Digital Twin-based Condition Monitoring with Distributed Data Mapping of OPC UA and ISO 10303 STEP StandardShow others and affiliations
2024 (English)In: Proceedings of the 4th Eclipse Security, AI, Architecture and Modelling Conference on Data Space (eSAAM 2024), Association for Computing Machinery , 2024, p. 57-65Conference paper, Published paper (Refereed)
Abstract [en]
A digital twin (DT), the digital counterpart of a physical entity, process, or system, is a pivotal innovation driving the manufacturing industry's digital transformation. DT plays a significant role in product lifecycle management (PLM) and product condition monitoring. However, the diversity of systems and processes involved poses challenges in DT and data management within PLM, particularly regarding efficiency, standardized data mapping, and latency.The paper presents a solution architecture to address these challenges and contribute towards an efficient and cost-effective product lifecycle management system. The architecture focuses on DT's data management and communication aspects, utilizing the edge-based, decentralized Eclipse Arrowhead Framework and EDMtruePLM (Enterprise Data Management True Product Lifecycle Management) for standardized data management and condition monitoring of products.Integrating the ISO 10303 STEP standard for data modeling and the Open Platform Communications Unified Architecture (OPC UA) standard for communication is emphasized, improving the contextual significance of the data and the system's interoperability. A use case implementation is presented, where a fischertechnik assembly line is monitored, capturing sensor data through the PLC's OPC UA server. The sensor data is then aligned with the STEP standard and stored in the EDMTruePLM database for monitoring.
Place, publisher, year, edition, pages
Association for Computing Machinery , 2024. p. 57-65
Keywords [en]
Digital Twin, OPC UA, ISO 10303 STEP, EDMtruePLM, Eclipse Arrowhead Framework
National Category
Computer Systems
Research subject
Cyber-Physical Systems
Identifiers
URN: urn:nbn:se:ltu:diva-110570DOI: 10.1145/3685651.3685653ISI: 001353672100009Scopus ID: 2-s2.0-85208805649OAI: oai:DiVA.org:ltu-110570DiVA, id: diva2:1908559
Conference
eSAAM 2024: 4th Eclipse Security, AI, Architecture and Modelling Conference on Data Space, Mainz Germany, October 22, 2024
Projects
Arrowhead Tools
Funder
Vinnova
Note
ISBN for host publication: 979-8-4007-0984-5;
Full text: CC BY license;
Funder: EU ECSEL (no:826452); Academy of Finland (no:352725);
2024-10-282024-10-282024-12-17Bibliographically approved