Affiliation:
1. Engineering Design, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Martensstr. 9, 91058 Erlangen, Germany
Abstract
The transformation of virtual product development to Digital Engineering (DE) requires the successful integration of Digital Engineering or data-driven methods into existing product development processes. Those methods allow for the analysis and usage of existing data. However, missing knowledge about these methods, as well as their performance or limitations, is a major burden for their application, especially in small and medium-sized enterprises. In order to close this gap, this paper proposes the AI4PD ontology, linking product development processes (PD) and Digital Engineering methods (AI). This knowledge representation gives companies an overview of the available methods to support them in selecting a suitable solution for their problems. The representation of AI4PD is performed in Protégé using the W3C standard OWL syntax. The opportunities of AI4PD are shown by a use case of identifying a DE-Method for predicting manufacturing possibilities based on test data and CAD files. Furthermore, after possible problems in existing product development processes are identified, AI4PD covers the necessary knowledge for a successful method of identification and integration to transform virtual product development to Digital Engineering.
Funder
Bayerische Forschungsstiftung
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Cited by
4 articles.
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