Statistical process control is commonly understood as an approach to optimizing production and service processes based on statistical techniques. Statistical process control (SPC) provides production teams with a consistent method of viewing and interpreting data to improve processes and identify and prevent production problems. SPC identifies instances of unnatural variation so that root causes can be assigned and corrected. Control charts are used by a variety of industries and agencies as a means to monitor and drive improvements in many types of processes. In many industries, the application of SQC has yielded major economic benefits. However, the use of SQC methods has been limited by the daunting and often tedious tasks of calculating samples and graphing data, especially for very large data sets.

In the wake of the end of PI Process Book support, many companies are facing migration to the new PI Vision. One problem is the absence of a popular and useful feature of the Process Books – the SPC/SQC Control. This is where the developed Control for PI Vision comes in. This enables you to use all the features of the SPC Control in the new environment. Furthermore, the Werusys PI Vision Suite provides you with many other controls for PI Vision. In connection with a statistical evaluation of a process, a box plot is of particular interest.

In Seeq, control charts and run control conditions can be created to monitor data in near real-time and flag when the data indicates abnormal or out-of-control behavior. The Werusys SPC Add-On for Seeq automates most of this task and allows users to efficiently and clearly monitor their process parameters. With the help of the Werusys PI Vision Suite, these analyses can be seamlessly integrated into PI Vision.