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| CURRENT
RESEARCH |
TEAM COORDINATION AND PERFORMANCE
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A primary factor contributing
to overall team performance is how effectively
and efficiently the team members can coordinate
individual effort and knowledge in order to
achieve the team’s goals. In this project
we propose using information processing theory
to develop a Team Coordination Model to simulate
and quantify team performance. The Team Coordination
Model will provide an a priori prediction
of the coordination load as a function of
the task structure and team composition. In
previous and ongoing research we have defined
the concept of coordination load as the amount
of effort required to coordinate all the work
activities and decision activities of a group
of people completing a task. If inadequate
or inappropriate coordination mechanisms (strategies
to coordinate the work of the group) are utilized
then team performance suffers. The Team Coordination
Model will provide recommendations as to the
most appropriate team composition and coordination
mechanisms to optimize team performance. Successful
completion of the project will demonstrate
that a simulation model can capture the dynamics
of a team and that coordination load can be
estimated before a team tackles a problem.
Extensions to the work include incorporation
of robot team members.
 FUNDING:
US Army Research Laboratory
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AN OPEN QUEUEING NETWORK MODEL TO ANALYZE BUSINESS
PROCESSES
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This research project is investigating
quantitative approaches to analyze the performance
of business processes. Important characteristics
of business processes is the need for coordination
among the activities and the learning and productivity
gains resulting from the division of labor.
In this research project we are incorporating
these two aspects into an analytical model
of business processes to evaluate various business
process reengineering heuristics. The model
is a multi-class open queueing network model
using the parameter-decomposition approximation
method. Included in the model is an approximation
for fork/join queues. A spreadsheet version
of the model has been implemented.
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PATIENT APPOINTMENT SCHEDULING
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Access to healthcare is one of the major
problems in healthcare industry in which many
patients are unable to receive timely healthcare.
Poor access has resulted in significant but
avoidable healthcare cost, poor quality of
healthcare service, and deterioration of general
public health. At the heart of the problem
is the appointment scheduling approach employed
in healthcare industries which results in heavy
appointment backlogs and consequently poor
access to healthcare. A promising and increasingly
popular patient scheduling policy called Advanced
Access leaves the majority of appointment slots
available for same-day demand. The performance
measures in Advanced Access are defined mathematically
and the scheduling policy is modeled in this
paper as a discrete stochastic optimization
problem. The model includes constraints to
provide minimum levels of access to healthcare
and continuity of care, two important measures
of healthcare outcomes. The model is analyzed
to derive bounds on the feasibility of providing
same-day access. Using numerical results, we
show the trade-offs between healthcare outcomes
and clinic profit. An important result shows
that high access can be provided while maintaining
high profits, indicating that Advanced Access
scheduling when well implemented is a good
scheduling policy for both patients and healthcare
providers. Advanced Access offsets the loss
of profit due to no-shows and cancellations
observed in the traditional appointment scheduling;
and by Advanced Access definition provides
timely and immediate which are the primary
motivating factors for clinics to implement
Advanced Access. We also show that by providing
higher access the growth of backlogs over the
time period is significantly low even when
demand is greater than the capacity.
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PATIENT APPOINTMENT
SCHEDULING
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Electronic products are built in a competitive
environment that demands constant miniaturization,
increased functionality of each new generation
of products, and compressed design cycles in
order to be the first to market with a new
product. We have investigated methods for improving
integration of the design to manufacturing
life-cycle of electronics products. Funded
by the US Army, we developed a printed circuit
board manufacturability evaluation system (PCBMES).
The PCBMES system lets designers evaluate cost,
first-pass process yield, and manufacturing
equipment constraints early in the design process.
There is a web-based and stand-alone system.
We have also studied approaches for simultaneously
optimizing PCB design decisions (such as component
location) with manufacturing optimization (assembly
time minimization).
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