Enterprise Modeling: Supply Chain Design to
Statistical Performance Analysis
Organizers: Bonnie Ray
(borayx@m.njit.edu)
New Jersey Institute of Technology
and
Leslie M. Moore
(lmoore@lanl.gov)
Los Alamos National Laboratory

 

Description:
The term enterprise model is used to describe the characterization of logistic relationships related to the flow of products and information between suppliers, manufacturers, distributors, buyers and their customers. The increasing use of computer simulation methods for modeling the supply chain of an enterprise has led to the need for statistical methods that can be used to understand such complex, interrelated systems. This session will focus on the interface between effective supply chain design and quantitative methods used to assess the effect of different policies and procedures within the supply chain.

Format:
The session will consist of three presentations, followed by a guided discussion. The first talk will be given by an industrial engineer and will provide an introduction to supply chain design. The other two talks will focus on particular elements of supply chain analysis where statistical methods can be of use, such as in improving demand forecasting, designing experiments for large simulations, and analyzing complex simulation output. A poster session will be coordinated to highlight related research problems.

Participants:
Charu Chandra (presentation, Systems Thinking in Supply Chain Management)
Charu Chandra is an Assistant Professor in Industrial and Manufacturing Systems Engineering at the University of Michigan, Dearborn, Michigan and has a concurrent appointment as a Faculty Researcher at the Technology Modeling and Analysis Group of Los Alamos National Laboratory. Prior to this, Charu was a Post Doctoral Fellow at Los Alamos National Laboratory and at the University of Minnesota. He has worked in the industry as Information Technology Manager and Systems Analyst. He is involved in research in Supply Chain Management, and in designing a complex Supply Chain for a leading industrial sector. Specifically, his research focuses on studying complex systems with the aim of developing cooperative models to represent coordination and integration in an enterprise. He teaches courses in Information Technology, Operations Research and Supply Chain Management. His Master and Ph.D. degrees are in Industrial Engineering and Operations Research from the University of Minnesota, and Arizona State University, respectively.

Leslie M. Moore Los Alamos National Laboratory; Bonnie Ray, New Jersey Institute of Technology; and Dennis R. Powell, Los Alamos National Laboratory (presentation, Planning Experiments with Computer Models of Complex Phenomena)
Leslie Moore is a Technical Staff Member in the Statistical Sciences Group at Los Alamos National Laboratory. She holds a B.S. in Mathematics and a Ph.D. in Mathematics, concentration in Statistics, from the University of Texas at Austin. Her research interests include experiment design, including the design and analysis of computer experiments, generalized linear mixed models, and statistical intervals.

Bonnie Ray (presentation, Forecasting Methods for Supply Chain Management)
Bonnie Ray is an Associate Professor in the Dept. of Mathematical Sciences at the New Jersey Institute of Technology and is currently a research affiliate with the Statistical Sciences group at Los Alamos National Laboratory. She holds a Ph.D. in Statistics from Columbia University and a B.S. in Mathematics from Baylor University. Her research interests include time series analysis, statistical computing, and statistical graphics.

Max Morris (discussant)
Max Morris received his Ph.D. in statistics from VPI&SU, has held faculty positions at the University of Texas Health Sciences Center in San Antonio and Mississippi State University, and was a member of the scientific staff of Oak Ridge National Laboratory for 18 years. He is currently Professor of Statistics at Iowa State University, and holds a joint appointment in the ISU Department of Industrial and Manufacturing Systems Engineering. He is a Fellow of the American Statistical Association, was editor of Technometrics from 1996-1998, and has been editorial statistical consultant for Radiation Research for several years.