Details
| Original language | English |
|---|---|
| Title of host publication | Software Architecture |
| Subtitle of host publication | ECSA 2022 Tracks and Workshops |
| Editors | Thais Batista, Claudia Raibulet, Tomas Bures, Henry Muccini |
| Publisher | Springer Science and Business Media Deutschland GmbH |
| Pages | 265-283 |
| Number of pages | 19 |
| ISBN (electronic) | 978-3-031-36889-9 |
| ISBN (print) | 9783031368882 |
| Publication status | Published - 2023 |
| Event | 16th European Conference on Software Architecture, ECSA 2022 - Prague, Czech Republic Duration: 19 Sept 2022 → 23 Sept 2022 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 13928 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (electronic) | 1611-3349 |
Abstract
For a broader adoption of AI in industrial production, adequate infrastructure capabilities and ecosystems are crucial. This includes easing the integration of AI with industrial devices, support for distributed deployment, monitoring, and consistent system configuration. IIoT platforms can play a major role here by providing a unified layer for the heterogeneous Industry 4.0/IIoT context. However, existing IIoT platforms still lack required capabilities to flexibly integrate reusable AI services and relevant standards such as Asset Administration Shells or OPC UA in an open, ecosystem-based manner. This is exactly what our next level Intelligent Industrial Production Ecosphere (IIP-Ecosphere) platform addresses, employing a highly configurable low-code based approach. In this paper, we introduce the design of this platform and discuss an early evaluation in terms of a demonstrator for AI-enabled visual quality inspection. This is complemented by insights and lessons learned during this early evaluation activity.
Keywords
- Artificial Intelligence, Asset Administration Shells, IIoT, Industry 4.0, Platform
ASJC Scopus subject areas
- Mathematics(all)
- Theoretical Computer Science
- Computer Science(all)
- General Computer Science
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Software Architecture: ECSA 2022 Tracks and Workshops. ed. / Thais Batista; Claudia Raibulet; Tomas Bures; Henry Muccini. Springer Science and Business Media Deutschland GmbH, 2023. p. 265-283 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13928 LNCS).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Developing an AI-Enabled IIoT Platform
T2 - 16th European Conference on Software Architecture, ECSA 2022
AU - Eichelberger, Holger
AU - Palmer, Gregory
AU - Reimer, Svenja
AU - Vu, Tat Trong
AU - Do, Hieu
AU - Laridi, Sofiane
AU - Weber, Alexander
AU - Niederée, Claudia
AU - Hildebrandt, Thomas
N1 - Funding Information: Supported by the German Ministry of Economics and Climate Action (BMWK) under grant numbers 01MK20006A and 01MK20006D.
PY - 2023
Y1 - 2023
N2 - For a broader adoption of AI in industrial production, adequate infrastructure capabilities and ecosystems are crucial. This includes easing the integration of AI with industrial devices, support for distributed deployment, monitoring, and consistent system configuration. IIoT platforms can play a major role here by providing a unified layer for the heterogeneous Industry 4.0/IIoT context. However, existing IIoT platforms still lack required capabilities to flexibly integrate reusable AI services and relevant standards such as Asset Administration Shells or OPC UA in an open, ecosystem-based manner. This is exactly what our next level Intelligent Industrial Production Ecosphere (IIP-Ecosphere) platform addresses, employing a highly configurable low-code based approach. In this paper, we introduce the design of this platform and discuss an early evaluation in terms of a demonstrator for AI-enabled visual quality inspection. This is complemented by insights and lessons learned during this early evaluation activity.
AB - For a broader adoption of AI in industrial production, adequate infrastructure capabilities and ecosystems are crucial. This includes easing the integration of AI with industrial devices, support for distributed deployment, monitoring, and consistent system configuration. IIoT platforms can play a major role here by providing a unified layer for the heterogeneous Industry 4.0/IIoT context. However, existing IIoT platforms still lack required capabilities to flexibly integrate reusable AI services and relevant standards such as Asset Administration Shells or OPC UA in an open, ecosystem-based manner. This is exactly what our next level Intelligent Industrial Production Ecosphere (IIP-Ecosphere) platform addresses, employing a highly configurable low-code based approach. In this paper, we introduce the design of this platform and discuss an early evaluation in terms of a demonstrator for AI-enabled visual quality inspection. This is complemented by insights and lessons learned during this early evaluation activity.
KW - Artificial Intelligence
KW - Asset Administration Shells
KW - IIoT
KW - Industry 4.0
KW - Platform
UR - http://www.scopus.com/inward/record.url?scp=85186770238&partnerID=8YFLogxK
U2 - 10.48550/arXiv.2207.04515
DO - 10.48550/arXiv.2207.04515
M3 - Conference contribution
AN - SCOPUS:85186770238
SN - 9783031368882
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 265
EP - 283
BT - Software Architecture
A2 - Batista, Thais
A2 - Raibulet, Claudia
A2 - Bures, Tomas
A2 - Muccini, Henry
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 19 September 2022 through 23 September 2022
ER -