Process Analytics Course 2025

 **Registration now open**

An IChemE accredited course

Introduction to Process Analytics using Multivariate Methods – Fundamentals     19 - 20 May 

Course participants will be introduced to modern day multivariate data analytics methods through lectures and hands-on workshops. The syllabus is geared towards general concepts on latent variable modelling (LVM) theory and advanced topics on the analysis of specific data scenarios (e.g. batch data, image analysis and chemometrics). LVM is a data-driven modelling technique particularly useful to understand processes where acquired data is: abundant, complex, correlated and noisy. Basic knowledge of statistics, linear algebra and geometry are helpful to fully understand the concepts of this course.

Day 1 Principal Components Analysis Fundamentals and common applications

• Conceptual, Geometric and statistical introduction to PCA
• Algorithms and objective functions
• Global diagnostics and contributions
• Outlier Detection
• Multivariate process monitoring
• Establishing multivariate specifications for materials
• Unsupervised clustering and classification

Day 2:  Partial Least Squares fundamentals and common applications

• Objective function and reduced rank regression
• Algorithms
• Parametric interpretation and model diagnostics
• Chemometrics  and soft sensors
• Multi-block methods

Advanced Applications of Process Analytics using Multivariate Methods      21 - 22 May 

Day 3 and Day 4 of the course will explore advanced applications of the Latent Variable Modelling (LVM). The syllabus is geared towards more advanced topics such as the analysis of batch data, process and product design, multivariate image and texture analysis and chemometrics. Knowledge of multivariate methods is required to fully understand the concepts covered in this course.

Day 3: Advanced Applications 

• Analysing dynamic data (Batch process analysis, monitoring and forecasting)
• Gentle introduction to Optimization Techniques using PYOMO
• Process condition design using PLS with optimization tools

Day 4: Advanced Applications

• In-silico formulation for new products
• Optimization Based Chemometrics
• Adaptive and localized modelling for soft sensors
• Varimax Rotations and Orthogonal PLS approaches
• Building Hybrid models with PLS in gPROMS

This course will be delivered by Dr Salvador Garcia-Munoz, Visiting Professor at Imperial College London, with 20+ years of experience in the implementation of systems engineering tools to industrial problems. He works for the pharmaceutical R&D sector leading the application of digital design tools for the development of new products and accelerated process design. He is an active member of AIChE, a founder of the Systems Based Pharmaceutics Alliance and associate editor for Chemical Engineering Research and Design. His research in multivariate modelling spans from industrial applications to the development of new methods and algorithms to analyse complex datasets common in contemporary industrial scenarios.