SEMINAR: Special MPO seminar, Tue 11/2, 3:00, MSC 343

[ikamenkovich@rsmas.miami.edu]

Tue, November 2, 3pm ? 4pm
MSC 343
Title: Integrated Decision Making using Dynamic-Data-Driven Adaptive
Simulations (DDDAS)

Speaker: Nurcin Celik

------------------------------

Integrated Decision Making using Dynamic-Data-Driven Adaptive Simulations
(DDDAS)
In simulation-based planning, timely monitoring, analysis, and control is
important not to disrupt
a dynamically changing system such as supply chains, and distributed power
systems. To meet
this temporal requirement, a Dynamic-Data-Driven Adaptive Simulation
(DDDAS) paradigm is
proposed in this study, where the fidelity of a complex simulation model
adapts to available
computational resources by incorporating dynamic data into the executing
model, which then
steers the measurement process for selective data update. To this end,
comprehensive system
architecture and methodologies are first proposed, where the components
include a real-time
simulation, grid modules, a web service communication server, databases,
various sensors, and a
real system. Abnormality detection, fidelity selection, fidelity
assignment, and prediction and
task generation are enabled through the embedded algorithms developed in
this work. Grid
computing is used for computational resources management and web services
are used for interoperable
communications among distributed software components. The proposed DDDAS
system has been successfully demonstrated for preventive maintenance
scheduling and part
routing scheduling in a semiconductor supply chain, reducing the average
waiting time of
batches and increasing the machine utilization significantly. Current
research focuses on
application of the proposed framework for load dispatching problem in
distributed electricity
systems.
*Supported in part by research grants from the National Science Foundation.


NURCIN CELIK, Ph.D., is an assistant professor in the Department of
Industrial Engineering at
the University of Miami. She received her B.S. degree in Industrial
Engineering from Bogazici
University and M.S. and Ph.D. degrees in Systems and Industrial
Engineering from the
University of Arizona. Her research interests lie in the areas of
integrated modeling and decision
making for large-scale, complex and dynamic systems such as supply chains
and distributed
electricity grids. Her dissertation work is on architectural design and
application of dynamic
data-driven adaptive simulations for distributed systems. She has received
several awards
including IIE Outstanding Graduate Research Award (2009), the Best Ph.D.
scientific poster
award in the Ph.D. Colloquium at IERC (2009), the University of Arizona
Outstanding Graduate
Student Award (2008, 2010), and Diversity in Science and Engineering Award
from Women in
Science and Engineering Program (2007).




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