Share This Article:

Application of Response Surfaces in Evaluating Tool Performance in Metalcutting

Abstract Full-Text HTML Download Download as PDF (Size:547KB) PP. 1333-1339
DOI: 10.4236/am.2013.49180    3,284 Downloads   4,908 Views   Citations

ABSTRACT

This paper advances the collection of statistical methods known as response surface methods as an effective experimental approach for describing and comparing the tool life performance capabilities of metalcutting tools. Example applications presented demonstrate the versatility of the power family of transformations considered by Box and Cox (1964) in modeling tool life behavior as revealed using simple response surface designs. A comparative analysis illustrates a method to gauge the statistical significance of differences in tool life estimates computed from response surface models. Routine use of these methods in experimental tool testing is supported by their ability to produce reliable relative performance representations of competing tools in field applications.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

M. Delozier, "Application of Response Surfaces in Evaluating Tool Performance in Metalcutting," Applied Mathematics, Vol. 4 No. 9, 2013, pp. 1333-1339. doi: 10.4236/am.2013.49180.

References

[1] C. A. Fung,“Statistical Topics in Off-Line Quality Control,”Ph.D.Thesis,University of Wisconsin—Madison,1986,p.167.
[2] P. Balakrishnan and M. F. DeVries, “Analysis of Mathematical Model Building Techniques Adaptable to Machinability Database Systems,” Eleventh North American Manufacturing Research Conference Proceedings, Society of Manufacturing Engineers, 1983, pp. 466-475.
[3] Minitab, Inc., “Minitab User’s Guide 2: Data Analysis and Quality Tools—Release 12,” 1998.
[4] D. M. Allen, “The Prediction Sum of Squares as a Criterion for Selecting Predictor Variables,” Technical Report Number 23, Department of Statistics, University of Kentucky, 1971.
[5] G. E. P. Box and D. R. Cox, “An Analysis of Transformations (with discussion),” Journal of the Royal Statistical Society, Series B, Vol. 26, 1964, pp. 211-252.

  
comments powered by Disqus

Copyright © 2018 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.