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.
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.
 C. A. Fung,“Statistical Topics in Off-Line
Quality Control,”Ph.D.Thesis,University of Wisconsin—Madison,1986,p.167.
 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.
 Minitab, Inc., “Minitab User’s Guide 2: Data Analysis and Quality Tools—Release 12,” 1998.
 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.
 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.