Physical concept ontology for the knowledge intensive engineering framework

  • Authors:

  • Masaharu Yoshioka;Yasushi Umeda;Hideaki Takeda;Yoshiki Shimomura;Yutaka Nomaguchi;Tetsuo Tomiyama

  • Affiliations:

  • Hokkaido University, N14 W9, Kita-ku, Sapporo-shi, Hokkaido 060-0814, Japan;Tokyo Metropolitan University, Tokyo 192-0397, Japan;National Institute of Informatics, Tokyo 101-8430, Japan;The University of Tokyo, Tokyo 113-8654, Japan;Osaka University, Osaka 565-0871, Japan;Delft University of Technology, AA Delft 2600 The Netherlands

  • Venue:
  • Advanced Engineering Informatics
  • Year:
  • 2004

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Abstract

Knowledge intensive engineering aims at flexible applications of a variety of product life cycle knowledge, such as design, manufacturing, operations, maintenance, and recycling. Many engineering domain theories are organized and embedded within CAD and CAE tools and engineering activities can be formalized as modeling operations to them. Since most of domain theories deal with the physical world and can be associated with physical concepts, a physical concept ontology can form a common ontology to integrate engineering models that are formed based on domain theories. This paper reports a physical ontology-based support system for knowledge intensive engineering called Knowledge Intensive Engineering Framework (KIEF) to integrate multiple engineering models and to allow more flexible use of them. First, the paper describes the physical ontology as the core of KIEF and an ontology-based reasoning system, called a pluggable metamodel mechanism, to integrate and maintain relationships among these models. The pluggable metamodel mechanism uses a metamodel that represents the designer's mental model about a design object as a concept network model. The designer builds and decomposes a functional hierarchy from functional specifications with an FBS (Function-Behavior-State) modeler. He/She then maps the functional hierarchy into a metamodel using physical features that are building blocks for conceptual design. Then, the pluggable metamodel mechanism enriches the information contained in the metamodel by using causal dependency knowledge about the physical world and by building and analyzing various engineering models. We demonstrate the power of KIEF by illustrating a design case performed on KIEF.