Speakers
Dr
Mattia Vallerio
(Solvay SA)
Francisco Navarro
(Imperial College)
Description
Typically, machine learning (ML) and artificial intelligence (AI) applications tend to focus on examples that are not relevant to process engineers.
In this talk, industrial data science fundamentals will be explained and linked with commonly-known examples in process engineering, followed by two common industrial applications using state-of-art ML techniques.
First, will discuss what open-source packages can be used to connect to industrial historians (Aspentech IP.21 and OSIsoft PI). Then we will cover AutoML and ExplainableAI Python packages that are commonly used in industry. Among them, We will show how Predictor Explainer (JMP+Python) automates the screening of process variables both for continuous and batch process data.
| Classification | Both methodology and application |
|---|---|
| Keywords | continuous data, batch data, industry, open-source |
Primary authors
Dr
Mattia Vallerio
(Solvay SA)
Dr
Carlos Perez-Galvan
(Solvay SA)
Francisco Navarro
(Imperial College)