Ontology Building for Cyber–Physical Systems: Application in the Manufacturing Domain

Hildebrandt, Constantin; Köcher, Aljosha; Kustner, Christof; Lopez-Enriquez, Carlos-Manuel; Müller, Andreas W.; Caesar, Birte; Gundlach, Claas Steffen; Fay, Alexander

doi:10.1109/tase.2020.2991777

Cited by 71 publications

(25 citation statements)

References 39 publications

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“…Hildebrandt et al present a domain-expert-centric approach to ontology design of CPPS, focusing on industry standards as ontology design patterns [10]. The approach is validated on an industrial use case encompassing system structure, processes, states, and data elements and has a strong focus on ontology reuse.…”

Section: Related Workmentioning

confidence: 99%

Accessing and Interpreting OPC UA Event Traces based on Semantic Process Descriptions

Tom¹,

Hranisavljevic²,

Fay³

2022

Preprint

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The analysis of event data from production systems is the basis for many applications associated with Industry 4.0. However, heterogeneous and disjoint data is common in this domain. As a consequence, contextual information of an event might be incomplete or improperly interpreted which results in suboptimal analysis results. This paper proposes an approach to access a production systems' event data based on the event data's context (such as the product type, process type or process parameters). The approach extracts filtered event logs from a database system by combining: 1) a semantic model of a production system's hierarchical structure, 2) a formalized process description and 3) an OPC UA information model. As a proof of concept we demonstrate our approach using a sample server based on OPC UA for Machinery Companion Specifications.

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Section: Related Workmentioning

confidence: 99%

Accessing and Interpreting OPC UA Event Traces based on Semantic Process Descriptions

Tom¹,

Hranisavljevic²,

Fay³

2022

Preprint

Self Cite

View full text Add to dashboard Cite

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“…For example, ontologies for robotics and autonomous system have been considered by Fiorini et al (2017) for task definition, automation, and other communication entities between humans and robots. Another example is ontology building for cyber-physical systems (CPS), which was proposed by Hildebrandt et al (2020). In contrast to those efforts, we are trying to employ ontologies in the automation process in order to generate data acquisition components.…”

Section: Related Workmentioning

confidence: 99%

Architecture and framework for data acquisition in cloud robotics

Watanobe¹,

Yaguchi²,

Nakamura³

et al. 2021

IJITCC

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“…When the proposed method is applied, heavyweight ontologies are created which formalize the knowledge of a domain (e.g., process description) in a reusable manner and can therefore be used as ontology design patterns. As presented in [Hildebrandt et al 2020] several ontology design patterns have already been published. In an ontology building project, these ontology design patterns are combined to obtain the ontology under development.…”

Section: Ontologies Define Terminologiesmentioning

confidence: 99%

Modeling and Analyzing Context-Sensitive Changes during Runtime

Wehrstedt

Brings

Caesar

et al. 2020

Model-Based Engineering of Collaborative Embedded Systems

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For collaborative embedded systems, it is essential to consider not only the behavior of each system and the interaction between systems, but also the interaction of systems with their often dynamic and unknown context.In this chapter, we present a solution approach based on process building blocks— describing both the modelling approach as well as the model execution approach—for engineering and operation to achieve the goal of developing systems that deal with dynamics in their open context at runtime by re-using the models from the engineering phase.

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Ontology Building for Cyber–Physical Systems: Application in the Manufacturing Domain

Cited by 71 publications

References 39 publications

Accessing and Interpreting OPC UA Event Traces based on Semantic Process Descriptions

Accessing and Interpreting OPC UA Event Traces based on Semantic Process Descriptions

Architecture and framework for data acquisition in cloud robotics

Modeling and Analyzing Context-Sensitive Changes during Runtime

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