CAPTURING, SHARING, AND DISCOVERING PRODUCT DATA AT A SEMANTIC LEVEL - MOVING FORWARD TO THE SEMANTIC WEB FOR ADVANCING THE ENGINEERING PRODUCT DESIGN PROCESS
MetadataShow full item record
Along with the greater productivity that CAD automation provides nowadays, the product data of engineering applications needs to be shared and managed efficiently to gain a competitive edge for the engineering product design. However, exchanging and sharing the heterogeneous product data is still challenging. This dissertation first presents a detailed exploration on semantic strategies based on ontology models for integrating product data between multiple engineering applications, including two typical CAD applications in Product Design Domain, and one CAE application in Assembly Simulation Domain. It is concluded that the semantic approach is superior for exchanging and sharing heterogeneous product data at a semantic level. Further, this dissertation postulates an approach to introduce reasoning capability into the engineering ontologies in product assembly domain to truly exploit this logic-based and formal representation for product data. A layered architecture for semantic applications containing reasoning units is proposed. Retrieval specifications and inference rules in SWRL/SQWRL are defined in these reasoning units. It is concluded that the reasoning mechanism extends the semantic representation made possible through the ontology and holds promise for improving design knowledge understanding and discovery. Finally, based on research achievements on ontology modeling and reasoning, this dissertation presents an online Product Design Semantic Knowledge Management System (PD-SKMS) for presenting, querying/reasoning, and authoring/updating product data semantics by incorporating Semantic Web technologies. The Product Semantic Repositories (PSR) in a Host Hybrid-Data Repository (HDR) preserves product data semantics for the product assembly domain. A Semantic Data Management Engine (SDME) provides querying/reasoning and authoring/updating services on PSRs. By linking to public linked data, the capability of PD-SKMS is extended to external data sources. It is concluded that the PD-SKMS delivers an interactive and knowledge-contextual design environment for the engineers on the Web and it greatly improves the traditional behaviors for exchanging and sharing product design knowledge. In summary, this dissertation proposes, discusses, and implements semantic approaches to support design activities for capturing, sharing, and discovering product data semantics in a knowledge-contextual environment. Several practical scenarios successfully demonstrate the proposed approaches and reveal the great potential of semantic approaches for advancing the traditional engineering product design process.