Plug-and-Simulate within Modular Assembly Line enabled by Digital Twins and the use of AutomationML
Open accessAbstract
The Digital Age is becoming the de-facto of future direction in manufacturing domain. Its main driver is the pressure of shorter product life cycles and leads companies to faster engineering time of their production lines. To cope with the need, recent literature has successfully shown modular production and assembly line concepts by using standardized interfaces on electromechanical and communication level. This change entails new challenges. Given the fact that production life cycle decreases, the usage of tools for digital manufacturing and simulation grow in importance to support and evaluate the impact of increasing engineering and decision-making processes. The concurrent combination of the physical world with its digital counterpart will be crucial. This paper proposes how engineers set up the digital environment automatically by using a common data model inspired by the Digital Twin concept. Its instantiation for several assembly modules based on AutomationML consists of a set of engineering data and relevant models to support a proof-of-concept of Plug-and-Simulate within a modular, multi-vendor assembly line.
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In some reviewed cases, DT was used for the design of a machine, a laboratory environment, a product or production environment, or for redesign of the working environment.
“- 7) In some cases, the DT is used for the 'Design' of a machine [68,72], of a laboratory environment [71], of a product or production environment [69,73] or for the redesign of the working environment [70].”
From Review of digital twin applications in manufacturing (2019) · cites this paper as [72]
Some DT applications in the reviewed literature do not comply with either of the two mentioned service groups, being developed specifically to offer one single service, such as only system monitoring or performance optimization.
“Some DT applications in literature do not comply with one of the two mentioned groups, as they are developed specifically to offer one single service, such as only for system monitoring ([67,72]), or for performance optimization ([41,64,73]).”
From Review of digital twin applications in manufacturing (2019) · cites this paper as [72]
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References 15 · Cited by 88
- Authors
- Um, J., Weyer, S., & Quint, F.
- Affiliations
- SmartFactory (Germany) (DE)
- German Research Centre for Artificial Intelligence (DE)
- Corresponding author
- Um, Jumyung
- Weyer, Stephan
- Quint, Fabian
- ORCID
- Um, Jumyung
- Venue
- IFAC-PapersOnLine
- Publisher
- Elsevier BV
- Published
- 2017-07
- Volume
- 50
- Issue
- 1
- Pages
- 15904-15909
- ISSN
- 2405-8963 (ISSN-L)
- OpenAlex
- W2766417543
- Cited by
- 88
- References
- 15
- Citations by year
- 2026: 3 · 2025: 5 · 2024: 13 · 2023: 17 · 2022: 14 · 2021: 16 · 2020: 10 · 2019: 7 · 2018: 3
- FWCI
- 6.00
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- IFAC-PapersOnLine (publishedVersion)
- Funders
- European Commission
- Horizon 2020 (678556, 680633)
- 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 › Manufacturing Process and Optimization
- Keywords
- digital twin, AutomationML, common data model, digital manufacturing, standardized interfaces
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