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Synergy of multi-modelling for process control
Open accessAbstract
In this paper a multi-modelling experiment is presented through which we have studied the possibilities of manufacturing process control supported by different digital simulation models. The main pillar of the study is a real, operating, research and demonstration cyber-physical production system which is detailed in the study. Our digital twin of the system in question includes two different virtual models; an agent-based model endowed with the ability of error handling, and a discrete-event simulation-based model for forecasting and supporting the error handling routine with evaluating bids. The experiment includes typical manufacturing processes with machine failures, which should be detected and recognized to invoke both simulations for re-forecast and error management.
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In the citing paper
“The concept of DT is still evolving and its definition has matured over the years as Negri reports in [6].”
From Review of digital twin applications in manufacturing (2019) · cites this paper as [6]
In the citing paper
“The latter type of simulation, when synchronized with the field, complies in all aspects with the definition of DT given by [17] and reported in [6,18]”
From Review of digital twin applications in manufacturing (2019) · cites this paper as [6]
In the citing paper
“In this vision, the future of manufacturing is characterized by entities, CPSs or CPPSs, able to collect data directly from the field and to replicate the physical production system in the cyber world through various digital models that compose a DT”
From Review of digital twin applications in manufacturing (2019) · cites this paper as [6]
In the citing paper
“This new simulation approach is generally referring to the elaboration of Digital Twins (DT) [6].”
From Review of digital twin applications in manufacturing (2019) · cites this paper as [6]
In the citing paper
“DT in production systems in the Industry 4.0 meaning were first proposed in 2015, as shown by [6].”
From Review of digital twin applications in manufacturing (2019) · cites this paper as [6]
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References 15 · Cited by 34
Research works printed but not linked: 11
- 2005, C2PS. A Digital Twin Architecture Reference Model for the Cloud-Based Cyber-Physical Systems, IEEE Access, 5, 2050
- Beregi, R. (2015): Design of a prototype production control system to the Smart Factory. In Master’s thesis, Department of Manufacturing Science and Engineering, Budapest University of Technology and Economics.
- Colledani, 2005, A Decomposition Method to Support the Configuration/Reconfiguration of Production Systems, In CIRP Annals, 54, 441, 10.1016/S0007-8506(07)60140-1 · DOI
- 2016, IET: E&T Magazine, 11, 44
- Kádár, 2013, Semantic Virtual Factory supporting interoperable modelling and evaluation of production systems, In CIRP Annals, 62, 443, 10.1016/j.cirp.2013.03.045 · DOI
- Márkus, 1996, A Market Approach to Holonic Manufacturing, In CIRP Annals, 45, 433, 10.1016/S0007-8506(07)63096-0 · DOI
- Monostori, 2006, Agent-Based Systems for Manufacturing, In CIRP Annals, 55, 697, 10.1016/j.cirp.2006.10.004 · DOI
- Monostori, 2015, Cooperative control in production and logistics, Annual Reviews in Control, 39, 12, 10.1016/j.arcontrol.2015.03.001 · DOI
- Monostori, 2016, Cyber-physical systems in manufacturing, In CIRP Annals, 65, 621, 10.1016/j.cirp.2016.06.005 · DOI
- Ryan, 2006, Process modeling for simulation, In Computers in Industry, 57, 437, 10.1016/j.compind.2006.02.002 · DOI
- Zhang, H.; Liu, Q.; Chen, X.; Zhang, D.; Leng, J. (2017): A digital twin-based approach for designing and decoupling of hollow glass production line. In IEEE Access, p. 1. DOI: 10.1109/ACCESS.2017.2766453. · DOI · Paper page
Metadata
- Authors
- Beregi, R., Szaller, Á., & Kádár, B.
- Affiliations
- Budapest University of Technology and Economics (HU)
- HUN-REN Institute for Computer Science and Control (HU)
- Corresponding author
- Beregi, Richárd
- Venue
- IFAC-PapersOnLine
- Publisher
- Elsevier BV
- Published
- 2018
- Volume
- 51
- Issue
- 11
- Pages
- 1023-1028
- ISSN
- 2405-8963 (ISSN-L)
- OpenAlex
- W2892379705
- Cited by
- 34
- References
- 15
- Citations by year
- 2025: 2 · 2024: 4 · 2023: 2 · 2022: 8 · 2021: 8 · 2020: 8 · 2019: 2
- FWCI
- 3.72
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- IFAC-PapersOnLine (publishedVersion)
- SZTAKI Publication Repository (Hungarian Academy of Sciences) (submittedVersion)
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Social Sciences › Decision Sciences › Management Science and Operations Research › Simulation Techniques and Applications
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Flexible and Reconfigurable Manufacturing Systems
- Keywords
- manufacturing process control, digital twin, cyber-physical production systems, agent-based modeling, discrete event simulation, error handling, machine failure detection, bid evaluation
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- The paper
- Beregi, R., Szaller, Á., & Kádár, B. (2018). Synergy of multi-modelling for process control. IFAC-PapersOnLine. https://doi.org/10.1016/j.ifacol.2018.08.473
