Introduction to Multivariate Statistical Process Control

Type of course:

Digital learning, Lesson

Language:

Duration:

15 minutes

Workload:

2 hours

Proficiency:

Beginner

Target:

Professionals, Students

This nugget will guide the learner through the concept of Multivariate Statistical Process Control (or its abbreviation MSPC), its definition, and the elements that compose a complete framework of data-driven process monitoring. We will show the structure of data that can be used for MSPC, the possible data arrangements that users can encounter, and the linear models that represent the foundation of this type of data analytics. Interactive plots and concise explanations of the mathematical concepts will give the learner a solid summary of MSPC.

Learning outcomes

The learner will be able to explain the concept of statistical process control based on multiple process variables with different matrix arrangements
The learner will recognize the mapping between the models and the data for process control
The learner will identify a set of monitoring metrics for process control