The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
The MTA SZTAKI Smart Factory: Platform for Research and Project-oriented Skill Development in Higher Education
Open accessAbstract
Nowadays, the potential of learning factories as test beds and research plants is gaining recognition, and several facilities are extended or built up already with these complementing purposes in mind—among them the Smart Factory at the Fraunhofer Project Center at MTA SZTAKI currently completing a major stage of development. The paper presents the structure and key design principles of the plant, and explains how the composition and functionalities of the equipment implement focal principles of the Industry 4.0 and Cyber-Physical Systems concepts. Furthermore, it is shown how the Smart Factory provides students with challenges and resources for project-oriented development of their skills, and where these opportunities fit into technical higher education by hosting both individual student projects and courses with a specific structure of progress.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“or limiting geometry faults in the additive manufacturing processes [32,38]”
From Review of digital twin applications in manufacturing (2019) · cites this paper as [32]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“Five articles use a 3D dynamical Finite Element Method (FEM)-based model [32,34,38,55,66]”
From Review of digital twin applications in manufacturing (2019) · cites this paper as [32]
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
A Cyber-Physical Systems architecture for Industry 4.0-based manufacturing systems
Lee, J., Bagheri, B., & Kao, H.-A. (2015) · Manufacturing Letters · doi:10.1016/j.mfglet.2014.12.001 · Cited by 5,113
Cyber-physical Production Systems: Roots, Expectations and R&D Challenges
Monostori, L. (2014) · Procedia CIRP · doi:10.1016/j.procir.2014.03.115 · Cited by 1,281
Learning Factories for Research, Education, and Training
Abele, E., Metternich, J., Tisch, M., Chryssolouris, G., Sihn, W., ElMaraghy, H. A., Hummel, V., & Ranz, F. (2015) · Procedia CIRP · doi:10.1016/j.procir.2015.02.187 · Cited by 447
Industry 4.0 Learning Factory for regional SMEs
Faller, C., & Feldmüller, D. (2015) · Procedia CIRP · doi:10.1016/j.procir.2015.02.117 · Cited by 273
Die Vierte Industrielle Revolution – Der Weg in ein wertschaffendes Produktionsparadigma
Bauernhansl, T. (2014) · Springer eBooks · doi:10.1007/978-3-658-04682-8_1 · Cited by 263
Promoting Work-based Learning through INDUSTRY 4.0
Schuh, G., Gartzen, T., Rodenhauser, T., & Marks, A. (2015) · Procedia CIRP · doi:10.1016/j.procir.2015.02.213 · Cited by 171
Towards Socio-Cyber-Physical Systems in Production Networks
Frazzon, E. M., Hartmann, J., Makuschewitz, T., & Scholz‐Reiter, B. (2013) · Procedia CIRP · doi:10.1016/j.procir.2013.05.009 · Cited by 162
The State-of-the-Art and Prospects of Learning Factories
Wagner, U., AlGeddawy, T., ElMaraghy, H. A., & MŸller, E. (2012) · Procedia CIRP · doi:10.1016/j.procir.2012.07.020 · Cited by 158
Towards an Understanding of Cyber-physical Systems as Industrial Software-Product-Service Systems
Mikusz, M. (2014) · Procedia CIRP · doi:10.1016/j.procir.2014.02.025 · Cited by 98
Cyber-physical product manufacturing
Wright, P. K. (2013) · Manufacturing Letters · doi:10.1016/j.mfglet.2013.10.001 · Cited by 55
Research works printed but not linked: 4
- R. Beregi, Design of a prototype production control system to the Smart Factory, Master's thesis, Department of Manufacturing Science and Engineering, Budapest University of Technology and Economics (2015).
- A. Szobonya, Optimizing the internal logistics of the Smart Factory pilot system, Bachelor's thesis, Department of Manufacturing Science and Engineering, Budapest University of Technology and Economics (2016).
- K. Abai, Complex expansion of a pilot production system, Bachelor's thesis, Department of Manufacturing Science and Engineering, Budapest University of Technology and Economics (2015).
- Á. Benke, UR5 industrial robot based solution of a packing problem, Bachelor's thesis, Department of Manufacturing Science and Engineering, Budapest University of Technology and Economics (2015).
Cited by
Sorted by citations
Cyber-physical systems in manufacturing
Monostori, L., Kádár, B., Bauernhansl, T., Kondoh, S., Kumara, S. R. T., Reinhart, G., Sauer, O., Schuh, G., Sihn, W., & Ueda, K. (2016) · CIRP Annals · doi:10.1016/j.cirp.2016.06.005 · Cited by 1,708
Review of digital twin applications in manufacturing
Cimino, C., Negri, E., & Fumagalli, L. (2019) · Computers in Industry · doi:10.1016/j.compind.2019.103130 · Cited by 874
The Digital Twin: Demonstrating the Potential of Real Time Data Acquisition in Production Systems ☆
Uhlemann, T., Schock, C., Lehmann, C., Freiberger, S., & Steinhilper, R. (2017) · Procedia Manufacturing · doi:10.1016/j.promfg.2017.04.043 · Cited by 426
Learning factories for future oriented research and education in manufacturing
Abele, E., Chryssolouris, G., Sihn, W., Metternich, J., ElMaraghy, H. A., Seliger, G., Sivard, G., ElMaraghy, W. H., Hummel, V., Tisch, M., et al. (2017) · CIRP Annals · doi:10.1016/j.cirp.2017.05.005 · Cited by 389
Requirements of the Smart Factory System: A Survey and Perspective
Mabkhot, M. M., Al-Ahmari, A. M., Salah, B., & Alkhalefah, H. (2018) · Machines · doi:10.3390/machines6020023 · Cited by 293
AN INVESTIGATION OF INDUSTRY 4.0 SKILLS REQUIREMENTS
Maisiri, W., Darwish, H., & Dyk, L. V. (2019) · The South African Journal of Industrial Engineering · doi:10.7166/30-3-2230 · Cited by 169
Development capabilities for smart products
Tomiyama, T., Lutters, E., Stark, R., & Abramovici, M. (2019) · CIRP Annals · doi:10.1016/j.cirp.2019.05.010 · Cited by 179
Tisch, M., & Metternich, J. (2017) · Procedia Manufacturing · doi:10.1016/j.promfg.2017.04.027 · Cited by 99
Resman, M., Pipan, M., Šimić, M., & Herakovič, N. (2019) · Advances in Production Engineering & Management · doi:10.14743/apem2019.2.318 · Cited by 85
A modular factory testbed for the rapid reconfiguration of manufacturing systems
Kim, D. Y., Park, J. W., Baek, S., Park, K., Kim, H.-R., Park, J.-I., Kim, H.-S., Kim, B., Oh, H., Namgung, K., et al. (2019) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-019-01471-2 · Cited by 77
A Smart Factory Architecture Based on Industry 4.0 Technologies: Open-Source Software Implementation
Fortoul-Díaz, J., Carrillo-Martínez, L. A., Centeno-Tellez, A., Cortes-Santacruz, F., Olmos-Pineda, I., & Flores-Quintero, R. R. (2023) · IEEE Access · doi:10.1109/access.2023.3316116 · Cited by 42
Added value of a virtual approach to simulation-based learning in a manufacturing learning factory
Tvenge, N., Ogorodnyk, O., Østbø, N. P., & Martinsen, K. (2020) · Procedia CIRP · doi:10.1016/j.procir.2020.05.007 · Cited by 47
Educational Test Bed 4.0: a teaching tool for Industry 4.0
Yoshino, R. T., Pinto, M. M. A., Pontes, J., Treinta, F. T., Justo, J. F., & Santos, M. M. D. (2020) · European Journal of Engineering Education · doi:10.1080/03043797.2020.1832966 · Cited by 35
Ward, R., Soulatiantork, P., Finneran, S., Hughes, R., & Tiwari, A. (2021) · Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture · doi:10.1177/09544054211002464 · Cited by 34
Synergy of multi-modelling for process control
Beregi, R., Szaller, Á., & Kádár, B. (2018) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2018.08.473 · Cited by 34
Self-citationElMaraghy, H. A., Moussa, M., ElMaraghy, W. H., & Abbas, M. (2017) · Procedia Manufacturing · doi:10.1016/j.promfg.2017.04.008 · Cited by 29
Development of a Smart Manufacturing Execution System Architecture for SMEs: A Czech Case Study
Pfeifer, M. R. (2021) · Sustainability · doi:10.3390/su131810181 · Cited by 26
A novel fluid architecture for cyber-physical production systems
Beregi, R. J., Pedone, G., & Mezgár, I. (2019) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2019.1571239 · Cited by 20
Self-citationPrioritising smart factory investments – A project portfolio selection approach
Dreyer, S., Egger, A., Püschel, L., & Röglinger, M. (2020) · International Journal of Production Research · doi:10.1080/00207543.2020.1849845 · Cited by 19
A science mapping study on learning factories research
Martı́nez, P., Vargas‐Martínez, A., Roman‐Flores, A., & Ahmad, R. (2020) · Procedia Manufacturing · doi:10.1016/j.promfg.2020.04.072 · Cited by 17
Preparation and Production Control in Smart Factory Model
Żywicki, K., Zawadzki, P., & Hamrol, A. (2017) · Advances in intelligent systems and computing · doi:10.1007/978-3-319-56541-5_53 · Cited by 16
A systematic review of faculty research repositories at higher education institutions
Zibani, P., Rajkoomar, M., & Naicker, N. (2021) · Digital Library Perspectives · doi:10.1108/dlp-04-2021-0035 · Cited by 15
Current trends in teaching cyber physical systems engineering: A literature review
Mäkiö, E. (2017) · IEEE International Conference on Industrial Informatics (INDIN) · doi:10.1109/indin.2017.8104826 · Cited by 14
Learning Factories in Vocational Schools
Scheid, R. (2018) · Springer eBooks · doi:10.1007/978-3-319-46215-8_15 · Cited by 11
Fulfilling Individual Requirements of Customers in Smart Factory Model
Żywicki, K., & Zawadzki, P. (2017) · Lecture notes in mechanical engineering · doi:10.1007/978-3-319-68619-6_18 · Cited by 10
SEPT Learning Factory Framework
Centea, D., Elbestawi, M. A., Singh, I., & Wanyama, T. (2018) · Lecture notes in networks and systems · doi:10.1007/978-3-319-95678-7_40 · Cited by 9
Hu, Y., Zhou, J., & Gao, B. (2021) · Advances in Multimedia · doi:10.1155/2021/1220512 · Cited by 8
RetractedSmart factory concepts and their fitness to the plastics processing industry: a critical review
Bibow, P., Sapel, P., & Hopmann, C. (2025) · Flexible Services and Manufacturing Journal · doi:10.1007/s10696-025-09593-x · Cited by 7
Cyber and physical equipment digital control system in Industry 4.0 item designing company
Gurjanov, A. V., Zakoldaev, D. A., Shukalov, A. V., & Zharinov, I. O. (2018) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1015/5/052035 · Cited by 7
Computer-aided design of technical documentation on the digital product models of Industry 4.0
Zakoldaev, D. A., Shukalov, A. V., Zharinov, I. O., & Zharinov, O. O. (2019) · IOP Conference Series Materials Science and Engineering · doi:10.1088/1757-899x/483/1/012069 · Cited by 6
A Learning Factory Framework: Challenges and Solutions for an Irish University*
Quinn, W., Cionca, V., Witheephanich, K., & Öztürk, C. (2022) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2022.09.471 · Cited by 5
Kovaleski, F. (2020) · AYA Editora eBooks · doi:10.47573/aya.88580.1.0 · Cited by 5
Diani, M., & Colledani, M. (2020) · Procedia CIRP · doi:10.1016/j.procir.2020.03.117 · Cited by 5
Digital Twin training concept based on miniature demonstration factoriesPreprint
Kremslehner, N., Sobottka, T., Nacsa, J., Beregi, R. J., & Schlund, S. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4458212 · Cited by 5
Self-citationBellucci, M., Chiurco, A., Cimino, A., Ferro, D., Longo, F., & Padovano, A. (2022) · IEEE Mediterranean Electrotechnical Conference (MELECON) · doi:10.1109/melecon53508.2022.9843084 · Cited by 4
Determining stable equilibria of spatial objects and validating the results with drop simulation
Fekula, M., & Horváth, G. (2019) · Procedia CIRP · doi:10.1016/j.procir.2019.03.055 · Cited by 4
Smart Development with Digital Intelligent Cities in Cross-Border Regions
Gyulai, T., Nagy, M., & Cibu-Buzac, R. (2022) · Soproni Egyetem Kiadó eBooks · doi:10.35511/978-963-334-411-8_s5_gyulai_et_al · Cited by 3
A Cross-Disciplinary Outlook of Directions and Challenges in Industrial Electronics
She, J., Guzmán-Miranda, H., Huang, V., Chen, A. C., Karnouskos, S., Dunai, L., Ma, C., Tisan, A., & Yokota, S. (2022) · IEEE Open Journal of the Industrial Electronics Society · doi:10.1109/ojies.2022.3174218 · Cited by 3
Main Requirements of a Cyber Physical Production System Demonstrator
Petruse, R. E., Bondrea, I., & Nicolae, I. C. (2019) · Acta Universitatis Cibiniensis Technical Series · doi:10.2478/aucts-2019-0015 · Cited by 3
Zakoldaev, D. A., Shukalov, A. V., Zharinov, I. O., & Zharinov, O. O. (2019) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1333/7/072030 · Cited by 3
A small-scale educational workbench for Industry 4.0
Pacheco, A., & Reis, J. S. D. S. (2019) · Annual Conference of the IEEE Industrial Electronics Society (IECON) · doi:10.1109/iecon.2019.8927746 · Cited by 3
Efficiency of Automatic Design in the Production Preparation Process for an Intelligent Factory
Zawadzki, P., Żywicki, K., Grajewski, D., & Górski, F. (2018) · Advances in intelligent systems and computing · doi:10.1007/978-3-319-97490-3_52 · Cited by 2
A Cross-Disciplinary View of Industrial Electronics: Change, Chance, and Challenge
She, J., Guzmán-Miranda, H., Huang, V., Chen, A. C., Karnouskos, S., Dunai, L., Tisan, A., & Yokota, S. (2021) · Annual Conference of the IEEE Industrial Electronics Society (IECON) · doi:10.1109/iecon48115.2021.9589742 · Cited by 2
Enabling Distance Learning and Remote Collaboration in Layout and Process PlanningPreprint
Kemény, Z., Beregi, R. J., Hajós, M., Csempesz, J., & Nacsa, J. (2021) · SSRN Electronic Journal · doi:10.2139/ssrn.3858609 · Cited by 2
Self-citationProject-based Learning Case of Master Students in Russian North
Druzhinina, M. V., & Zashikhina, I. M. (2017) · International Scientific and Practical Conference "Current Issues of Linguistics and Didactics: The Interdisciplinary Approach in Humanities" (CILDIAH) · doi:10.2991/cildiah-17.2017.13 · Cited by 1
Computer control system for automatic manufacturing Industry 4.0
Gurjanov, A. V., Zakoldaev, D. A., Shukalov, A. V., Zharinov, I. O., & Zharinov, O. O. (2018) · IOP Conference Series Materials Science and Engineering · doi:10.1088/1757-899x/441/1/012063 · Cited by 1
Ecosystem of education competence center of the Industry 4.0
Zakoldaev, D. A., Shukalov, A. V., Zharinov, I. O., & Dorofeev, N. I. (2019) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1399/4/044015 · Cited by 1
Concept of a Modular Embedded Computing Platform for Automation Extension ExperimentsPreprint
Kemény, Z., Beregi, R. J., & Abai, K. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4469200 · Cited by 1
Self-citationTransport system organization of an Industry 4.0 cyber and physical production company
Zakoldaev, D. A., Shukalov, A. V., Zharinov, I. O., & Zharinov, O. O. (2018) · IOP Conference Series Materials Science and Engineering · doi:10.1088/1757-899x/450/4/042018
The smart design process of seats mounting for public transport vehicles
Zawadzki, P., KŻywicki, Krajanowski-Kaleta, J., Promiński, R., Jankowiak, T., Szymański, S., Szymański, M., & Mróz, A. (2022) · Journal of Physics Conference Series · doi:10.1088/1742-6596/2198/1/012043
Beregi, R. J., Kemény, Z., Godó, G., Abai, K., Farbaky, P., & Pedone, G. (2025) · Lecture notes in networks and systems · doi:10.1007/978-3-031-98880-6_18
Self-citation
Metadata
- Authors
- Kemény, Z., Beregi, R. J., Erdős, G., & Nacsa, J.
- Affiliations
- HUN-REN Institute for Computer Science and Control (HU)
- Budapest University of Technology and Economics (HU)
- Corresponding author
- Kemény, Zsolt
- Venue
- Procedia CIRP
- Publisher
- Elsevier BV
- Published
- 2016
- Volume
- 54
- Pages
- 53-58
- ISSN
- 2212-8271 (ISSN-L)
- OpenAlex
- W2534809762
- Cited by
- 52
- References
- 15
- Citations by year
- 2025: 2 · 2023: 4 · 2022: 5 · 2021: 6 · 2020: 6 · 2019: 12 · 2018: 8 · 2017: 8 · 2016: 1
- FWCI
- 8.60
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- Locations
- Procedia CIRP (publishedVersion, cc-by-nc-nd)
- SZTAKI Publication Repository (Hungarian Academy of Sciences) (submittedVersion)
- Fraunhofer-Publica (Fraunhofer-Gesellschaft) (submittedVersion)
- Funders
- Fonds National de la Recherche Luxembourg
- Hungarian Scientific Research Fund
- Topics
- Physical Sciences › Engineering › Mechanical Engineering › Mechatronics Education and Applications
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Social Sciences › Education › Engineering Education and Pedagogy
- Keywords
- learning factory, smart factory, Industry 4.0, cyber-physical systems, project-based learning, skill development, higher technical education, student projects
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
