Details
| Original language | English |
|---|---|
| Title of host publication | 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation |
| Subtitle of host publication | ETFA |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Number of pages | 8 |
| ISBN (electronic) | 9798350339918 |
| ISBN (print) | 979-8-3503-3992-5 |
| Publication status | Published - 2023 |
| Event | 28th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2023 - Sinaia, Romania Duration: 12 Sept 2023 → 15 Sept 2023 |
Publication series
| Name | IEEE International Conference on Emerging Technologies and Factory Automation, ETFA |
|---|---|
| Volume | 2023-September |
| ISSN (Print) | 1946-0740 |
| ISSN (electronic) | 1946-0759 |
Abstract
The development of intelligent solutions for manufacturing is a challenging task. Industry 4.0 platforms can provide a unifying layer here. However, flexible AI support, openness for evolving service and components from different vendors and adaptability to the diverse and changing requirements is required from such a platform to boost IIoT development. For this purpose, our approach combines - as a "power trio"- (1) wide use of Asset Administration Shells (AAS) for targeting device, component and service heterogeneity, with (2) configuration support for dealing with the diverse and changing requirements and (3) code generation for cost-effective creation of customer specific platform instances, AAS and AI-based Industry 4.0 applications on top of the IIP-Ecosphere platform. The platform has been implemented based on vertically scaled AAS and evaluated with two Industry 4.0 demonstrators. In this context, we discuss the experiences we made with our approach.
Keywords
- Artificial Intelligence, Asset Administration Shells, Industry 4.0/IIoT Platforms, Model-driven Engineering
ASJC Scopus subject areas
- Engineering(all)
- Electrical and Electronic Engineering
- Engineering(all)
- Control and Systems Engineering
- Engineering(all)
- Industrial and Manufacturing Engineering
- Computer Science(all)
- Computer Science Applications
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2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation: ETFA. Institute of Electrical and Electronics Engineers Inc., 2023. (IEEE International Conference on Emerging Technologies and Factory Automation, ETFA; Vol. 2023-September).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Asset Administration Shells, Configuration, Code Generation
T2 - 28th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2023
AU - Eichelberger, Holger
AU - Niederée, Claudia
N1 - Funding Information: ACKNOWLEDGEMENT This work is partially supported by the German Federal Ministry of Economic Affairs and Climate Action (BMWK, IIP-Ecosphere – 01MK20006A, 01MK20006C). We also would like to thank Monika Staciwa and Christopher Knappe for their work on the AAS-based platform management HMI.
PY - 2023
Y1 - 2023
N2 - The development of intelligent solutions for manufacturing is a challenging task. Industry 4.0 platforms can provide a unifying layer here. However, flexible AI support, openness for evolving service and components from different vendors and adaptability to the diverse and changing requirements is required from such a platform to boost IIoT development. For this purpose, our approach combines - as a "power trio"- (1) wide use of Asset Administration Shells (AAS) for targeting device, component and service heterogeneity, with (2) configuration support for dealing with the diverse and changing requirements and (3) code generation for cost-effective creation of customer specific platform instances, AAS and AI-based Industry 4.0 applications on top of the IIP-Ecosphere platform. The platform has been implemented based on vertically scaled AAS and evaluated with two Industry 4.0 demonstrators. In this context, we discuss the experiences we made with our approach.
AB - The development of intelligent solutions for manufacturing is a challenging task. Industry 4.0 platforms can provide a unifying layer here. However, flexible AI support, openness for evolving service and components from different vendors and adaptability to the diverse and changing requirements is required from such a platform to boost IIoT development. For this purpose, our approach combines - as a "power trio"- (1) wide use of Asset Administration Shells (AAS) for targeting device, component and service heterogeneity, with (2) configuration support for dealing with the diverse and changing requirements and (3) code generation for cost-effective creation of customer specific platform instances, AAS and AI-based Industry 4.0 applications on top of the IIP-Ecosphere platform. The platform has been implemented based on vertically scaled AAS and evaluated with two Industry 4.0 demonstrators. In this context, we discuss the experiences we made with our approach.
KW - Artificial Intelligence
KW - Asset Administration Shells
KW - Industry 4.0/IIoT Platforms
KW - Model-driven Engineering
UR - http://www.scopus.com/inward/record.url?scp=85175451222&partnerID=8YFLogxK
U2 - 10.1109/ETFA54631.2023.10275339
DO - 10.1109/ETFA54631.2023.10275339
M3 - Conference contribution
AN - SCOPUS:85175451222
SN - 979-8-3503-3992-5
T3 - IEEE International Conference on Emerging Technologies and Factory Automation, ETFA
BT - 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 12 September 2023 through 15 September 2023
ER -