Summary
PhD. Chemical Engineering (McMaster University, Canada).
MS. Chemical Engineering (Monterrey Tech, Mexico)
BS. Chemical and Computer Systems Engineering ( Monterrey Tech, Mexico)
NEW - Process Analytics using multivariate methods - May 20 to May 23 2024
Description of the course:
The 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 Multivariate Data Analysis (MVDA) using methods like PCA and PLS. The agenda includes theory and applications on a variety of scenarios (e.g. continuous and batch processes, chemometrics). MVDA is a data-driven modeling technique particularly useful to understand systems 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.
The course includes various hands-on workshops using data from real applications, using Python tools.
2024 Course offerings
"Introduction to Process Analytics using Multivariate Methods " - May 20 and 21 2024
Day 1: Principal Components Analysis Fundamentals and common applications
- 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" - MAY 22 - 23 2024
Day 3 – Batch analysis and optimization based solutions
- Batch process analysis and monitoring
- Introduction to optimization using PYOMO
- Process and product design using PLS with optimization tools
- In-silico formulation of new formulated products (blending optimization)
Day 4
- Optimization Based Chemometrics
- NEW ! - Handling of missing samples
- Adaptive and localized modeling
- NEW! - Building hybrid models with PLS
Registration Fee applies (discounts available for CPSE Consortium companies, students and researchers )
For inquiries regarding the detailed agenda or to register please email:
sargent.centre@imperial.ac.uk
Publications
Journals
Odgers J, Kappatou C, Misener R, et al., 2023, Probabilistic predictions for partial least squares using bootstrap, Aiche Journal, Vol:69, ISSN:0001-1541, Pages:1-16
Wehbe M, Haslam AJ, Garcia-Munoz S, et al., 2023, Thermodynamic modelling of the nature of speciation and phase behaviour of binary and ternary mixtures of formaldehyde, water and methanol, Molecular Physics, ISSN:0026-8976
Nascu I, Diangelakis NA, Munoz SG, et al., 2023, Advanced model predictive control strategies for evaporation processes in the pharmaceutical industries, Computers & Chemical Engineering, Vol:173, ISSN:0098-1354
Kappatou C, Odgers J, García-Muñoz S, et al., 2023, An optimization approach coupling pre-processing with model regression for enhanced chemometrics, Industrial and Engineering Chemistry Research, Vol:62, ISSN:0888-5885, Pages:6196-6213
Zhao F, Ochoa MP, Grossmann IE, et al., 2022, Novel formulations of flexibility index and design centering for design space definition, Computers & Chemical Engineering, Vol:166, ISSN:0098-1354