A Feature-Based Framework for Structuring Industrial Digital Twins

Thumbnail Image
Journal Title
Journal ISSN
Volume Title
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Degree programme
IEEE Access, Volume 8
Digital twin is a virtual entity that is linked to a real-world entity. Both the link and the virtual representation can be realized in several different ways. However, the ambiguous meanings associated with the term digital twin are causing unnecessary miscommunications as people have different interpretations of what can be accomplished with it. To provide clarity around the concept, we introduce a general approach to analyze and construct digital twins in various applications. We identify the common features of digital twins from earlier literature and propose an analysis method that compares digital twin instances based on these features. The method is used to verify the existence of the features and can be further enhanced. We formulate the observations to a feature-based digital twin framework (FDTF) to universally define and structure digital twins. The framework consists of three main principles: i) the idea that all digital twins consist of a definite set of features, ii) the features can be used to compare digital twin instances to each other, and iii) the features can be combined via a data link feature to construct future digital twins more efficiently. As key contributions, we found that the features can be identified in existing digital twin implementations and the feature combinations of the implementations are diverse. We suggest that the features should be leveraged to provide clarity and efficiency in digital twin discussion and implementation. We further propose a general procedure for building digital twins.
cyber-physical systems, Digital twin, enterprise systems, Industrial Internet of Things
Other note
Autiosalo , J , Vepsalainen , J , Viitala , R & Tammi , K 2020 , ' A Feature-Based Framework for Structuring Industrial Digital Twins ' , IEEE Access , vol. 8 , 8887161 , pp. 1193-1208 . https://doi.org/10.1109/ACCESS.2019.2950507