The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
Design, modelling, simulation and integration of cyber physical systems: Methods and applications
Open accessAbstract
Presentation of a systematic classification of systems and new CPS paradigms.Analyses of literature conducted across a range of different perspectives.A systematic review of CPS-design literature was carried out, with an emphasis on the design, modelling, simulation and integration of CPS.An architectural and behavioural paradigm for CPS.Compilation of different viewpoints referring to applications at different levels of granularity. The main drivers for the development and evolution of Cyber Physical Systems (CPS) are the reduction of development costs and time along with the enhancement of the designed products. The aim of this survey paper is to provide an overview of different types of system and the associated transition process from mechatronics to CPS and cloud-based (IoT) systems. It will further consider the requirement that methodologies for CPS-design should be part of a multi-disciplinary development process within which designers should focus not only on the separate physical and computational components, but also on their integration and interaction. Challenges related to CPS-design are therefore considered in the paper from the perspectives of the physical processes, computation and integration respectively. Illustrative case studies are selected from different system levels starting with the description of the overlaying concept of Cyber Physical Production Systems (CPPSs). The analysis and evaluation of the specific properties of a sub-system using a condition monitoring system, important for the maintenance purposes, is then given for a wind turbine.
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Cited by
González, I., Calderón, A. J., Figueiredo, J., & Sousa, J. M. C. (2019) · Electronics · doi:10.3390/electronics8050510 · Cited by 103
Automatic assembly planning based on digital product descriptions
Sierla, S., Kyrki, V., Aarnio, P., & Vyatkin, V. (2018) · Computers in Industry · doi:10.1016/j.compind.2018.01.013 · Cited by 95
Integration of Sensors, Controllers and Instruments Using a Novel OPC Architecture
González, I., Calderón, A., Barragán, A., & Andújar, J. (2017) · Sensors · doi:10.3390/s17071512 · Cited by 52
A Design Approach to IoT Endpoint Security for Production Machinery Monitoring
Tedeschi, S., Emmanouilidis, C., Mehnen, J., & Roy, R. (2019) · Sensors · doi:10.3390/s19102355 · Cited by 33
(2025) · doi:10.1016/j.iot.2026.101938 · Cited by 31
Metadata
- Authors
- Hehenberger, P., Vogel-Heuser, B., Bradley, D., Eynard, B., Tomiyama, T., & Achiche, S.
- Venue
- Computers in Industry
- Publisher
- Elsevier BV
- Published
- 2016-10
- Volume
- 82
- Pages
- 273-289
- ISSN
- 0166-3615 (ISSN-L)
- OpenAlex
- W2503313501
- Cited by
- 312
- References
- 35
- FWCI
- 42.62
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.