A knowledge-based semantic tool for standard part management in aerospace industry

Abstract

Manufacture-based high-tech industries such as automotive and aerospace essentially pay attention to reducing costs and improving the quality of their products. In this context, assembly of products is one prominent part of finalizing the product. During the assembly, finding the most suitable standard parts1 that combines one or more bodies of assembly to form the final product is the common task for design engineers. Quite a few relational standard part databases can be found on the market, however none of them properly address the design needs. While querying relational databases, results are mostly vague or irrelevant, hence it requires domain experience about the features of parts. On the other hand semantic search [1] by the help of graphic model, it is possible to navigate and access all standard parts on graph; it returns relevant results as usual. In this paper, we propose semantic based search engine for inquiring standard parts from the repository. In our approach, we model and store Standard Part data on a commercial RDF (Resource Description Framework) Database [2]. We used OWLIM [3] to store data on database and we created an intelligent search engine, which discover link relations on RDF data. Our prototype system is still being developed in collaboration with the TOBB University. Final product will be used in Turkish Aerospace Industries (TAI)2 to resolve their critical problems.