Reliability-based NC milling parameters optimization using ensemble metamodel

In this paper, an ensemble metamodel trained by inherited latin hypercube design (ILHD) is introduced to model the effort of cutting speed and feed per tooth on the milled surface roughness and on the maximum milling force. ILHD using the initial design as inherited point is used to generate 16 combinations of milling parameters. Using these milling parameters, milling experiments are performed in Shanghai Fadal VMC4020C machining center. To further take the slight fluctuations of the milling speed and feed per tooth into consideration, the milling parameters optimization model is built by reliability-based methods. With this model, the optimal milling parameters are calculated using Monte Carlo simulation (MCS) and sequential approximation programming (SAP) algorithm. MCS is used here to conduct reliability analysis because of the nonlinear relationship between the maximum milling force and cutting parameters. Using the optimization results to perform milling verification experiments, the effectiveness of the proposed method is demonstrated, which obtains a smaller milled surface roughness with reliability satisfaction of maximum milling force.