Satisfied surface topography is important to achieve the function of a part, thereby machined surface prediction is essential. A surface forecasting model called space-time multioutput support vector regression (STMSVR) is developed in this paper. With machined surfaces pervading in manufacturing, high definition metrology (HDM) is adopted to measure the three dimensional machined surface. Millions of data points are generated to represent the entire surface. The STMSVR model captures the spatial-temporal characteristics of the successively machined surface and predicts the future surface. To verify the prediction accuracy of STMSVR, a case study on the engine cylinder block face milling process is applied. The results indicate that the developed model achieves a good agreement between the predicted surface and the real surface using four important indexes.

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