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Tool-Life Testing by Response Surface Methodology Coupled with a Random Strategy Approach

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Proceedings of the Thirteenth International Machine Tool Design and Research Conference

Summary

The paper presents a study of tool-life testing combining response surface methodology with Monte Carlo random strategy so as to obtain improved predictions with a 95% confidence level for the life of a tool used in machining operations. The analysis is based on a second-order model in which the tool-life is expressed as a function of the three not entirely independent variables, namely, speed, feed and depth-of-cut. The results and the reliability of the new model are discussed and compared with results obtained using the surface response methodology approach only.

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References

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Author information

Authors and Affiliations

  1. Windsor University, Windsor, Ontario, Canada

    R. Vilenchich (Engineering)

  2. McMaster University, Hamilton, Ontario, Canada

    K. Strobele (Mechanical Engineering)

  3. de Beers Industrial Diamond Division, Johannesburg, South Africa

    R. Venter

Authors
  1. R. Vilenchich
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  2. K. Strobele
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  3. R. Venter
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Editor information

Editors and Affiliations

  1. Department of Mechanical Engineering, University of Birmingham, UK

    S. A. Tobias (Chance Professor and Head of Department) (Chance Professor and Head of Department)

  2. University of Manchester Institute of Science and Technology, UK

    F. Koenigsberger (Professor of Machine Tool Engineering) (Professor of Machine Tool Engineering)

Copyright information

© 1973 Macmillan Publishers Limited

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Cite this chapter

Vilenchich, R., Strobele, K., Venter, R. (1973). Tool-Life Testing by Response Surface Methodology Coupled with a Random Strategy Approach. In: Tobias, S.A., Koenigsberger, F. (eds) Proceedings of the Thirteenth International Machine Tool Design and Research Conference. Palgrave, London. https://doi.org/10.1007/978-1-349-01857-4_39

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  • DOI: https://doi.org/10.1007/978-1-349-01857-4_39

  • Publisher Name: Palgrave, London

  • Print ISBN: 978-1-349-01859-8

  • Online ISBN: 978-1-349-01857-4

  • eBook Packages: EngineeringEngineering (R0)

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