Information
technology and mathematical optimization are of strategic importance to manufacturers
and service providers alike, as they can be used to improve their bottom line
by helping companies to cut lead-times, improve on-time delivery of orders,
reduce inventory, deliver customized products, and better coordinate with suppliers
and customers. With Dr.
Peter Luh as the Director, the Manufacturing Systems Laboratory at University
of Connecticut has been working extensively with industry, and is well known
for developing near-optimal and computationally efficient approaches for the
planning, scheduling, and coordination of design, manufacturing, and service
activities to improve inventory measures and the delivering of customized or
semi-customized products. The Laboratory has also developed near-optimal methods
for the planning, scheduling, load and price forecasting, and market participation
for power systems to maximize profit while managing risks. The facilities include
an Ethernet cluster of PCs within the lab, as well as systems of Pratt
& Whitney, Toshiba,
General Electric, Northeast
Utilities, Select Energy, Southern
California Edison, PLM, Sikorsky,
Delta, J. M. Products, Cannondale,
etc., as test beds for developing advanced optimization-based methods. Current
efforts include scheduling, inventory optimization, and coordination of overhaul
and repair networks; supply chain modeling, simulation, and analysis; demand
forecasting and optimization-based portfolio management; and the analysis and
optimization of auctions.
