of process variations for thin steel sheet bending. / Havinga, Gosse Tjipke; van den Boogaard, Antonius H.

Material Forming ESAFORM 2015. Trans Tech Publications Ltd, 2015. p. 1363-1368.

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

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AB - The stability of a metal forming production process is influenced by several sources of scatter such as variation of material and lubrication properties. Identification of the sources of variation is needed to optimize the process settings or to design a control strategy for the process. Many engineers point out sources of variation by experience, but in complex cases a computational identification algorithm may be used to investigate the process. When using parameter estimation in a control system, process forces can be used for the estimation. However, many parameters may influence the process forces. Therefore extensive models are needed to be able to identify the process parameters, including parameters such as tooling misalignment. In the current work, a thin steel flap bending process is studied. Measurements from an industrial press are used to identify the process parameters. A metamodel based inverse analysis procedure is used. The procedure is extended with proper orthogonal decomposition (POD) of the force curves to increase its convergence rate.

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