loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Digital Twin-enabled Application Architecture for the Process Industry

Topics: Cognitive Cyber-Physical Systems and Applications; Concrete Realization of Artificial Intelligence based Systems for Smart Production; Data Collection and Big-Data Management Systems and Strategies: Needs, Prospects and Concrete Realizations; Ontology and Knowledge Extraction for Smart Production and Manufacturing

Authors: Christoph Nölle 1 ; Asier Arteaga 2 ; Joseba Egia 3 ; Antonio Salis 4 ; Gabriele De Luca 5 and Norbert Holzknecht 1

Affiliations: 1 VDEh-Betriebsforschungsinstitut (BFI), Sohnstraße 69, 40237 Düsseldorf, Germany ; 2 Sidenor I+D, Barrio Urgate, 48970 Basauri, Spain ; 3 Mondragón Sistemas, S.COOP., Ama Kandida Etorbidea 21, 20140 Andoain, Spain ; 4 Engineering Ingegneria Informatica S.p.A., Loc. Sa Illetta, SS195 km 2,3, I-09123 Cagliari, Italy ; 5 Engineering Ingegneria Informatica S.p.A. Via Monteroni s.n., C/O Edificio Dhitech, Ecotekne, I-73100, Lecce, Italy

Keyword(s): Digital Twin, Process Industry, Steel, Ontology, Cognitive Solution, Open Source.

Abstract: We develop a software platform architecture for the integration of heterogeneous software applications in the process industries, ranging from physical simulation models to data-driven AI applications and visualizations. Digital twins play a key role in this architecture, providing harmonised interfaces to a diverse set of data sources, based on a domain-specific data model rooted in standard ontologies. We investigate the applicability of existing standards and open-source software, demonstrating on the one hand their immense potential for software-based innovations in the process industries, but also highlighting some shortcomings and the need for further developments. Finally, a concrete implementation and data model for the production of steel long products is presented.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.135.194.138

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Nölle, C.; Arteaga, A.; Egia, J.; Salis, A.; De Luca, G. and Holzknecht, N. (2022). Digital Twin-enabled Application Architecture for the Process Industry. In Proceedings of the 3rd International Conference on Innovative Intelligent Industrial Production and Logistics - ETCIIM; ISBN 978-989-758-612-5; ISSN 2184-9285, SciTePress, pages 255-266. DOI: 10.5220/0011561800003329

@conference{etciim22,
author={Christoph Nölle. and Asier Arteaga. and Joseba Egia. and Antonio Salis. and Gabriele {De Luca}. and Norbert Holzknecht.},
title={Digital Twin-enabled Application Architecture for the Process Industry},
booktitle={Proceedings of the 3rd International Conference on Innovative Intelligent Industrial Production and Logistics - ETCIIM},
year={2022},
pages={255-266},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011561800003329},
isbn={978-989-758-612-5},
issn={2184-9285},
}

TY - CONF

JO - Proceedings of the 3rd International Conference on Innovative Intelligent Industrial Production and Logistics - ETCIIM
TI - Digital Twin-enabled Application Architecture for the Process Industry
SN - 978-989-758-612-5
IS - 2184-9285
AU - Nölle, C.
AU - Arteaga, A.
AU - Egia, J.
AU - Salis, A.
AU - De Luca, G.
AU - Holzknecht, N.
PY - 2022
SP - 255
EP - 266
DO - 10.5220/0011561800003329
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic