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research-article

Probabilistic Sequential Prediction of Cutting Forces using Kienzle models in Orthogonal Turning Process

[+] Author and Article Information
Mehdi Salehi

Institute for Information Management in Engineering, Karlsruhe Institute of Technology, Kaiserstr. 12, 76131, Karlsruhe, Germany; Institute of Materials and Processes, Karlsruhe University of Applied Science, Moltkestr.30, 76133, Karlsruhe, Germany
mehdi.salehi@hs-karlsruhe.de

Tony Schmitz

Department of Mechanical Engineering and Engineering Science, University of North Carolina at Charlotte, Charlotte, NC, USA
tony.schmitz@uncc.edu

Ryan Copenhaver

Department of Mechanical Engineering and Engineering Science, University of North Carolina at Charlotte, Charlotte, NC, USA
rcopenha@uncc.edu

Rüdiger Haas

Institute of Materials and Processes, Karlsruhe University of Applied Science, Moltkestr.30, 76133, Karlsruhe, Germany
ruediger.haas@hs-karlsruhe.de

Jivka Ovtcharova

Institute for Information Management in Engineering, Karlsruhe Institute of Technology, Kaiserstr. 12, 76131, Karlsruhe, Germany
jivka.ovtcharova@kit.edu

1Corresponding author.

ASME doi:10.1115/1.4041710 History: Received June 04, 2018; Revised October 04, 2018

Abstract

Probabilistic prediction of cutting forces is performed applying Bayesian inference to the Merchant and Kienzle force models. The models uncertainties are evaluated and minimized using the Metropolis-Hastings (MH) algorithm of the Markov Chain Monte Carlo (MCMC) approach. Prior probabilities are established and posteriors of the models parameters and force predictions are completed using the results of orthogonal turning experiments. Two types of tools with chamfer (rake) angles of 0 and -10 deg are tested under various cutting speed and feed per revolution values. The results of the probabilistic forces prediction are obtained and discussed for the 0 deg tool rake angle tool first. Second, the results of the posteriors of the Kienzle model parameters are used as prior probabilities of the -10 deg rake angle tool. Additionally, the simulation results are compared with the experiments which are obtained under other cutting conditions for model verification.

Copyright (c) 2018 by ASME
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