Research Papers

An Ontology for Reusable and Executable Decision Templates

[+] Author and Article Information
Zhenjun Ming

School of Mechanical Engineering,
Beijing Institute of Technology,
No. 5 Zhongguancun South Street,
Haidian District, Beijing 100081, China
e-mail: zhenjun.ming@bit.edu.cn

Guoxin Wang

Associate Professor
School of Mechanical Engineering,
Institute for Industrial Engineering,
Beijing Institute of Technology,
No. 5 Zhongguancun South Street,
Haidian District, Beijing 100081, China
e-mail: wangguoxin@bit.edu.cn

Yan Yan

School of Mechanical Engineering,
Beijing Institute of Technology,
No. 5 Zhongguancun South Street,
Haidian District, Beijing 100081, China
e-mail: yanyan331@bit.edu.cn

Joseph Dal Santo

School of Aerospace and Mechanical Engineering,
University of Oklahoma,
202 W. Boyd Street, Suite. 219,
Norman, OK 73019
e-mail: jjdalsanto96@ou.edu

Janet K. Allen

Fellow ASME
School of Industrial and Systems Engineering,
University of Oklahoma,
202 W. Boyd Street, Suite. 116,
Norman, OK 73019
e-mail: janet.allen@ou.edu

Farrokh Mistree

Fellow ASME
School of Aerospace and Mechanical Engineering,
University of Oklahoma,
865 Asp Avenue, Felgar Hall, Room No. 306,
Norman, OK 73019
e-mail: farrokh.mistree@ou.edu

1Corresponding author.

Contributed by the Computers and Information Division of ASME for publication in the JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING. Manuscript received June 12, 2016; final manuscript received July 28, 2016; published online February 16, 2017. Editor: Bahram Ravani.

J. Comput. Inf. Sci. Eng 17(3), 031008 (Feb 16, 2017) (13 pages) Paper No: JCISE-16-1985; doi: 10.1115/1.4034436 History: Received June 12, 2016; Revised July 28, 2016

Engineering design is increasingly recognized as a decision making process. Providing decision support is crucial to augment designers' decision-making capability in this process. In this paper, we present a template-based ontological method that integrates the decision-making mechanism with problem-specific information; thus, it can provide design decision support from both the “construct” and the “information” perspectives. The “construct,” namely, decision-making mechanism, is the utility-based Decision Support Problem (u-sDSP), which is a rigorous mathematical model that facilitates designers making multi-attribute selection decisions under uncertainty, while the information for decision making is archived as u-sDSP templates and represented using frame-based ontology to facilitate reuse, execution, and consistency-maintaining. This paper is an extension of our earlier work on the ontological modeling of the compromise decisions. The unique advantage of this ontology is that it captures both the declarative and procedural knowledge of selection decisions and represents them separately, thus facilitating designers reusing, executing previous documented decision knowledge to effect new decisions. The efficacy of ontology is demonstrated using a rapid prototyping (RP) resource selection example.

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Hazelrigg, G. A. , 1998, “ A Framework for Decision-Based Engineering Design,” ASME J. Mech. Design., 120(4), pp. 653–658. [CrossRef]
Lewis, K. E. , Chen, W. , and Schmidt, L. C. , 2006, Decision Making in Engineering Design, ASME Press, New York.
Mistree, F. , Smith, W. , Bras, B. , Allen, J. , and Muster, D. , 1990, “ Decision-Based Design: A Contemporary Paradigm for Ship Design,” Trans. Soc. Nav. Archit. Mar. Eng., 98, pp. 565–597.
Thurston, D. L. , 1991, “ A Formal Method for Subjective Design Evaluation with Multiple Attributes,” Res. Eng. Des., 3(2), pp. 105–122. [CrossRef]
Fernandez, M. G. , Seepersad, C. C. , Rosen, D. W. , Allen, J. K. , and Mistree, F. , 2005, “ Decision Support in Concurrent Engineering—The Utility-Based Selection Decision Support Problem,” Concurrent Eng-Res A, 13(1), pp. 13–27. [CrossRef]
Kulok, M. , and Lewis, K. , 2007, “ A Method to Ensure Preference Consistency in Multi-Attribute Selection Decisions,” ASME J. Mech. Des., 129(10), pp. 1002–1011. [CrossRef]
Resende, C. B. , Heckmann, C. G. , and Michalek, J. J. , 2012, “ Robust Design for Profit Maximization With Aversion to Downside Risk From Parametric Uncertainty in Consumer Choice Models,” ASME J. Mech. Des., 134(10), p. 100901. [CrossRef]
Gu, X. Y. , Renaud, J. E. , Ashe, L. M. , Batill, S. M. , Budhiraja, A. S. , and Krajewski, L. J. , 2002, “ Decision-Based Collaborative Optimization,” ASME J. Mech. Des., 124(1), pp. 1–13. [CrossRef]
Lewis, K. , and Mistree, F. , 1998, “ Collaborative, Sequential, and Isolated Decisions in Design,” ASME J. Mech. Des., 120(4), pp. 643–652. [CrossRef]
Muster, D. , and Mistree, F. , 1988, “ The Decision Support Problem Technique in Engineering Design,” Int. J. Appl. Eng. Educ., 4(1), pp. 23–33.
Pahl, G. , Pahl, G. , Wallace, K. , and Blessing, L. T. M. , 2007, Engineering Design: A Systematic Approach, Springer, London.
Gruber, T. R. , 1993, “ A Translation Approach to Portable Ontology Specifications,” Knowl. Acquis., 5(2), pp. 199–220. [CrossRef]
Li, Z. , Raskin, V. , and Ramani, K. , 2008, “ Developing Engineering Ontology for Information Retrieval,” ASME J. Comput. Inf. Sci. Eng., 8(1), p. 011003. [CrossRef]
Liu, Y. , Lim, S. C. J. , and Lee, W. B. , 2013, “ Product Family Design Through Ontology-Based Faceted Component Analysis, Selection, and Optimization,” ASME J. Mech. Des., 135(8), p. 081007. [CrossRef]
Rockwell, J. , Grosse, I . R. , Krishnamurty, S. , and Wileden, J. C. , 2009, “ A Decision Support Ontology for Collaborative Decision Making in Engineering Design,” IEEE Collaborative Technologies and Systems, May 18–22.
Rockwell, J. A. , Witherell, P. , Fernandes, R. , Grosse, I. , Krishnamurty, S. , and Wileden, J. , 2008, “ A Web-Based Environment for Documentation and Sharing of Engineering Design Knowledge,” ASME Paper No. DETC2008-50086.
Witherell, P. , Krishnamurty, S. , and Grosse, I . R. , 2007, “ Ontologies for Supporting Engineering Design Optimization,” ASME J. Comput. Inf. Sci. Eng., 7(2), pp. 141–150. [CrossRef]
Ming, Z. , Yan, Y. , Wang, G. , Panchal, J. , Goh, C. H. , Allen, J. K. , and Mistree, F. , 2015, “ Ontology-Based Executable Design Decision Template,” ASME Paper No. DETC2015-46272.
Mistree, F. , Smith, W. , Kamal, S. , and Bras, B. , 1991, “ Designing Decisions: Axioms, Models and Marine Applications,” Fourth International Marine Systems Design Conference, pp. 1–24.
Ming, Z. , Yan, Y. , Wang, G. , Panchal, J. H. , Goh, C. H. , Allen, J. K. , and Mistree, F. , 2016, “ Ontology-Based Executable Design Decision Template Representation and Reuse,” Artif. Intell. Eng. Des. Anal. Manuf., 30, pp. 391–406. (in press). [CrossRef]
Mistree, F. , Lewis, K. , and Stonis, L. , 1994, “ Selection in the Conceptual Design of Aircraft,” AIAA J., pp. 1153–1166.
Von Neumann, J. , and Morgenstern, O. , 1947, Theory of Games and Economic Behavior, Princeton University Press, Princeton, NJ.
Bascaran, E. , Bannerot, R. B. , and Mistree, F. , 1989, “ Hierarchical Selection Decision Support Problems in Conceptual Design,” Eng. Optim., 14(3), pp. 207–238. [CrossRef]
Flaschner, A. B. , 1997, “ Creating Innovative Products Using Total Design: The Living Legacy of Stuart Pugh - Clausing, D., Andrade, R.,” J. Prod. Innovat. Manag., 14(3), pp. 233–235.
Saaty, T. L. , 1980, The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation, McGraw-Hill International Book, New York.
Hazelrigg, G. A. , 2003, “ Validation of Engineering Design Alternative Selection Methods,” Eng. Optim., 35(2), pp. 103–120. [CrossRef]
Yang, D. , Dong, M. , and Miao, R. , 2008, “ Development of a Product Configuration System With an Ontology-Based Approach,” Comput. Aided Des., 40(8), pp. 863–878. [CrossRef]
Lu, W. L. , Qin, Y. C. , Liu, X. J. , Huang, M. F. , Zhou, L. P. , and Jiang, X. Q. , 2015, “ Enriching the Semantics of Variational Geometric Constraint Data With Ontology,” Comput. Aided Des., 63, pp. 72–85. [CrossRef]
Barbau, R. , Krima, S. , Rachuri, S. , Narayanan, A. , Fiorentini, X. , Foufou, S. , and Sriram, R. D. , 2012, “ OntoSTEP: Enriching Product Model Data Using Ontologies,” Comput. Aided Des., 44(6), pp. 575–590. [CrossRef]
Li, L. , Qin, F. , Gao, S. , and Liu, Y. , 2014, “ An Approach for Design Rationale Retrieval Using Ontology-Aided Indexing,” J. Eng. Des., 25(7–9), pp. 259–279. [CrossRef]
Li, L. , Qin, F. , Gao, S. , and Qin, X. , 2014, “ Ontology-Based Design Rationale Retrieval Supporting Natural Language Query,” ASME Paper No. DETC2014-34350.
Rockwell, J. A. , Grosse, I. R. , Krishnamurty, S. , and Wileden, J. C. , 2010, “ A Semantic Information Model for Capturing and Communicating Design Decisions,” ASME J. Comput. Inf. Sci. Eng., 10(3), p. 031008. [CrossRef]
Chang, X. M. , Rai, R. , and Terpenny, J. , 2010, “ Development and Utilization of Ontologies in Design for Manufacturing,” ASME J. Mech. Des., 132(2), p. 021009. [CrossRef]
Sivaloganathan, S. , and Shahin, T. , 1999, “ Design Reuse: An Overview,” Proc. Inst. Mech. Eng. Part B, 213(7), pp. 641–654. [CrossRef]
Panchal, J. H. , Fernández, M. G. , Paredis, C. J. J. , and Mistree, F. , 2004, “ Reusable Design Processes Via Modular, Executable, Decision-Centric Templates,” AIAA Paper No. 2004-4601.
Keeney, R. L. , and Raiffa, H. , 1976, Decisions With Multiple Objectives: Preferences and Value Tradeoffs, Wiley, New York.
Wang, H. , Noy, N. , Rector, A. , Musen, M. , Redmond, T. , Rubin, D. , Tu, S. , Tudorache, T. , Drummond, N. , and Horridge, M. , 2006, “ Frames and OWL Side by Side,” 9th International Protege Conference, Stanford, CA, July 24–26, p. 54.
Sandia, 2013, “Jess,” Sandia National Laboratories, Livemore, CA, accessed July 28, 2016, http://herzberg.ca.sandia.gov/
Stanford University, 2013, “ Protégé 3.5 Release,” Stanford University, Standford, CA, accessed July 28, 2016, http://protegewiki.stanford.edu/wiki/Protege_3.5_Release_Notes
Eriksson, H., 2008, “ Jess Tab,” Dept. of Computer and Information Science, Linköping University, Linköping, Sweden, accessed July 28, 2016, http://www.jessrules.com/jesswiki/view?JessTab


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Fig. 4

Individual utility function construction

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Fig. 3

The u-sDSP template

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Fig. 2

Summary of the steps of the utility-based selection decision problem

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Fig. 1

Word formulation of the u-sDSP

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Fig. 5

Multi-attribute utility function construction

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Fig. 6

Expected utility calculation

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Fig. 8

Overview of the complete structure for the u-sDSP template ontology

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Fig. 9

Screen shot of the RP resource selection Instance in Protégé ontology editor

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Fig. 7

Postsolution sensitivity analysis

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Fig. 12

Adjusting the original Instance when new attributes are introduced

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Fig. 10

Light switch cover plate assembly

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Fig. 11

Modifying the original Instance when new alternatives are introduced

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Fig. 13

Instantiation of the postsolution sensitivity analysis




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