6.1. In context

This section considers the important area of latent variable modelling. These models have been shown, about 20 to 30 years ago, to be very powerful tools in dealing with the very data that (chemical) engineers face frequently. Our main goal of this section is to show how one can extract value from these data. But we first introduce the concept of a latent variable, and specifically the principal component analysis (PCA) model: the cornerstone of all latent variable models. Then we consider different ways to use our databases for interesting applications such as troubleshooting, soft-sensors, process monitoring, and new product development.

6.1.1. What we will cover


6.2. References and readings

These readings cover a variety of topics in the area of latent variable methods: