Digital twin is regarded as the virtual counterpart of physical entities, which can mirror the physical behavior and performance. Digital twin technology provides strong support for the achievement of cyber-physical system and intelligent manufacturing. Many investigations have been carried out for the digital twin of specific products. However, there are less researches on digital twin in the shop-floor domain, and there is a lack of model-driven digital twin comprehensive architecture. The modeling approach to the full lifecycle of digital twin is not considered enough. This paper proposes a meta-model-based shop-floor digital twin construction approach and a comprehensive architecture. A meta-model based on RAMI 4.0 is constructed, which provide a novel idea for the description of manufacturing resources and their status. The proposed shop-floor digital twin architecture consists of three key implementation elements: the meta-model construction, data modeling (including data interaction between cyber-physical spaces) and constructing different integration level models of shop-floor digital twin based on iteration feedback between the demands and models. The proposed approach is validated through a case study of the fischer learning factory 4.0.

数字孪生被视为物理实体的虚拟副本，可以反映物理行为和性能。数字孪生技术为信息物理系统和智能制造的实现提供了有力支撑。针对特定产品的数字孪生进行了许多调查。然而，车间领域对数字孪生的研究较少，缺乏模型驱动的数字孪生综合架构。对数字孪生全生命周期的建模方法考虑不够。本文提出了一种基于元模型的车间数字孪生构建方法和综合架构。构建了基于RAMI 4.0的元模型，为制造资源及其状态的描述提供了一种新思路。拟议的车间数字孪生架构由三个关键实施要素组成：元模型构建、数据建模（包括信息物理空间之间的数据交互）和基于迭代反馈构建车间数字孪生的不同集成级别模型需求和模型。所提出的方法通过慧鱼学习工厂 4.0 的案例研究得到验证。