Adaptive control for multistage machining process scenario—bar turning with varying material properties

Abstract

This paper discusses the multistage manufacturing scenario in context of progressive machining and demonstrates an adaptive control scheme for turning operation of a partially hardened bar. A nonlinear mechanistic force model-based control framework attempts to control the cutting force at a designated set point, with material properties changing over the cut. The force coefficients for the material are calculated offline using experimental data and Bayesian inference methods. Since the hardened part of the bar will shift the force coefficient values, an online estimation strategy (Bayesian recursive least square estimator) is used to learn the new coefficients as well as satisfying the control objective. With the newly learned coefficients passed downstream, the subsequent operation experiences no compromise of control objective as well as reduces the maximum values of force encountered. Numerical analyses presented show the adaptation and control scheme performance. Finally, the experimental analysis show the open-loop and closed-loop model adaptation and effective force set point regulation using experimental apparatus and partially hardened MS (AISI1045) bar.