The performance of a cyclone separator is often measured by grade-efficiency, which captures the efficiency of separating particles of a given feed size from the dusty gas stream. Accurate prediction of grade-efficiency has huge implications on design, safety, energy consumption, and environment. Based on comprehensive experimentation, this study exploits the best possible model to predict grade-efficiency and to conduct robust parameter design for minimizing the process variations. The grade-efficiency model via generalized linear mixed effects modeling (GLME) is identified to characterize grade-efficiency under uncertainties. The GLME modeling achieves 71.7% reduction compared to the ordinary linear model and 63% reduction compared to the beta regression model in prediction variability and therefore provides insights into the engineering design of the cyclone separator system through robust parameter design. (C) 2019 Elsevier B.V. All rights reserved.