Cited by 27Digital Transformation in IndustryFlexible and Reconfigurable Manufacturing SystemsApplied Advanced Technologies

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Systematic comparison of software agents and Digital Twins: differences, similarities, and synergies in industrial production

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Reinpold, Lasse M., Wagner, Lukas P., Gehlhoff, Felix, Ramonat, Malte, Kilthau, Maximilian, Gill, Milapji S., Reif, Jonathan T., Henkel, Vincent, Scholz, Lena, Fay, Alexander·2025·Journal of Intelligent Manufacturing

DOI 10.1007/s10845-023-02278-y

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Abstract

Abstract To achieve a highly agile and flexible production, a transformational shift is envisioned whereby industrial production systems evolve to be more decentralized, interconnected, and intelligent. Within this vision, production assets collaborate with each other, exhibiting a high degree of autonomy. Furthermore, information about individual production assets is accessible throughout their entire life-cycles. To realize this vision, the use of advanced information technology is required. Two commonly applied software paradigms in this context are Software Agents (referred to as Agents) and Digital Twins (DTs). This work presents a systematic comparison of Agents and DTs in industrial applications. The goal of the study is to determine the differences, similarities, and potential synergies between the two paradigms. The comparison is based on the purposes for which Agents and DTs are applied, the properties and capabilities exhibited by these software paradigms, and how they can be allocated within the Reference Architecture Model Industry 4.0. The comparison reveals that Agents are commonly employed in the collaborative planning and execution of production processes, while DTs are generally more applied to monitor production resources and process information. Although these observations imply characteristic sets of capabilities and properties for both Agents and DTs, a clear and definitive distinction between the two paradigms cannot be made. Instead, the analysis indicates that production assets utilizing a combination of Agents and DTs would demonstrate high degrees of intelligence, autonomy, sociability, and fidelity. To achieve this, further standardization is required, particularly in the field of DTs.

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Dario, O., Nagore, I., Arantza, B., et al. (2019). Fault injection in Digital Twin as a means to test the response to process faults at virtual commissioning: Paraninfo Building, University of Zaragoza, 10–13 September, 2019: Proceedings. 2019 24th IEEE international conference on emerging technologies and factory automation (ETFA).
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Sorted by citations

A decentralized optimization approach for scalable agent-based energy dispatch and congestion management
Kilthau, M., Henkel, V., Wagner, L. P., Gehlhoff, F., & Fay, A. (2024) · Applied Energy · doi:10.1016/j.apenergy.2024.124606 · Cited by 30
Self-citation
Semantic and modular orchestration of AI-driven digital twins for industrial interoperability and optimization
Juarez, M. G. J., Giret, A., & Botti, V. J. (2025) · Journal of Industrial Information Integration · doi:10.1016/j.jii.2025.100959 · Cited by 12
An inceptive approach for designing simple digital twins and industrial metaverse process frameworks for small manufacturing I5.0 environments using Node-RED
Kiangala, K. S., & Wang, Z. (2025) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-025-16434-6 · Cited by 9
A Multi-Agent Approach for the Optimized Operation of Modular Electrolysis Plants
Henkel, V., Wagner, L. P., Kilthau, M., Gehlhoff, F., & Fay, A. (2024) · Energies · doi:10.3390/en17143370 · Cited by 7
Self-citation
Towards enhanced cybersecurity in industrial control systems: a systematic review of context-based modeling, digital twins, and machine learning approaches
Abraham, D., Erceylan, G., Gkioulos, V., & Houmb, S. H. (2025) · International Journal of Information Security · doi:10.1007/s10207-025-01158-1 · Cited by 10

See all 27

Authors: Reinpold, L. M., Wagner, L. P., Gehlhoff, F., Ramonat, M., Kilthau, M., Gill, M. S., Reif, J. T., Henkel, V., Scholz, L., & Fay, A.
Affiliations: Helmut Schmidt University (DE)
Corresponding author: Reinpold, Lasse M.
ORCID: Reinpold, Lasse M.
Wagner, Lukas P.
Gehlhoff, Felix
Ramonat, Malte
Kilthau, Maximilian
Gill, Milapji S.
Henkel, Vincent
Fay, Alexander
Venue: Journal of Intelligent Manufacturing
Publisher: Springer Science and Business Media LLC
Published: 2024-01-04
Volume: 36
Issue: 2
Pages: 765-800
ISSN: 0956-5515 (ISSN-L)
1572-8145
DOI: 10.1007/s10845-023-02278-y
OpenAlex: W4390576566
Cited by: 27
References: 214
Citations by year: 2026: 7 · 2025: 11 · 2024: 9
FWCI: 5.54
Type: journal article
Language: en
Open access: hybrid
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0 (tdm)
creativecommons.org/licenses/by/4.0 (vor)
Locations: Journal of Intelligent Manufacturing (publishedVersion, cc-by)
arXiv (Cornell University) (submittedVersion)
Econstor (Econstor) (submittedVersion, cc-by)
RePEc: Research Papers in Economics (submittedVersion)
arXiv (Cornell University)
Funders: Digitalization and Technology Research Center of the Bundeswehr
Bundesministerium für Wirtschaft und Klimaschutz (03EI6035A)
VDI/VDE Innovation + Technik GmbH (16KN102724)
Bundesministerium für Bildung und Forschung (03HY116)
Helmut-Schmidt-Universität Universität der Bundeswehr Hamburg
Topics: Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Flexible and Reconfigurable Manufacturing Systems
Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Applied Advanced Technologies
Keywords: software agents, digital twin, industrial production, Industry 4.0, reference architecture, production monitoring

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Systematic comparison of software agents and Digital Twins: differences, similarities, and synergies in industrial production

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