Improved knowledge management through first-order logic in engineering design ontologies

  • Authors:

  • Paul Witherell;Sundar Krishnamurty;Ian r. Grosse;Jack c. Wileden

  • Affiliations:

  • Department of mechanical and industrial engineering, university of massachusetts, amherst, massachusetts, usa;Department of mechanical and industrial engineering, university of massachusetts, amherst, massachusetts, usa;Department of mechanical and industrial engineering, university of massachusetts, amherst, massachusetts, usa;Department of computer science, university of massachusetts, amherst, massachusetts, usa

  • Venue:
  • Artificial Intelligence for Engineering Design, Analysis and Manufacturing
  • Year:
  • 2010

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Abstract

This paper presents the use of first-order logic to improve upon currently employed engineering design knowledge management techniques. Specifically, this work uses description logic in unison with Horn logic, to not only guide the knowledge acquisition process but also to offer much needed support in decision making during the engineering design process in a distributed environment. The knowledge management methods introduced are highlighted by the ability to identify modeling knowledge inconsistencies through the recognition of model characteristic limitations, such as those imposed by model idealizations. The adopted implementation languages include the Semantic Web Rule Language, which enables Horn-like rules to be applied to an ontological knowledge base and the Semantic Web's native Web Ontology Language. As part of this work, an ontological tool, OPTEAM, was developed to capture key aspects of the design process through a set of design-related ontologies and to serve as an application platform for facilitating the engineering design process. The design, analysis, and optimization of a classical I-beam problem are presented as a test-bed case study to illustrate the capabilities of these ontologies in OPTEAM. A second, more extensive test-bed example based on an industry-supplied medical device design problem is also introduced. Results indicate that well-defined, networked relationships within an ontological knowledge base can ultimately lead to a refined design process, with guidance provided by the identification of infeasible solutions and the introduction of “best-case” alternatives. These case studies also show how the application of first-order logic to engineering design improves the knowledge acquisition, knowledge management, and knowledge validation processes.