Abstract : Workflows and supply chains can be monitored for execution effectiveness, in a statistical process control sense. In both cases one can model entities with attributes moving through a network, with entity-specific stochastic sojourn times and routing probabilities. Special characteristics include i) dealing with censored data and ii) exploiting the network structure. This talk describes a framework for monitoring such systems for ‘out-of-control’ signals. This work is joint with Jun Shu and Akhil Kumar.

Biography : Russell Barton is Distinguished Professor of Supply Chain and Information Systems in the Smeal College of Business at Penn State and holds a courtesy appointment in the Department of Industrial and Manufacturing Engineering. From 2013-2018 he served as Senior Associate Dean for Research and Faculty.  In 2017-18 he was Vice President, INFORMS Sections and Societies. From 2010-2012 he was Program Director for Service Enterprise Systems and Manufacturing Enterprise Systems at the U.S. National Science Foundation. He has a B.S. in electrical engineering from Princeton University, and M.S. and Ph.D. degrees in operations research from Cornell University. He is a Fellow of IISE, a Certified Analytics Professional®, and Senior Member of IEEE. His research has focused on the interface between applied statistics, simulation of manufacturing and service processes, and product design and manufacturing.