论文标题
基于图的知识表示和模式挖掘支持现有制造系统的数字双胞胎的创建
A graph-based knowledge representation and pattern mining supporting the Digital Twin creation of existing manufacturing systems
论文作者
论文摘要
为现有制造系统（即所谓的棕地系统）创建数字双胞胎，这是一项具有挑战性的任务，因为关于棕地系统结构以及实现数字模型的努力所需的专家知识。已经提出了几种方法和方法，至少部分将有关棕地制造系统的信息数字化。数字双胞胎需要来自多个来源的链接信息。本文提出了一种基于图的方法，以合并异质来源的信息。此外，该方法提供了一种使用图结构分析自动识别模板的方法，以促进与所得数字双胞胎及其进一步增强的进一步工作。
The creation of a Digital Twin for existing manufacturing systems, so-called brownfield systems, is a challenging task due to the needed expert knowledge about the structure of brownfield systems and the effort to realize the digital models. Several approaches and methods have already been proposed that at least partially digitalize the information about a brownfield manufacturing system. A Digital Twin requires linked information from multiple sources. This paper presents a graph-based approach to merge information from heterogeneous sources. Furthermore, the approach provides a way to automatically identify templates using graph structure analysis to facilitate further work with the resulting Digital Twin and its further enhancement.
