Skip to main content
Log in

A decision support system for material and manufacturing process selection

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

Abstract

The material and manufacturing process selection problem is a multi-attribute decision-making problem. These decisions are made during the preliminary design stages in an environment characterized by imprecise and uncertain requirements, parameters, and relationships. Material and process selection decisions must occur before design for manufacturing can begin. This paper describes a prototype material and manufacturing process selection system called MAMPS that integrates a formal multi-attribute decision model with a relational database. The decision model enables the representation of the designer's preferences over the decision factors. A compatibility rating between the product profile requirements and the alternatives stored in the database for each decision criteria is generated using possibility theory. The vector of compatibility ratings are aggregated into a single rating of that alternative's compatibility. A ranked set of compatible material and manufacturing process alternatives is output by the system. This approach has advantages over existing systems that either do not have a decision module or are not integrated with a database.

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

Access this article

Subscribe and save

Springer+ Basic
¥17,985 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Japan)

Instant access to the full article PDF.

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  • Abel, C. A., Edwards, K. L. and Ashby, M. F. (1994) Materials, processing and the environment in engineering design: the issues. Materials and Design, 15(4), 179-193.

    Google Scholar 

  • Algeo, M. E. A. (1994) A state-of-the-art survey of methodologies for representing manufacturing process capabilities. NISTIR 5391, National Institute of Standards and Technology, Gaithersburg, MD.

    Google Scholar 

  • Ashby, M. F. (1992) Material Selection in Mechanical Design, Pergamon Press, Cambridge, UK.

    Google Scholar 

  • ASM International (1988) Engineered Materials Handbook, Volume 2: Engineering Plastics, ASM International, Metals Park, OH.

    Google Scholar 

  • Beiter, K., Krizan, S., Ishii, K. and Hornberger, L. (1991) Hy-perQ/Plastics: an expert system for plastic material selection. ASME Computers in Engineering, 1, 71-76.

    Google Scholar 

  • Boothroyd, G., Dewhurst, P. and Knight, W. A. (1992) Selection of materials and processes for component parts in Proceed-ings of the 1992 NSF Design and Manufacturing Systems Conference, Atlanta, GA, 8-10 January, pp. 255-263.

  • Chang, T. C. and Wysk, R. A. (1985) An Introduction to Auto-mated Process Planning Systems, Prentice-Hall, NJ.

    Google Scholar 

  • Dixon, J. R. and Poli, C. (1995) Engineering Design and Design for Manufacturing a Structured Approach, Field Stone Publishers, Conway, MA.

    Google Scholar 

  • Dubois, D. and Prade, H. (1988) Possibility Theory, Plenum Press, New York.

    Google Scholar 

  • Dubois, D., Fargier, H. and Prade, H. (1995) Fuzzy constraints in job-shop scheduling. Journal of Intelligent Manufacturing, 6, 215-234.

    Google Scholar 

  • Esawi, A. M. K. and Ashby, M. F. (1996) Systematic process selection in mechanical design in Proceedings of the 1996 ASME Design Engineering Technical Conference, Irvine, CA, 18-22 August, pp. 1-8.

  • Groover, M. P. (1996) Fundamentals of Modern Manufacturing, Prentice-Hall, Upper Saddle River, NJ.

    Google Scholar 

  • Ishii, K., Adler, R. and Barkan, P. (1988) Application of design compatibility analysis to simultaneous engineering. Artificial Intelligence in Design Analysis and Manufacturing, 2(1), 53-65.

    Google Scholar 

  • Jurrens, K. K., Fowler, J. E. and Algeo, M. E. A. (1995) Modeling of manufacturing resource information: requirements specification. NISTIR 5707, National Institute of Standards and Technology, Gaithersburg, MD.

    Google Scholar 

  • Kalpakjian, S. (1992) Manufacturing Engineering and Technology, 2nd edn, Addision-Wesley, Reading, MA.

    Google Scholar 

  • Klir, G. J. and Yuan, B. (1995) Fuzzy Sets and Fuzzy Logic, Prentice Hall, NJ.

    Google Scholar 

  • NIST (1997) NIST Design, Process Planning, and Assembly Repository, http://www. nist. gov/pptb/repository. html.

  • Otto, K. N. and Antonsson, E. K. (1994) Modeling imprecision in product design in 1994 IEEE International Conference on Fuzzy Systems, 1, pp. 346-351.

    Google Scholar 

  • Ullman, D. G. (1992) The Mechanical Design Process, McGraw Hill, New York.

    Google Scholar 

  • Waterman, N. A. and Ashby, M. F. (1991) Material Selector, Vol. 1, CRC Press, Boca Raton, FL.

    Google Scholar 

  • Whitney, D. E. (1988) Manufacturing by design. Harvard Business Review, 66(4), 83-91.

    Google Scholar 

  • Yager, R. R. (1977) Fuzzy decision-making including unequal objectives. Fuzzy Sets and Systems, 1, 87-95.

    Google Scholar 

  • Young, R. E., Giachetti, R. E. and Ress, D. (1996) Fuzzy constraint satisfaction in design and manufacturing in Proceed-ings of the Fifth IEEE International Conference on Fuzzy Systems, 2, pp. 1106-1112.

    Google Scholar 

  • Yu, J.-C., Krizan, S. and Ishii, K. (1993) Computer-aided design for manufacturing process selection, Journal of Intelligent Manufacturing, 4, 199-208.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Giachetti, R.E. A decision support system for material and manufacturing process selection. Journal of Intelligent Manufacturing 9, 265–276 (1998). https://doi.org/10.1023/A:1008866732609

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1008866732609

Navigation