论文标题
棕地植物的数字双胞胎的自动数据驱动创建
Automated data-driven creation of the Digital Twin of a brownfield plant
论文作者
论文摘要
现有制造系统的重新配置的成功（所谓的棕地系统）在很大程度上取决于对系统的知识。可以通过提供此知识的系统的数字双元来计划，支持和简化重新配置。但是，这些工厂通常缺少数字模型作为数字双胞胎的基础。本文介绍了一种数据驱动的方法，以获取有关棕地系统的知识，以创建数字双胞胎及其关系的数字模型。最后，概念证明表明，作为数据源的过程数据和位置数据可以交付数字双胞胎模型之间的关系。
The success of the reconfiguration of existing manufacturing systems, so called brownfield systems, heavily relies on the knowledge about the system. Reconfiguration can be planned, supported and simplified with the Digital Twin of the system providing this knowledge. However, digital models as the basis of a Digital Twin are usually missing for these plants. This article presents a data-driven approach to gain knowledge about a brownfield system to create the digital models of a Digital Twin and their relations. Finally, a proof of concept shows that process data and position data as data sources deliver the relations between the models of the Digital Twin.
