Federated composite manufacturing process simulation using digital twins

Authors: de Vrieze, P.T., Arshad, R. and Xu, L.

Journal: International Journal of Simulation and Process Modelling

Publisher: Inderscience

eISSN: 1740-2131

ISSN: 1740-2123

Abstract:

Digital twins play a key role in the operation and management of smart factories. In some cases, an entire production line can be seen as a (composite) digital twin. The production line is often composed of multiple components and corresponding digital twins with their own (simulation) models. In this paper, we propose a federated simulation model that allows the simulation of such a composition to be built from independent digital twins of the components. We provide a formal model as the basis for the approach. The federated simulation provides a building block towards context-aware, autonomous, and adaptive simulation blocks for future factories. The solution is evaluated using proof-of-concept implementations in Python and Kotlin.

https://eprints.bournemouth.ac.uk/40328/

https://www.inderscience.com/jhome.php?jcode=ijspm

Source: Manual

Federated composite manufacturing process simulation using digital twins

Authors: de Vrieze, P.T., Arshad, R. and Xu, L.

Journal: International Journal of Simulation and Process Modelling

Publisher: Inderscience

ISSN: 1740-2123

Abstract:

Digital twins play a key role in the operation and management of smart factories. In some cases, an entire production line can be seen as a (composite) digital twin. The production line is often composed of multiple components and corresponding digital twins with their own (simulation) models. In this paper, we propose a federated simulation model that allows the simulation of such a composition to be built from independent digital twins of the components. We provide a formal model as the basis for the approach. The federated simulation provides a building block towards context-aware, autonomous, and adaptive simulation blocks for future factories. The solution is evaluated using proof-of-concept implementations in Python and Kotlin.

https://eprints.bournemouth.ac.uk/40328/

https://www.inderscience.com/jhome.php?jcode=ijspm

Source: BURO EPrints

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