Advanced analytics for evaluating critical joining technologies in automotive body structures and body shops

The product development process within the automotive industry is subject to changing demands due to internal and external influences. These influences and adjustments especially affect the car body and its inherent joining technology, as critical stages of variant creation. However, current literat...

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Bibliographic Details
Published inProcedia CIRP Vol. 112; pp. 442 - 447
Main Authors Wagner, Eduard, Keller, Bernd, Reimann, Peter, Gröger, Christoph, Spath, Dieter
Format Journal Article
LanguageEnglish
Published Elsevier B.V 2022
Subjects
advanced analytics
analytics
biw
Body shop
data mining
data science
kdd
machine learning
substructure
analytics
biw
advanced analytics
data science
data mining
kdd
machine learning
Body shop
substructure
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Summary:The product development process within the automotive industry is subject to changing demands due to internal and external influences. These influences and adjustments especially affect the car body and its inherent joining technology, as critical stages of variant creation. However, current literature does not offer a suitable analytical method to identify and assess these critical influences. We propose an advanced analytics approach that combines data mining and machine learning techniques within the car body substructure. The evaluation within the Mercedes-Benz AG shows that our approach facilitates a quantitative assessment of unknown interdependencies between car body modules and corresponding joining techniques.
ISSN:2212-8271
2212-8271
DOI:10.1016/j.procir.2022.09.034