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A method to reduce ambiguities of qualitative reasoning for conceptual design applications

Published online by Cambridge University Press:  15 January 2013

Valentina D'Amelio ,
Magdalena K. Chmarra  and
Tetsuo Tomiyama
Valentina D'Amelio*
Affiliation:
Faculty of Mechanical, Maritime, and Materials Engineering, Department of Intelligent Mechanical Systems, Delft University of Technology, Delft, The Netherlands
Magdalena K. Chmarra
Affiliation:
Faculty of Mechanical, Maritime, and Materials Engineering, Department of Intelligent Mechanical Systems, Delft University of Technology, Delft, The Netherlands
Tetsuo Tomiyama
Affiliation:
Faculty of Mechanical, Maritime, and Materials Engineering, Department of Intelligent Mechanical Systems, Delft University of Technology, Delft, The Netherlands
*
Reprint requests to: Valentina D'Amelio, Faculty of Mechanical, Maritime, and Materials Engineering, Department of Intelligent Mechanical Systems, Delft University of Technology, Mekelweg 2, 2628 CD, Delft, The Netherlands. E-mail: [email protected]
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Abstract

Qualitative reasoning can generate ambiguous behaviors due to the lack of quantitative information. Despite many different research results focusing on ambiguities reduction, fundamentally it is impossible to totally remove ambiguities with only qualitative methods and to guarantee the consistency of results. This prevents the wide use of qualitative reasoning techniques in practical situations, particularly in conceptual design, where qualitative reasoning is considered intrinsically useful. To improve this situation, this paper initially investigates the origin of ambiguities in qualitative reasoning. Then it proposes a method based on intelligent interventions of the user who is able to detect ambiguities, to prioritize interventions on these ambiguities, and to reduce ambiguities based on the least commitment strategy. This interaction method breaks through the limit of qualitative reasoning in practical applications to conceptual design. The method was implemented as a new feature in a software tool called the Knowledge Intensive Engineering Framework in order to be tested and used for a printer design.

Keywords

Ambiguity ReductionConceptual DesignQualitative Process TheoryQualitative ReasoningUser Intervention
Type
Regular Articles
Information
AI EDAM , Volume 27 , Issue 1 , February 2013 , pp. 19 - 35
Copyright
Copyright © Cambridge University Press 2013

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