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Research Papers

Problem Map: An Ontological Framework for a Computational Study of Problem Formulation in Engineering Design

[+] Author and Article Information
Mahmoud Dinar

Mechanical and Aerospace Engineering,
Arizona State University,
Tempe, AZ 85287
e-mail: mdinar@asu.edu

Andreea Danielescu

School of Computing, Informatics and
Decision Systems Engineering,
Arizona State University,
Tempe, AZ 85821

Christopher MacLellan

Human-Computer Interaction Institute,
Carnegie Mellon University,
Pittsburgh, PA 15124
e-mail: cmaclell@cs.cmu.edu

Jami J. Shah

Mechanical and Aerospace Engineering,
Arizona State University,
Tempe, AZ 85287
e-mail: jami.shah@asu.edu

Pat Langley

Department of Computer Science,
University of Auckland,
Private Bag 92019,
Auckland 1142, New Zealand
e-mail: patrick.w.langley@gmail.com

The term function was a reserved word in the ASP solver that we employed, thus fnction is used when representing predicates of functions.

Contributed by the Design Engineering Division of ASME for publication in the JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING. Manuscript received September 13, 2013; final manuscript received February 16, 2015; published online April 24, 2015. Editor: Bahram Ravani.

J. Comput. Inf. Sci. Eng 15(3), 031007 (Sep 01, 2015) (10 pages) Paper No: JCISE-13-1178; doi: 10.1115/1.4030076 History: Received September 13, 2013; Revised February 16, 2015; Online April 24, 2015

Studies of design cognition often face two challenges. One is a lack of formal cognitive models of design processes that have the appropriate granularity: fine enough to distinguish differences among individuals and coarse enough to detect patterns of similar actions. The other is the inadequacies in automating the recourse-intensive analyses of data collected from large samples of designers. To overcome these barriers, we have developed the problem map (P-maps) ontological framework. It can be used to explain design thinking through changes in state models that are represented in terms of requirements, functions, artifacts, behaviors, and issues. The different ways these entities can be combined, in addition to disjunctive relations and hierarchies, support detailed modeling and analysis of design problem formulation. A node–link representation of P-maps enables one to visualize how a designer formulates a problem or to compare how different designers formulate the same problem. Descriptive statistics and time series of entities provide more detailed comparisons. Answer set programming (ASP), a predicate logic formalism, is used to formalize and trace strategies that designers adopt. Data mining techniques (association rule and sequence mining) are used to search for patterns among large number of designers. Potential uses of P-maps are computer-assisted collection of large data sets for design research, development of a test for the problem formulation skill, and a tutoring system.

FIGURES IN THIS ARTICLE
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Copyright © 2015 by ASME
Topics: Design , Modeling
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References

Figures

Grahic Jump Location
Fig. 1

A part of a concept map used in formulating a design problem

Grahic Jump Location
Fig. 2

The entities and the relationships of the P-maps framework

Grahic Jump Location
Fig. 3

P-maps states representing changes in a designer’s problem formulation through time: (a) after 4 min and (b) after 8 min

Grahic Jump Location
Fig. 4

Differences in thinking about the problem; the designer on the top continuously adds requirements, functions, and artifacts, while the designer on the bottom focuses on behaviors (from Ref. [37])

Grahic Jump Location
Fig. 5

Comparison of box plots of the five entities for two designers (from Ref. [37])

Grahic Jump Location
Fig. 6

A comparison of iterations among different entity types for two designers

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