Dr. John F. MacGregor
Distinguished University Professor Emeritus
Department of Chemical Engineering
McMaster University
1280 Main Street West
Hamilton Ontario, Canada L8S 4L7
Email: macgreg@mcmaster.ca; john.macgregor@prosesnus.ca
B.Eng., McMaster University (1965)
M.Sc., University of Wisconsin (1967)
Ph.D. University of Wisconsin (1972)
FRSC, FCAE, FASA
Topics
Dr. MacGregor retired from McMaster University in 2008 and is currently a Professor Emeritus.
He is President of ProSensus Inc., a company spun out of MACC in 2004 (www.prosensus.ca).
He is therefore not accepting new graduate students, but is still very actively involved with
MACC and in collaborative research with other MACC faculty.
Research Interests
1)
Multivariate Statistical Methods
Massive amounts of process data are collected routinely by on-line process computers and
automated instrumentation. This area of research involves the development of multivariate
statistical methods to enable engineers, scientists, managers and operators to easily use
information extracted from these data in both off-line and real-time settings. The main
application areas being investigated are:
a) Real-time Monitoring, Control and Optimization of Processes: This area covers
methods for the on-line monitoring of continuous and batch processes and for the
advanced model predictive control over final product quality and yields in batch
processes.
b) Digital Imaging for On-line Monitoring and Control: This area covers the use of colour
and multi-spectral digital imaging for the on-line monitoring and control of processes and
product quality. This is a particularly important issue for industries making solid products
or slurries where instruments for measuring product properties on-line are not readily
available.
c) Rapid Development of New Products and Formulations: The development of new
products generally involves three degrees of freedom: (i) the selection of the best set of
raw materials; (ii) the formulation ratios in which to combine/react the materials; (iii) the
process conditions to use in manufacturing the product. This research involves
developing greatly improved multivariate modeling and optimization approaches to
enable such rapid develop novel products.
Selected Publications
C. Duchesne, J.J. Liu and J.F. MacGregor, “Multivariate Image Analysis in the Process
Industries: A Review”, Chemometrics & Intelligent laboratory Systems, 117, 116-128, 2012.
Z. Liu, M.J. Bruwer, J.J. MacGregor, S, Rathore, D.E. Reed, M.J, Champagne. “Modeling and
Optimization of a Tablet Manufacturing Line”, J. Pharmaceutical Innovation, 6, 170-180, 2011.
Garcia-Munoz, S., J.F. MacGregor, D. Neogi, B.E. Latshaw and S. Mehta, “Optimization of
batch operating policies. Part II: Incorporating process constraints and industrial applications”,
Ind. & Eng. Chem. Res., 47, 4202-4208, 2008
Bruwer, M.J., J.F. MacGregor and M.D. Noseworthy, “Dymanic Contrast-Enhanced MRI
Diagnostics in Oncology via Principal Component analysis”, J. Chemometrics, 22, 708-716,
2008.
Muteki, K., J.F. MacGregor and T. Ueda, “On the Rapid development of New Polymer Blends:
The optimal selection of materials and blend ratios”, Ind. & Eng. Chem. Res., 45, 4653-4660,
2006.
Flores-Cerrillo, J. and J.F. MacGregor, “Control of batch product quality by trajectory
manipulation using latent variable models”, J. Process Control, 14, 539-553, 2004.