Meta-model-based shop-floor digital twin architecture, modeling and application

Abstract

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.