Thomas Marlin, McMaster University
Chemical Engineering
Professor
Hamilton, Ontario
marlint@mcmaster.ca
Office:
(905) 525-9140 ext. 27125
Expert In
Bio/Research
Competitive pressures require today's process plants to be tightly integrated and to achieve consistently high yields, low energy consumption and excellent product quality. The overall objective of this research is the development of new real-time technology that enables plant personnel to satisf...
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Bio/Research
Competitive pressures require today's process plants to be tightly integrated and to achieve consistently high yields, low energy consumption and excellent product quality. The overall objective of this research is the development of new real-time technology that enables plant personnel to satisfy these ever-increasing demands. Particular emphasis is placed on the design, optimization, control, and monitoring of the integrated plant, not on individual units.
Considerable opportunity exists to optimize operating variables in existing process plants, but the analysis is challenging. New analysis procedures address the realistic environment of dynamic plants, noisy data and models with errors. The research concentrates on model updating, model formulation, optimization, and results analysis that are designed to function as an integrated, feedback system.
Operations optimization exists in a hierarchical decision-making system, so that the research must also address the proper structure and communication between these levels. The higher scheduling level considers longer-term issues and provides an operating window and goals(economics) to the optimizer. The lower, multivariable control level enforces the proper operating policy as disturbances enter the plant.
I collaborate with several Faculty members and 18 industrial sponsors in the McMaster Advanced Control Consortium (MACC). MACC fosters industrially relevant research in process systems engineering and provides a community of graduate students who share knowledge and experiences. Further information about MACC is available at the following website.
Click to Shrink <<
Considerable opportunity exists to optimize operating variables in existing process plants, but the analysis is challenging. New analysis procedures address the realistic environment of dynamic plants, noisy data and models with errors. The research concentrates on model updating, model formulation, optimization, and results analysis that are designed to function as an integrated, feedback system.
Operations optimization exists in a hierarchical decision-making system, so that the research must also address the proper structure and communication between these levels. The higher scheduling level considers longer-term issues and provides an operating window and goals(economics) to the optimizer. The lower, multivariable control level enforces the proper operating policy as disturbances enter the plant.
I collaborate with several Faculty members and 18 industrial sponsors in the McMaster Advanced Control Consortium (MACC). MACC fosters industrially relevant research in process systems engineering and provides a community of graduate students who share knowledge and experiences. Further information about MACC is available at the following website.
Click to Shrink <<