汽车工业
相互依存
分析
计算机科学
制造工程
过程(计算)
产品(数学)
新产品开发
工程类
工业工程
数据科学
业务
数学
操作系统
航空航天工程
营销
法学
政治学
几何学
作者
Eduard Wagner,Bernd Keller,Peter Reimann,Christoph Gröger,Dieter Späth
出处
期刊:Procedia CIRP
[Elsevier]
日期:2022-01-01
卷期号:112: 442-447
被引量:2
标识
DOI:10.1016/j.procir.2022.09.034
摘要
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI