Development and Validation of Digital Twin Behavioural Model for Virtual Commissioning of Cyber-Physical System
Modern manufacturing systems are influenced by the growing complexity of mechatronics, control systems, IIoT, and communication technologies integrated into cyber-physical systems. These systems demand flexibility, modularity, and rapid project execution, making digital tools critical for their design. Virtual commissioning, based on digital twins, enables the testing and validation of control systems and designs in virtual environments, reducing risks and accelerating time-to-market. This research explores the development of digital twin models to bridge the gap between simulation and real-world validation. The models identify design flaws, validate the PLC control code, and ensure interoperability across software platforms. A case study involving a modular Festo manufacturing system modelled in Tecnomatix Process Simulate demonstrates the ability of digital twins to detect inefficiencies, such as collision risks, and to validate automation systems virtually. This study highlights the advantages of virtual commissioning for optimizing manufacturing systems. Communication testing showed compatibility across platforms but revealed limitations with certain data types due to software constraints. This research provides practical insights into creating robust digital twin models, improving the flexibility, efficiency, and quality of manufacturing system design. It also offers recommendations to address current challenges in interoperability and system performance.
Authors
- Roman Zelník (ORCID: https://orcid.org/0009-0000-3053-8037)
- Eduard Nemlaha (ORCID: https://orcid.org/0000-0001-8941-3677)
- Richard Skýpala (ORCID: https://orcid.org/0000-0003-4018-8899)
- Tibor Horák (ORCID: https://orcid.org/0000-0002-1620-6199)
- Roman Ružarovský (ORCID: https://orcid.org/0000-0002-9465-4544)
- Michal Kopček (ORCID: https://orcid.org/0000-0001-8466-598X)
- Ján Šido (ORCID: https://orcid.org/0009-0009-9277-6511)
- Martin Csekei (ORCID: https://orcid.org/0009-0000-6399-5971)
Institutions
- Slovak University of Technology in Bratislava (SK)
Publication Details
- Journal
- Applied Sciences
- Published
- 2025-03-06
- DOI
- https://doi.org/10.3390/app15052859
- Citations
- 7
- Primary Topic
- Digital Transformation in Industry
- Type
- article
- Field-Weighted Citation Impact
- 8.70
Funders
- Agentúra na Podporu Výskumu a Vývoja