A review and classification of manufacturing ontologies

Patrick Sapel (), Lina Molinas Comet (), Iraklis Dimitriadis, Christian Hopmann and Stefan Decker
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Patrick Sapel: Institute for Plastics Processing at RWTH Aachen University
Lina Molinas Comet: Fraunhofer Institute for Applied Information Technology FIT
Iraklis Dimitriadis: Fraunhofer Institute for Applied Information Technology FIT
Christian Hopmann: Institute for Plastics Processing at RWTH Aachen University
Stefan Decker: Fraunhofer Institute for Applied Information Technology FIT

Journal of Intelligent Manufacturing, 2025, vol. 36, issue 6, No 1, 3669-3693

Abstract: Abstract One core concept of Industry 4.0 is establishing highly autonomous manufacturing environments. In the vision of Industry 4.0, the product leads its way autonomously through the shopfloor by communicating with the production assets. Therefore, a common vocabulary and an understanding of the domain’s structure are mandatory, so foundations in the form of knowledge bases that enable autonomous communication have to be present. Here, ontologies are applicable since they define all assets, their properties, and their interconnection of a specific domain in a standardized manner. Reusing and enlarging existing ontologies instead of building new ontologies facilitates cross-domain and cross-company communication. However, the demand for reusing or enlarging existing ontologies of the manufacturing domain is challenging as no comprehensive review of present manufacturing domain ontologies is available. In this contribution, we provide a holistic review of 65 manufacturing ontologies and their classification into different categories. Based on the results, we introduce a priority guideline and a framework to support engineers in finding and reusing existent ontologies of a specific subdomain in manufacturing. Furthermore, we present 16 supporting ontologies to be considered in the ontology development process and eight catalogs that contain ontologies and vocabulary services.

Keywords: Ontology; Manufacturing domain; Review; Knowledge engineering; Industry 4.0 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10845-024-02425-z

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