Workshop on Mechanical Engineering Design Knowledge Modeling; Washington, DC; 28 August 2011

Georgia Tech Research Corporation, Atlanta GA

Investigators

Abstract

The objective of this award will be to conduct a one day workshop with the aim of clearly defining a research program for capturing, representing, and modeling mechanical engineering design knowledge that the research, academic, and industrial community can pursue in both the near and long term. A formalized language of mechanical engineering is envisioned that will allow engineers to communicate more precisely between each other and with computers. The resulting formalized ME design knowledge and language will be encoded and implemented in an open-knowledge repository. Such a knowledge repository could capture the disparate and representationally diverse ME knowledge of typical undergraduate students providing numerous benefits, including: 1) a standard for ME knowledge; 2) a knowledge base to support engineering design; 3) a knowledge base for computer-aided tutoring systems; and 4) a key component of the ME research and education infrastructure. A convergence of artificial intelligence, engineering informatics, description logics, and the semantic web with mechanical engineering design research will be the enabling factor to realize the vision of this research proposal and workshop. If successful, the work may impact US economic and national security since a ME knowledge repository could increase the value of US graduates who have expertise beyond just the application of engineering science principles. Successful definition of a research agenda toward an ME knowledge repository has the potential for transformational outcomes. Increased awareness in the research community of high-impact research areas will increase interest in knowledge modeling. Establishing an ME knowledge repository as part of the educational infrastructure enables myriad methods and tools. The knowledge repository also has the potential to be a valuable resource for ME education research, as well as ME research in general. The networking function of the workshop will establish new relationships between individuals spanning widely across the field. This opportunity will provide a stimulus for new interactions and collaboration to advance the state of the art in engineering knowledge modeling. An understanding should emerge of the potential for this work to impact critical areas of engineering education, engineering information modeling, knowledge modeling, and the semantic web. The results will be disseminated through presentations, conference papers, and journal articles.