Abstract
Engineering knowledge representation is an important step for creating applications that can automate product development in various problem domains. This article looks at enablers and obstacles for knowledge-based engineering (KBE) systems development. The key enabler envisioned is a well-established knowledge representation language supporting extendibility and interoperability for the concepts it describes. So far the transfer of knowledge within an organzation is seen highly dependent on in-house expertise and training routines. This paper proposes selection principles for knolwedge-based engineering framework implementation for organizations, which may want to preserve and learn from their dynamically evolving knowledge. These priniciples are based on extendibility and interoperability of models, tools and techniques used within a KBE system. Having these three elements extendable and interoperable can support systematic development of a KBE system along with its adaptation to new knowledge emerging in a dedicated problem domain. This can help organizations employing KBE systems to better manage their know-how in a longer run.
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