Statistics in polymer reaction engineering

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In this research program, statistical methods are used to analyse data and develop mathematical models of chemical processes in particular polymerization processes used to manufacture various plastics and engineering polymers.  These models can be used to design reactors and ancilliary equipment for a process, optimize new and exisiting processes and control processes to produce material to specification and prevent unsafe operating conditions.  The statistical aspects of the model development address the fundamental and important question of how to bring process data into the mathematical model in an optimal fashion.  In this work, relatively recent developments in the field of applied statistics involving Markov Chain Monte Carlo methods will be used to solve the problems mentioned above.  This has the potential to lead to a general, flexible regression framework and software package.  This will significantly improve the ability of practicing engineers and scientists to correctly conduct regression analysis thereby efficiently extracting information from process models.