A Review, Focused on Data Transfer Standards, of the Uncertainty Representation in the Digital Twin Context

Abstract

In the context of the digital twin, the relevance and challenges of the uncertainty quantification are recognized. Data acquired in the physical domain are incorporated into a cyber-space to assist in predictive and decision-making processes. The acquisition of data in the physical domain involves the measurement of physical magnitudes. The digital as-built or as-manufactured model derives from measured or scanned data of a physical product. Thus, it is relevant to know how much the data are true. The uncertainty of a measured magnitude is a significant indicator of the data truthfulness. This work shows how the uncertainty is being modeled in standards related to product data representation and in an engineering data fusion context. The ongoing uncertainty modeling work in the Collaborative Research Center (SFB 805) at TU Darmstadt is presented as an example of a data fusion context.