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The Study of a Knowledge-Based Constraints Network System (KCNS) for Concurrent Engineering

  • Wei-ming Wang
  • Jie Hu
  • Fei Zhou
  • Da-yong Li
  • Xiang-jun Fu
  • Ying-hong Peng
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3930)

Abstract

This research article demonstrates the use of a constraints network for modeling the knowledge which is necessary for concurrent product design. A Knowledge-based Constraints Network System (KCNS) has been developed to maintain design consistency and to support the selection of appropriate design parameter intervals. A data-mining algorithm named fuzzy-rough algorithm is developed to acquire the knowledge level constraints from the numerical simulation. The method integrated Case Based Reasoning (CBR) and Rule Based Reasoning (RBR) with interval consistency algorithm is adopted to predict the potential conflicts and to specify the interval of design parameters. The design example of a crank connecting link in a V6 engine shows the validity of the system.

Keywords

Linguistic Term Case Base Reasoning Constraint Network Rule Base Reasoning Implicit Constraint 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Wei-ming Wang
    • 1
  • Jie Hu
    • 1
  • Fei Zhou
    • 1
  • Da-yong Li
    • 1
  • Xiang-jun Fu
    • 1
  • Ying-hong Peng
    • 1
  1. 1.School of Mechanical EngineeringShanghai Jiao Tong UniversityShanghaiP.R. China

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