Title: Value of information and experimentation in milling profit optimisation

Authors: R.E. Zapata-Ramos, T.L. Schmitz, M. Traverso, A. Abbas

Addresses: Machine Tool Research Center, Department of Mechanical and Aerospace Engineering, University of Florida, 237 MAE-B, Gainesville, FL 32611, USA. ' Machine Tool Research Center, Department of Mechanical and Aerospace Engineering, University of Florida, 237 MAE-B, Gainesville, FL 32611, USA. ' Department of Industrial and Enterprise Systems Engineering, University of Illinois at Urbana-Champaign, 8 Florida Drive, Urbana, IL 61801, USA. ' Information Systems and Decision Analysis Lab (ISDAL), Department of Industrial and Enterprise Systems Engineering, University of Illinois at Urbana-Champaign, 117 Transportation Building, MC-238, Urbana, IL 61801, USA

Abstract: This paper presents a decision-analytic approach to milling optimisation in the presence of uncertainty. The decisions include the milling parameter settings and the uncertainties include the probability of stability and tool life. We quantify the stability uncertainty by Monte Carlo simulation, where the force model coefficients and frequency response function uncertainties are propagated through the stability model. We treat tool life uncertainty using encoding. We then apply a single attribute objective function, expected profit, to determine optimal settings. Using this formulation, we determine the value of an experiment, the optimal experiment settings, and the value of perfect information.

Keywords: milling optimisation; decision analysis; stability lobe diagram; stability uncertainty; perfect information value; value of experiments; tool life; Monte Carlo simulation; force modelling; frequency response function.

DOI: 10.1504/IJMMS.2009.028082

International Journal of Mechatronics and Manufacturing Systems, 2009 Vol.2 No.5/6, pp.580 - 599

Published online: 03 Sep 2009 *

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