A fixture design system using case-based reasoning

Shu Huang Sun, Jahau Lewis Chen

Research output: Contribution to journalArticlepeer-review

40 Citations (Scopus)


An intelligent fixture design system based on case-based reasoning (CBR) is proposed in this paper. The system, instead of saving knowledge in a rule-like form, saves experience as cases. This system retrieves the most similar case from the antecedent cases when it faces a new problem, and modifies the case to satisfy the new situation. This new solution is then stored in the case base after the new problem has been solved, and can be employed again the next time a similar situation arises. Function features are applied in the modification stage to represent the function of each part. Those parts of which the functions are unsatisfactory would be modified to fit the new problem. This fixture design system is expected to possess two characteristics. First, the design system becomes more intelligent than the traditional CAD system; it participates in complete design work rather than just printing the design. Second, the system can itself learn from every consultation, and it becomes more experienced; not only is the learning ability emphasized in this system, but also it will become the most meaningful part of a future CAD system.

Original languageEnglish
Pages (from-to)533-540
Number of pages8
JournalEngineering Applications of Artificial Intelligence
Issue number5
Publication statusPublished - 1996 Oct

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering


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