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OntoSTEP: Enriching Product Model Data Using Ontologies

Published

Author(s)

Raphael Barbau, Sylvere I. Krima, Xenia Fiorentini, Sudarsan Rachuri, Anantha Narayanan Narayanan, Sebti Foufou, Ram D. Sriram

Abstract

The representation and management of product lifecycle information is critical to the success of any manufacturing organization. Different modeling languages are adopted to represent different product information, for example EXPRESS for geometry as seen in STEP, and UML for beyond geometry information as defined in CPM. It is necessary to consolidate product information created using these different languages to create a coherent knowledge base. In this paper, we present a translation of from EXPRESS to OWL and that will enable translation of STEP schema defined in EXPRESS to OWL. This gives a semantically rich model, which we call OntoSTEP that can easily be integrated with OWL ontologies. Manufacturing systems today must deal with product life cycle information that goes beyond basic 3D geometry. In this paper, we combine the OntoSTEP with another ontology to add beyond geometry information, resulting in a new semantically enriched product model. A plug-in for Protege is developed to enable the beyond geometry information of the designed product to be included in the OntoSTEP representations. As additional benefits, reasoning, inference procedures, and queries can be performed on the enriched model. We describe the mapping rules for the translation from EXPRESS to OWL, and illustrate the benefits of OWL translation with an example. We will also describe how these mapping rules can be implemented through meta-model based model transformations.
Citation
IEEE Transactions on Knowledge and Data Engineering
Volume
Submitted for Publication, 8/2010

Keywords

product model data, ontostep, ontologies, product lifecycle

Citation

Barbau, R. , Krima, S. , Fiorentini, X. , Rachuri, S. , , A. , Foufou, S. and Sriram, R. (2010), OntoSTEP: Enriching Product Model Data Using Ontologies, IEEE Transactions on Knowledge and Data Engineering, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=906151 (Accessed March 28, 2024)
Created August 31, 2010, Updated February 19, 2017