Record link: 
http://hdl.handle.net/20.500.12708/192833
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Title: 
Knowledge Representation of Asset Information and Performance in OT Environments
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Citation: 
Bhole, M., Kastner, W., & Sauter, T. (2023). Knowledge Representation of Asset Information and Performance in OT Environments. In 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA). 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA), Sinaia, Romania. IEEE. https://doi.org/10.1109/ETFA54631.2023.10275721
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Publisher DOI: 
10.1109/ETFA54631.2023.10275721
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Publication Type: 
Inproceedings - Full-Paper Contribution
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Language: 
English
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Authors: 
Bhole, Mukund 
Kastner, Wolfgang 
Sauter, Thilo 
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Organisational Unit: 
E191-03 - Forschungsbereich Automation Systems 
E384-01 - Forschungsbereich Software-intensive Systems 
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Published in: 
2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA) 
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ISBN: 
979-8-3503-3991-8
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DOI of the book: 
10.1109/ETFA54631.2023
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Date (published): 
12-Oct-2023
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Event name: 
2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA) 
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Event date: 
12-Sep-2023 - 15-Sep-2023
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Event place: 
Sinaia, Romania
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Number of Pages: 
8
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Publisher: 
IEEE, Piscataway
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Peer reviewed: 
Yes
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Keywords: 
Asset Information Mining; Knowledge Representation; Operational Technology
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Abstract: 
To make a management decision for the Operational Technology (OT) environment, obtaining OT asset information from a plant is essential. Key Performance Indicators (KPIs) can play a crucial role in evaluating the performance of the manufacturing process, minimizing production costs, assessing process effectiveness, and investigating various settings to improve performance, operations, and quality in OT. This paper aims to provide a detailed examination of how Asset Information Mining Sources (AIMSs) support the process for acquiring both static and runtime OT asset information. Once we have obtained accurate OT asset information, we can calculate the KPIs and incorporate them into a knowledge representation using an ontology-based model. This model can assist the management team in making informed decisions and provide a roadmap for exploring further automation possibilities.
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Project title: 
Model-based Security & Safety Evaluation of OT Components: 1708499 (TÜV Austria Holding AG) 
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Research Areas: 
Digital Transformation in Manufacturing: 20%
Computer Engineering and Software-Intensive Systems: 60%
Automation and Robotics: 20%
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Science Branch: 
1020 - Informatik: 50%
2020 - Elektrotechnik, Elektronik, Informationstechnik: 40%
1010 - Mathematik: 10%
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Appears in Collections:
Conference Paper

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