Cranfield Online Research Data (CORD)
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Data: A Design Framework for Adaptive Digital Twins

posted on 2023-09-04, 08:26 authored by John ahmet ErkoyuncuJohn ahmet Erkoyuncu, Iñigo Fernández del amo blanco, Dedy Ariansyah, Dominik Bulka, Rok Vrabič, Rajkumar RoyRajkumar Roy

This paper develops a new DT design framework that uses ontologies to enable co-evolution with the CES by capturing data in terms of variety, velocity, and volume across the asset life-cycle. The framework has been tested successfully on a helicopter gearbox demonstrator and a mobile robotic system across their life cycles, illustrating DT adaptiveness without the data architecture needing to be modified. The data presented in this portal is related to the data that was generated in the validation process.


Digital Toolkit for optimisation of operators and technology in manufacturing partnerships (DigiTOP)

Engineering and Physical Sciences Research Council

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