Purpose - The purpose of this paper is to investigate the economic-statistical design of EWMA charts with variable sampling intervals (VSIs) under non-normality to reduce the process production cycle cost and improve the statistical performance of control charts. The objective is to minimize the cost function by adjusting the control chart parameters which suffice for the statistical restriction. Design/methodology/approach - First, using the Burr distribution to approximate various non-normal distributions, the economic-statistical model of the VSI EWMA charts under non-normality can be developed. Further, the genetic algorithms will be used to search for the optimal values of parameters of the VSI EWMA charts under non-normality. Finally, a sensitivity analysis is carried out to investigate the effect of model parameters and statistical restriction on the solution of the economic-statistical design. Findings - The result of sensitivity analysis shows that a large lower bound of average time to signal when the process is in control increases the control limit coefficient, no model parameter significantly affects the short sampling intervals, and so on. Originality/value - The economic-statistical design method proposed in this paper can improve the statistical performance of economic design of control charts and the general idea can be applied to other VSI control charts.