Reliability-based EDM process parameter optimization using kriging model and sequential sampling

Abstract

Electrical discharge machining (EDM) is an effective method to process micro-hole for electrically conductive materials regardless of the hardness. However, the machining accuracy and cost are greatly affected by EDM parameters, which are of slight fluctuations in actual machining process. In view of this, reliability-based design optimization (RBDO) method is introduced to balance the electrode wear and aperture gap when unavoidable uncertainties are considered. Kriging model trained by inherited Latin hypercube design (ILHD) and expected feasibility function with objective function (OEFF) criterion is applied to model the influences of peak current, pulse on time and pulse off time on electrode wear and aperture gap. By calling the Kriging model, the probability and corresponding gradient of aperture gap less than the requirement are calculated using Monte Carlo simulation (MCS) and the EDM process parameters are optimized using sequential approximation programming (SAP) algorithm. Using the optimal EDM parameters to perform verification experiments, the feasibility of proposed method is demonstrated, where smaller electrode wear as low as 174.2 m is obtained with the reliability satisfaction ( =3.02) of aperture gap.