Ontological Representation of Cyber–Physical Systems for Knowledge-Based Production

This paper presents a process-centric ontology for the semantic representation of cyber–physical systems (CPSs) within knowledge-based production planning (KPP). The approach integrates physical systems (PSs), cyber systems (CSs), and CPSs into a unified semantic model based on a three-layer classification. The ontology was implemented using OWL and integrated into a Neo4j-based graph architecture to support semantic querying and process modeling. The evaluation was conducted using prototypical manufacturing scenarios, including semiconductor and mechanical engineering domains. Validation included (i) consistency checking using the HermiT reasoner, (ii) execution of SPARQL queries for retrieving CPS-related process information, and (iii) integration into a three-stage planning model. The results show that the ontology enables consistent semantic representation and cross-domain querying of CPS-based production processes. The work provides a validated proof-of-concept and establishes a foundation for future research on ontology-based production systems.

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Publication Details

Journal
Electronics
Published
2026-05-22
DOI
https://doi.org/10.3390/electronics15112235
Primary Topic
Flexible and Reconfigurable Manufacturing Systems
Type
article
Field-Weighted Citation Impact
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article

Ontological Representation of Cyber–Physical Systems for Knowledge-Based Production

Kathrin Gorgs, Matthias L. Hemmje, Tobias Vogel, Tom Löhnert
Electronics
Flexible and Reconfigurable Manufacturing Systems
article

Ontological Representation of Cyber–Physical Systems for Knowledge-Based Production

Kathrin Gorgs, Matthias L. Hemmje, Tobias Vogel, Tom Löhnert
article en

Abstract

This paper presents a process-centric ontology for the semantic representation of cyber–physical systems (CPSs) within knowledge-based production planning (KPP). The approach integrates physical systems (PSs), cyber systems (CSs), and CPSs into a unified semantic model based on a three-layer classification. The ontology was implemented using OWL and integrated into a Neo4j-based graph architecture to support semantic querying and process modeling. The evaluation was conducted using prototypical manufacturing scenarios, including semiconductor and mechanical engineering domains. Validation included (i) consistency checking using the HermiT reasoner, (ii) execution of SPARQL queries for retrieving CPS-related process information, and (iii) integration into a three-stage planning model. The results show that the ontology enables consistent semantic representation and cross-domain querying of CPS-based production processes. The work provides a validated proof-of-concept and establishes a foundation for future research on ontology-based production systems.

ElectronicsVol. 15(11)
FernUniversität in Hagen (DE)
Openalex Percentile: Top 5%
Flexible and Reconfigurable Manufacturing Systems
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