Milling Optimization of Accuracy and Removal Rate Under Uncertainty

Milling provides an efficient method for accurate discrete part fabrication. However, successful implementation requires the selection of appropriate operating parameters. Balancing the multiple process requirements, including high material removal rate, maximum part accuracy, chatter avoidance, and adequate surface finish, to arrive at an optimum solution is difficult without the aid of an optimization framework. In this work a robust optimization algorithm that accounts for the inherent process uncertainty and surface location error sensitivity is developed. Two optimization criteria are considered, namely, surface location error and material removal rate under the stability constraint. The trade off curve of surface location error versus material removal rate is calculated for the mean values of input parameters, as well as for a confidence level in the stability boundary. The validity of the optimization algorithm is established by comparison to experiment.