ChE 2026 Spring Seminar Series – L. Ricardez-Sandoval, PhD

Details

Speaker: L. Ricardez-Sandoval, PhD

Title: Deep Reinforcement Learning Strategies for Optimal Process Design, Scheduling and Control of Chemical Manufacturing Plants and Emerging Energy Systems

Abstract:
The integration of decision variables from process scheduling, process control and optimal integration of scheduling and control tasks are of interest since they may offer an opportunity to increase profits and enhance sustainability in chemical processing plants including advanced energy systems. Moreover, the growing number of sensory data, which can be collected and processed, is a major area of opportunity to approach these problems in real time. Nevertheless, a challenge to use this information for making decisions is the asynchronous way in which it is generated, i.e., the generation of information happens at a different time scale for different processes. Thus, there is a need for reactive (online) methods that can handle and use the generated data from the process to avoid infeasible decisions. Recently, the use of Deep Reinforcement Learning (DRL) algorithms has emerged as an attractive option to generate policies for decision-making processes. Despite the novel applications of machine learning in chemical engineering and advanced energy systems, the application of such tools to address problems in process scheduling, process control and optimal process integration is limited but it is gaining traction.
This talk will go over our recent efforts developed in our group to address problems emerging in process scheduling of batch plants, process control for emerging energy systems such as Chemical Looping Combustion (CLC), and the integration of design, scheduling and control decisions for chemical plants. The set of methods presented in this talk will illustrate the advantages and limitations of the incorporation of DRL as an alternative strategy to design online policies that can aid in the decision-making process during the design and operation of chemical plants and advanced energy systems.

Bio: Dr. L. Ricardez-Sandoval is a Professor in the Department of Chemical Engineering at the University of Waterloo (UW). Dr. Ricardez-Sandoval holds a Canada Research Chair (Tier II) in Multiscale Modelling and Process Systems and leads the development of methods for optimal design and operations management under uncertainty, the development of novel CO2 capture and conversion technologies aimed at reducing the carbon footprint, and computer-aided design of novel catalyst materials. Dr. Ricardez-Sandoval has published more than 235 journal articles, 80 full-length peer-reviewed conference papers, 5 book chapters and 1 book. Dr. Ricardez-Sandoval (h-index: 51) has 15 publications that each have been cited more than 100 times and has published numerous publications on optimal process integration, modelling and optimization of conventional and emerging CO2 capture technologies, atomistic and molecular design of novel catalyst materials for CO2 conversion, chemical looping combustion (CLC) technologies, and the implementation of machine learning (ML) methods for the optimal design and manufacture of nano-scale and macro-scale systems and materials. Dr. Ricardez-Sandoval‘s novel contributions in optimal process integration, multiscale modelling, process systems and CO2 capture and conversion technologies have been widely recognized by delivering multiple plenary and keynote talks at international conferences, leading the organization of top-tier conferences (e.g. International Program Chair: 2022 DYCOPS-CAB IFAC Symposium) and receiving multiple research-related awards, e.g., the 2024 D.G. Fisher Award sponsored by the Chemical Institute of Canada (CIC), the NSERC Discovery Accelerator Supplement (2017), and Ontario’s Early Researchers Award (2015). Dr. Ricardez-Sandoval serves as editor of Computers and Chemical Engineering, Digital Chemical Engineering and the Canadian Journal of Chemical Engineering. More information about Dr. Ricardez-Sandoval’s research activities can be found at the following links:

https://www.linkedin.com/in/luis-ricardez-sandoval-182b72298/

https://uwaterloo.ca/chemical-process-optimization-multiscale-modelling-process-systems/