Modelling Production Workflows in Automotive Manufacturing

被引：3

作者：

Koenig, Simone ^{[1
,2
]}

Vogel-Heuser, Birgit ^{[1
]}

Fieg, Etienne ^{[1
]}

Hahn, Michael ^{[2
]}

Kopp, Oliver ^{[2
]}

机构：

[1] Tech Univ Munich, Chair Automat & Informat Syst, Garching, Germany

[2] Mercedes Benz AG, Sindelfingen, Germany

来源：

2021 IEEE 23RD CONFERENCE ON BUSINESS INFORMATICS, CBI 2021, VOL 2 | 2021年

关键词：

Automotive testing; manufacturing; production workflows; BPMN; DMN; guideline;

D O I：

10.1109/CBI52690.2021.10053

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

Interest in applications based on business process modelling in Industry 4.0 is on the rise, with corporations worldwide shifting from simply exploring the potential of process models to creating productive business cases with executable process models in cloud computing. However, despite numerous applications existing in process modelling, engineers are still lacking proper guidelines for modelling production workflows in automotive diagnostics. To address the issue, we evaluated Business Process Model and Notation (BPMN) and Decision Model and Notation (DMN) as modelling notations for production workflows in assembly lines. Based on the results, this paper presents an evaluated guideline for modelling production car diagnostics workflows in BPMN 2.0 and DMN 1.3 in the automotive industry. Our work contributes to science, as we provide an overview and analysis of business process modelling in automotive testing and diagnostics.

引用

页码：39 / 46

页数：8

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