Skip to main content
×
Home
    • Aa
    • Aa

A framework for supporting multidisciplinary engineering design exploration and life-cycle design using underconstrained problem solving

  • XIU-TIAN YAN (a1) and HIROYUKI SAWADA (a2)
Abstract

The problem investigated in this research is that engineering design decision making can be complicated and made difficult by highly coupled design parameters and the vast number of design parameters. This complication often hinders the full exploration of a design solution space in order to generate optimal design solution. These hindrances result in inferior or unfit design solutions generated for a given design problem due to a lack of understanding of both the problem and the solution space. This research introduces a computational framework of a new algebraic constraint-based design approach aimed at providing a deeper understanding of the design problem and enabling the designers to gain insights to the dynamic solution space and the problem. This will enable designers to make informed decisions based on the insights derived from parameter relationships extracted. This paper also describes an enhanced understanding of an engineering design process as a constraint centered design. It argues that with more effort and appreciation of the benefits derived from this constraint-based design approach, engineering design can be advanced significantly by first generating a more quantitative product design specification and then using these quantitative statements as the basis for constraint-based rigorous design. The approach has been investigated in the context of whole product life-cycle design and multidisciplinary design, aiming to derive a generic constraint-based design approach that can cope with life-cycle design and different engineering disciplines. A prototype system has been implemented based on a constraint-based system architecture. The paper gives details of the constraint-based design process through illustrating a worked real design example. The successful application of the approach in two highly coupled engineering design problems and the evaluation undertaken by a group of experienced designers show that the approach does provide the designers with insights for better exploration, enabled by the algebraic constraint solver. The approach thus provides a significant step towards fuller scale constraint-based scientific design.

Copyright
Corresponding author
Reprint requests to: Xiu-Tian Yan, CAD Centre, Department of Design Manufacture & Engineering Management, University of Strathclyde, 75 Montrose Street, Glasgow G1 1XJ, Scotland. E-mail: x.yan@strath.ac.uk
Linked references
Hide All

This list contains references from the content that can be linked to their source. For a full set of references and notes please see the PDF or HTML where available.

Andreasen, M.M. (1991a). Design methodology,Journal of Engineering Design2(4), 321335.

Borg, J., Yan, X.T., & Juster, N.P. (2000). Exploring decision's influence on life-cycle performance to aid “design for multi-X.”Artificial Intelligence for Engineering Design, Analysis and Manufacturing14(2), 91113.

Bowen, J. & Bahler, D. (1992). Frames, quantification, perspectives, and negotiation in constraint networks for life-cycle engineering. Artificial Intelligence in Engineering7(2), 199226.

Gao, X., Lin, Q., & Zhang, G. (2006). A C-tree decomposition algorithm for 2D and 3D geometric constraint solving. Computer-Aided Design38(1), 113.

Lottaz, C., Stalker, R., & Smith, I. (1998). Constraint solving and preference activation for interactive design. Artificial Intelligence for Engineering Design, Analysis and Manufacturing12(1), 1327.

O'Sullivan, B. (2002). Interactive constraint-aided conceptual design. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 16(4), 303328.

Petrie, C., Webster, T.A., & Cutkosky, M.R. (1995). Using Pareto optimality to coordinate distributed agents. Artificial Intelligence for Engineering Design, Analysis and Manufacturing9(4), 269281.

Sawada, H. & Yan, X.T. (2004). Application of Gröbner bases and quantifier elimination for insightful engineering design. Mathematics and Computers in Simulation67(1–2), 135148.

Sitharam, M., Oung, J., Zhou, Y., & Arbree, A. (2006). Geometric constraints within feature hierarchies. Computer-Aided Design38(1), 2238.

Stumptner, M., Friedrich, G., & Haselbock, A. (1998). Generative constraint-based configuration of large technical systems. Artificial Intelligence for Engineering Design, Analysis and Manufacturing12(4), 307320.

Thornton, A.C. & Johnson, A. (1996). CADET: a software support tool for constraint processes in embodiment design. Research in Engineering Design8(1), 113.

Weispfenning, V. (1997). Quantifier elimination for real algebra—the quadratic case and beyond. Applicable Algebra in Engineering, Communication and Computing8(1), 85101.

Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

AI EDAM
  • ISSN: 0890-0604
  • EISSN: 1469-1760
  • URL: /core/journals/ai-edam
Please enter your name
Please enter a valid email address
Who would you like to send this to? *
×

Keywords:

Metrics

Full text views

Total number of HTML views: 1
Total number of PDF views: 7 *
Loading metrics...

Abstract views

Total abstract views: 66 *
Loading metrics...

* Views captured on Cambridge Core between September 2016 - 25th March 2017. This data will be updated every 24 hours.