The advance of new sensing technologies, such as the 3-D laser scanning, creates a data-rich environment for quality control in modern industries. The free-form surfaces of complex manufactured parts can be quickly scanned, producing thousands of data points. To monitor these large-scale surface scanning data, three major challenges have to be solved simultaneously: 1) simple parametric models are no longer sufficient to describe free-form surfaces; 2) the massive data points need fast computations; and 3) the presence of outliers calls for robust analytics. To fulfill this task, this paper proposes a novel monitoring scheme where the control chart is designed based on a new robust bilateral kernel smoothing method. A fast approximation algorithm is also developed for efficient online monitoring. This fast and robust nonparametric control chart shows significant superiority for surface monitoring in our numerical simulations. Finally, a real case study demonstrates the effectiveness of our proposed scheme in monitoring the stability of a 3-D printing process.