Rubber Injection Molding with Quality Recognition

Publikationen: Beitrag in FachzeitschriftArtikelForschung(peer-reviewed)

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Rubber Injection Molding with Quality Recognition. / Hutterer, Thomas; Berger-Weber, Gerald; Roman Christopher, Kerschbaumer et al.
in: Kunststoffe <München> / Kunststoffe international, Jahrgang 2021, Nr. 4, 04.2021, S. 6 - 9.

Publikationen: Beitrag in FachzeitschriftArtikelForschung(peer-reviewed)

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Author

Hutterer, Thomas ; Berger-Weber, Gerald ; Roman Christopher, Kerschbaumer et al. / Rubber Injection Molding with Quality Recognition. in: Kunststoffe <München> / Kunststoffe international. 2021 ; Jahrgang 2021, Nr. 4. S. 6 - 9.

Bibtex - Download

@article{dc52924e477b46b7b145bf92ee128ce5,
title = "Rubber Injection Molding with Quality Recognition",
abstract = "With the increasing digitalization of injection molding, new process parameters are coming under the spotlight.Engel, together with the Polymer Competence Center Leoben and Montan University Leoben, Austria, isusing machine-learning methods to explore the potential of mold breathing for quality assurance in rubberinjection molding. This research project was supported by the partner company SKF Sealing Solutions Austria.",
author = "Thomas Hutterer and Gerald Berger-Weber and {Roman Christopher}, Kerschbaumer and Walter Friesenbichler and Alexander Klutz and Thomas Leng and Karlheinz Mayr",
year = "2021",
month = apr,
language = "English",
volume = "2021",
pages = "6 -- 9",
journal = "Kunststoffe <M{\"u}nchen> / Kunststoffe international",
publisher = "Carl Hanser Verlag GmbH & Co. KG",
number = "4",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Rubber Injection Molding with Quality Recognition

AU - Hutterer, Thomas

AU - Berger-Weber, Gerald

AU - Roman Christopher, Kerschbaumer

AU - Friesenbichler, Walter

AU - Klutz, Alexander

AU - Leng, Thomas

AU - Mayr, Karlheinz

PY - 2021/4

Y1 - 2021/4

N2 - With the increasing digitalization of injection molding, new process parameters are coming under the spotlight.Engel, together with the Polymer Competence Center Leoben and Montan University Leoben, Austria, isusing machine-learning methods to explore the potential of mold breathing for quality assurance in rubberinjection molding. This research project was supported by the partner company SKF Sealing Solutions Austria.

AB - With the increasing digitalization of injection molding, new process parameters are coming under the spotlight.Engel, together with the Polymer Competence Center Leoben and Montan University Leoben, Austria, isusing machine-learning methods to explore the potential of mold breathing for quality assurance in rubberinjection molding. This research project was supported by the partner company SKF Sealing Solutions Austria.

UR - https://res.cloudinary.com/sternwald-systems/raw/upload/v1/hugoprd/ARTIKEL_ATTACH/00298EE6_070D8F011B65/1592997213b9b5364415b4c6c4d26ed00f65f4e3/Rubber%20Injection%20Molding%20with%20%20Quality%20Recognition%20-%20KUint%2004%202021.pdf

M3 - Article

VL - 2021

SP - 6

EP - 9

JO - Kunststoffe <München> / Kunststoffe international

JF - Kunststoffe <München> / Kunststoffe international

IS - 4

ER -