Skip to main content
Log in

Feature sequencing in the rapid design system using a genetic algorithm

  • Published:
Journal of Intelligent Manufacturing Aims and scope Submit manuscript

This paper addresses the feature sequencing problem in the Rapid Design System (RDS). The RDS is a feature-based design system that integrates product design and process planning. An important issue in feature-based process planning for machined parts is the order in which material is removed to form the resultant part. The order, or sequence, is partially dependent on the geometric relationships between features. The sequence affects the safety, the time it takes to machine the part, and the quality of the finished part. The sequence of material removal depends on two types of relations between features: (1) intersections and (2) interfeature associations. Both types of relations compound the search for an ‘optimal’ sequence of material removal. Therefore, the research problem has been the discovery and development of a genetic algorithm (GA) that efficiently searches the solution space for all possible sequences and identifies the best sequences in terms of safety, time and quality.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Chang, T. C. (1990)Expert Process Planning for Manufacturing, Addison-Wesley, Reading, MA.

    Google Scholar 

  • Chen, C. L. P. and LeClair, S. R. (1994) An integration of design and manufacturing: solving setup generation and feature sequencing using an unsupervised learning approach.Computer Aided Design,26 (1).

  • Davis, L. and Steenstrup, A. (1987)Genetic Algorithms and Simulated Annealing, Morgan-Kaufmann, San Mateo, CA, pp. 4–11.

    Google Scholar 

  • Goldberg, E. D. (1989)Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, Reading, MA.

    Google Scholar 

  • Hayes, C. (1990) Machining planning: a model of an expert level planning process, PhD Dissertation, Carnegie-Mellon University.

  • LeClair, S. R. (1991) The Rapid Design System: memory-driven feature-based design, inProceedings of the 1991 IEEE Conference of Systems Engineering, Dayton, OH, August.

  • Lester, I. (1993) Simulated annealing: practice versus theory.Statistics and Computing.

  • Pao, Y. H. (1989)Adaptive Pattern Recognition and Neural Networks, Addison-Wesley, Reading, MA.

    Google Scholar 

  • Westhoven, T. E., Chen, C. L. P., LeClair, S. R. and Pao, Y.-H. (1991) Episodal associative memory approach for sequencing interactive features in process planning.Artificial Intelligence in Engineering, Design Analysis, and Manufacturing (AIEDAM),6(4), 177–197.

    Google Scholar 

  • Whitley, D. (1988) GENITOR: a different genetic algorithm, inProceedings of the Rocky Mountain Conference on Artificial Intelligence, Denver, CO.

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kamhawi, H.N., Leclair, S.R. & Chen, C.L.P. Feature sequencing in the rapid design system using a genetic algorithm. J Intell Manuf 7, 55–67 (1996). https://doi.org/10.1007/BF00114138

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF00114138

Keywords

Navigation