Manufacturing-driven Design of Sculptured Surfaces

  • Ahmad Barari
  • Hoda ElMaraghy
Part of the Springer Series in Advanced Manufacturing book series (SSAM)


Designers in every industry from automotive, aerospace and telecommunications to medical equipments and biomedical artifacts strive to enhance the product design efficiency in order to cope with changing demands, while delivering higher quality products with shorter lead time and for less cost. Effective integration of the product design and process planning can improve manufacturability and maximize satisfaction of the designer’s intent. This paper presents a Design For Machining (DFM) tool that enables designers to the estimate effect of the design decisions on the accuracy of the machined product, particularly those containing sculptured surfaces. Actual variations of machined features can be predicted using the proposed analytical method. The comparison of these variations with the nominal allocated tolerances identifies critical portions of the design where unacceptable deviations may occur after machining. Constraints may be imposed on the design space to take into consideration the manufacturing limitations, increase parts acceptance and reduce scrap and rework. The designers can use these results to guide or drive the product design either by changing the design geometry or by modifying the specified design tolerances. The developed method is applicable to any geometry and is particularly useful and efficient for designing accurate sculptured surfaces. A sculptured surface auto-part is used for illustration.


design for manufacturing tolerance allocation machining errors 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

43.7 References

  1. [1]
    Boothroyd, G., 1994, “Product Design for Manufacture and Assembly,” Computer Aided Design, Vol. 26, pp. 505–515.CrossRefGoogle Scholar
  2. [2]
    Vliet, J.W., and Luttervelt, C.A., 1999, “State-of-the-Art Report on Design for Manufacturing,” 4 th Design for Manufacturing Conf., ASME Design Engineering Tech. Conf., 1999, Las Vegas, Nevada; DETC99-DFM-8970.Google Scholar
  3. [3]
    Boothroyd, G., Dewhurst, P., and Kinght, W., 2002, Product Design for Manufacture and Assembly, Second Edition, N. Y.: Marcel Dekker Inc.Google Scholar
  4. [4]
    Bralla, J.G., 1986, Handbook of Prod. Design for Manuf., McGraw-Hill.Google Scholar
  5. [5]
    Gupta, S.K., Regli, W.C., Das, D., and Nau, D.S., 1995, Automated Manufacturability Analysis: A Survey, ISR-TR-95-14, NIST, IR 5713 Carnegie Mellon University.Google Scholar
  6. [6]
    Barari, A., and Arezo, B., 1997, “A Feature Recognition Approach for CNC Milling of 2 1/2 parts,” Proc. of 3 rd Iranian Conf. on Manufacture Engineering, Amirkabir Univ. of Tech., Tehran, Iran, pp. 111–121.Google Scholar
  7. [7]
    Gadalla, M.A., and ElMaraghy, W.H., 1997, “Tolerancing of Free Form Surfaces,” 5 th CIRP Int. Seminar on Computer Aided Tolerancing, 1997, Toronto, ONGoogle Scholar
  8. [8]
    Nassef, A.O., and ElMaraghy, H.A., 1997, “Allocation of Geometric Tolerances: New Criterion and Methodology,” CIRP Annals 1997, Vol. 46/1, pp. 101–106.CrossRefGoogle Scholar
  9. [9]
    Nassef, A.O., and ElMaraghy H.A., 1995, “Statistical Analysis and Optimal Allocation of Geometric Tolerances,” Proc. of the Computers in Engineering Conf. and the Engineering Database Symposium, ASME 1995, pp. 817–823.Google Scholar
  10. [10]
    Ji, S., Li, X., Cai, M., and Cai, H., 2000, “Optimal Tolerance Allocation Based on Fuzzy Comprehensive Evaluation and Genetic Algorithm,” Int. Journal of Advanced Manufacturing Technology, Vol. 16, pp. 461–468.CrossRefGoogle Scholar
  11. [11]
    Barari, A., ElMaraghy, H.A., Knopf, G.K., and Orban, P., 2004, “Integrated Inspection and Machining Approach to Machining Error Compensation; Advantages and Limitations,” Proc. of Flexible Automation & Intelligent Manufacturing (FAIM) 2004, Toronto, Canada, pp. 563–572.Google Scholar
  12. [12]
    Hocken, R.J., 1980, “Technology of Machine Tools. Machine Tool Accuracy,” UCRL —52960-5, Lawrence Livermore Laboratory, University of California, Vol. 5.Google Scholar
  13. [13]
    ElMaraghy, H.A., Barari, A., and Knopf, G.K., 2004, “Integrated Inspection and Machining for Maximum Conformance to Design Tolerances,” CIRP Annals-Manufacturing Technology 2004. Vol. 53/1, pp. 411–416.Google Scholar

Copyright information

© Springer-Verlag London Limited 2006

Authors and Affiliations

  • Ahmad Barari
    • 1
  • Hoda ElMaraghy
    • 1
  1. 1.Intelligent Manufacturing Systems (IMS) Centre, Faculty of EngineeringUniversity of WindsorWindsorCanada

Personalised recommendations