迈向数字模型/影子/双工作流和架构家族

Randy Paredis, C. Gomes, H. Vangheluwe
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引用次数: 3

摘要

数字孪生(DTs)可用于优化、分析和适应复杂的工程系统,特别是在这些系统已经部署之后。DTs充分利用了历史知识和来自传感器的流数据。在文献中已经给出了许多(不同的)定义和描述。在术语上没有达成一致,也没有对工作流和体系结构的全面描述。遵循多范式建模原则,本文建议明确地建模构建和使用dt及其体系结构的工作流。我们将可变性(也称为产品族)建模的概念应用到DT工作流和体系结构中。这允许以一种原则性的、可重复的和部分自动化的方式对不同的DT变体进行解构/重建。为了说明我们的想法,我们讨论了两个小的用例:一个随行机器人(代表自动引导车辆)和一个培养箱(代表工业对流炉)。用例关注工业环境中的重要系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards a Family of Digital Model/Shadow/Twin Workflows and Architectures
: Digital Twins (DTs) can be used for optimization, analysis and adaptation of complex engineered systems, in particular after these systems have been deployed. DTs make full use of both historical knowledge and of streaming data from sensors. DTs have been given numerous (distinct) definitions and descriptions in the literature. There is no consensus on terminology, nor a comprehensive description of workflows nor architectures. Following Multi-Paradigm Modelling principles, this paper proposes to explicitly model construction and use workflows of DTs as well as their architectures. We apply the concepts of variability (also known as product family) modeling, in particular to DT workflow and architecture. This allows for the de-/re-construction of the different DT variants in a principled, reproducible and partially automatable manner. To illustrate our ideas, two small use cases are discussed: a line-following robot (representative for an Automated Guided Vehicle) and an incubator (representative for an Industrial Convection Oven). The use cases focus on important systems in an industrial context.
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