Title: Milling optimisation of removal rate and accuracy with uncertainty: Part 2: parameter variation

Authors: Mohammad H. Kurdi, Tony L. Schmitz, Raphael T. Haftka, Brian P. Mann

Addresses: Mechanical and Aerospace Engineering Department, University of Florida, Gainesville, FL 32611, USA. ' Mechanical and Aerospace Engineering Department, University of Florida, Gainesville, FL 32611, USA. ' Mechanical and Aerospace Engineering Department, University of Florida, Gainesville, FL 32611, USA. ' Mechanical and Aerospace Engineering Department, University of Missouri, Columbia, MO 65211, USA

Abstract: Milling models provide tools for estimating stability and surface location error. Existing models are deterministic, though inherent variations in the model inputs propagate to uncertainty in the model outputs. In this paper the experimental procedures used to estimate the model parameters are presented. The effect of correlation between parameters is addressed. The variability of the stability boundary and surface location errors are determined using Latin Hypercube sampling. It is seen that including the correlation between parameters reduced the output variability by as much as 55% with a minimum reduction of 10%. Comparisons between mean model predictions and experimental results are provided.

Keywords: milling optimisation; multi-objective optimisation; sensitivity; Pareto; uncertainty; correlation; stability; parameter variation; modelling; spindle speed; axial depth; material removal rate; MRR; surface location error; optimal design.

DOI: 10.1504/IJMPT.2009.025211

International Journal of Materials and Product Technology, 2009 Vol.35 No.1/2, pp.26 - 46

Available online: 16 May 2009 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article