Study Of Statistical Process Control Method And Application

Quality is very important for the enterprise. The traditional quality control is mainly dependent on manual inspection. Statistical process control is a technology using statistical methods to monitor the production process. This technique can monitor the production process and alarm. It is convenient to remind quality managers to take timely measures to improve. But traditional statistical process control theory is based on assumption that the quality characteristics data must be normally distributed. In this case, the traditional theory of process capability analysis will no longer apply for non-normal process. Based on this situation, this article describes the methods and steps of the non-normal process capability analysis and determines the distribution of data.The paper introduces the method of non-normal data stability-Mann-Whitney test and non-normal control charts. The article discusses several transmation ways for non-normal process capability. A way is using Johnson curve to describe non-normal process data. Another way is Box-Cox transformation methods. The paper also introduces clements’s method to calculate process capability for non-normal distributions and compares the above methods. The methods can solve non-normal phenomenon in the production process and perfect the statistical process control theory.Finally, the implementation of the project to verify the practicality of the SPC test methods. The project can improve the quality of the product stability, low product defect rates, and greatly reduce the labor intensity. The test method can solve real production problems. It is of great significance to ensure product quality.