Automatic Generation of a Simulation-based Digital Twin of an Industrial Process Plant

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Researchers

Research units

  • Luleå University of Technology

Abstract

A Digital Twin (DT) of a production plant is a digital replica of the plant’s physical assets which contains the structure and the dynamics of how the devices and process operate. Simulation-based DTs (SBDTs) are those based on online first principle simulation models. In these systems, model parameter estimation techniques keep an online plant simulator in the same state as the targeted device or process. As a result, non-measured information of the current state of the plant can be obtained from the model. SBDTs can be used for a number of important applications and they have various advantages compared to DTs based on data-driven models. However, wider industrial adoption of SBDTs is hindered by laborious development of their underlying first principle simulation model as well as by a lack of integrated lifecycle-wide implementation methods and simulation architectures. This paper focuses on applying previously presented methods for reducing implementation effort of SBDTs. Firstly, laborious simulation model development is tackled by applying an automatic model generation method. Secondly, an integrated implementation methodology of a lifecycle-wide online simulation architecture is followed for developing the SBDT. The results show a higher level of fidelity compares to previous publications. A SBDT of a laboratory-scale process is implemented to demonstrate the proposed method.

Details

Original languageEnglish
Title of host publicationProceedings of the 44th Annual Conference of the IEEE Industrial Electronics Society, IECON 2018
Publication statusPublished - 2018
MoE publication typeA4 Article in a conference publication
EventAnnual Conference of the IEEE Industrial Electronics Society - Washington, United States
Duration: 21 Oct 201823 Oct 2018
Conference number: 44

Publication series

NameProceedings of the Annual Conference of the IEEE Industrial Electronics Society
PublisherIEEE
ISSN (Print)1553-572X

Conference

ConferenceAnnual Conference of the IEEE Industrial Electronics Society
Abbreviated titleIECON
CountryUnited States
CityWashington
Period21/10/201823/10/2018

    Research areas

  • ditigal twin, dynamic process simulation, first principles model, simulation-based digital twin

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