Research on improvement of non-normally distributed data SPC control chart

Statistical process control (SPC) is the use of statistical technology to monitor the parameters of each process in the production process, so as to achieve the purpose of improving production line efficiency and ensuring product quality. But the parameter data of traditional SPC method need to obey the normal distribution. For data that do not obey the normal distribution, the application results of the conventional SPC method will have certain errors, and often produce false positives. A method using data conversion technology can solve this problem well. However, in the traditional non-normally distributed SPC method, the×- R control chart is only sensitive to large deviation data, and it is slow to respond to non-normally distributed and small deviation data, which makes the non-normally distributed SPC method use efficiency. A data improvement method based on the association model can make up for this shortcoming of the non-normally distributed SPC method and further improve the use efficiency of the non-normally distributed SPC method.