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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Mechatronics and Manufacturing Systems
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
