Applying grey forecasting method for fitting and predicting the performance characteristics of an electro-conductive ceramic (Al2O3+30%TiC) during electrical discharge machining

This paper presents a residual modified grey dynamic model RGM(1,3) in order to fit and predict the performance characteristics of an electro-conductive ceramic (Al₂O₃+30%TiC) during electrical discharge machining (EDM). Grey system theory is suitable for the system in which some information is poor, incomplete and uncertain, so it is feasible to study the performance characteristics of EDM with this model. The RGM(1,3) model is modified to promote the forecasting accuracy of predicting values using the residual grey dynamic model GM(1,1). The fitted and predicted values of various performance characteristics, including the material removal rate (MRR), maximum surface roughness (Rmax), and electrode wear ratio (EWR) agreed sufficiently with the experimental data. It is proved that RGM(1,3) model fitted and predicted the above performance characteristics with a high predicting accuracy. Therefore this procedure of grey forecasting model is relatively simple and convenient, and it is greatly suited for the analysis of question which obtained a few experimental data, and acts an auxiliary to calculate the unfinished experimental data.