Along with the development of various engineering technologies, the recent manufacturing technology and statistical quality control technology have made much progress. Statistical quality management technology is being researched to maintain and manage the quality of parts per million (PPM) level to satisfy the needs of customers. Among them, control chart is a technique to monitor the variation of various quality parameters. In particular, the defective rate control chart for monitoring fraction of nonconforming has a problem in that too many samples are required when fraction of nonconforming decreases to the PPM level. To solve this problem, there are various methods such as acceptance control chart, but it also has a limitation that it can be used only when the quality parameter is normally distributed. In this paper, we propose a method to manage the minimum defect rate of PPM level in the process where the quality parameter has non-normal distribution characteristics. First, we apply the Z_P statistic that can represent the minimum defect rate with a small number of samples. Also, Burr_ZP distribution is suggested by using Burr distribution that can fit most single-probability distribution. And Burr_ZP distribution is used to show the performance of Burr_ZP control chart using 3 sigma control chart method.