Error prognosis in automobile assembly: Use of a supervised learning algorithm for vehicle and station-related error prognosis Fehlerprognose in der Automobilmontage: Einsatz eines überwachten Lernalgorithmus zur fahrzeug-und stations-bezogenen Fehlerprognose
Huber T, Winkler H (2022)
Publication Type: Journal article
Publication year: 2022
Journal
Book Volume: 117
Pages Range: 192-199
Journal Issue: 4
Abstract
Prognosis of Defects in Automobile Assembly – Use of a Supervised Learning Algorithm for Vehicle and Prognosis of Station-related Defects.Automotive assembly is currently characterized by product variance and the human factor, so that despite numerous pre-ventive tools, this is not completely free of de-fects. To predict these defects, a classification model from the field of supervised machine learning was trained and validated over a period of three months. During this period, around 60 % of the relevant defects were cor-rectly predicted.
Involved external institutions
Austria (AT)How to cite
APA:
Huber, T., & Winkler, H. (2022). Error prognosis in automobile assembly: Use of a supervised learning algorithm for vehicle and station-related error prognosis Fehlerprognose in der Automobilmontage: Einsatz eines überwachten Lernalgorithmus zur fahrzeug-und stations-bezogenen Fehlerprognose. Zeitschrift Kunststofftechnik, 117(4), 192-199. https://dx.doi.org/10.1515/zwf-2022-1042
MLA:
Huber, Tobias, and Herwig Winkler. "Error prognosis in automobile assembly: Use of a supervised learning algorithm for vehicle and station-related error prognosis Fehlerprognose in der Automobilmontage: Einsatz eines überwachten Lernalgorithmus zur fahrzeug-und stations-bezogenen Fehlerprognose." Zeitschrift Kunststofftechnik 117.4 (2022): 192-199.
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