Uncertainty of data and the digital twin: a review
by José Ríos; Georg Staudter; Moritz Weber; Reiner Anderl; Alain Bernard
International Journal of Product Lifecycle Management (IJPLM), Vol. 12, No. 4, 2020

Abstract: The digital twin (DT) incorporates measured data from the physical domain to create as-built or as-manufactured and as-operated product models. To comprehend some implications of creating a DT, this work provides a holistic review of the uncertainty of measured data and of the data flow context where they must be integrated. This work is based on the review of a selected group of publications and standards. The emphasis is on the as-built or as-manufactured 3D models and the showed uncertainty values refer to dimensional measurement data. The uncertainty ranges for different geometric data capture techniques are compare against the international dimensional tolerance grades. The alternative of predicting as-manufactured models is also discussed. Considering that parts must be manufactured within tolerances, the need to create as-manufactured 3D models, only for simulation purposes, is questioned. The uncertainty representation was also reviewed in three main groups of standards, and their location within the main data flow of the DT is illustrated.

Online publication date: Tue, 02-Feb-2021

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