New Design of SPC Control Limit Setting Flow for Super Large Amount of Engineering Data

Abstract

SPC (Statistic Process Control) Control charts are widely used to establish and maintain statistical process control in many domains for process performance shift detection. But the assumption of process data distribution is a potential risk to cause unexpected alarm ratio when we use inadequate control limit setting method. In manufactory practice, we found many engineering data are not following normal distribution. So one by one to analyzes and data transmit is hard to execute in practice, special for large amount of engineering data in semiconductor manufactory. Therefore, in this paper we propose to use different control methods or control chart for the different data types. Basically, 4 types of data distribution are mainly focused: fix valued data (just only one constant value occurs in normality), discrete distribution, normal distribution and continuous non-normal distribution. We design to use data level counts and normal distribution test to split them base on some statistical methods. Depending on the result of classification, we assign the suitable quality control method or control chart type for each class. Of course, the false alarm rate is considered to balance all data types into comparable level.