Whether you study on-campus or in Manhattan, Industrial and Systems Engineering graduate courses
at Binghamton University offer unique, internationally recognized, transdisciplinary
learning and research experiences.
As an industrial and systems engineer, you'll study complex systems and look for simplifying
solutions across all environments and fields of study, including manufacturing, management,
health systems and social sciences.
Programs Offered
PhD in Industrial and Systems Engineering
MS in Industrial and Systems Engineering
MS in Industrial and Systems Engineering with Engineering Management concentration
MS in Industrial and Systems Engineering with Health Systems concentration
Basic concepts in probability and statistics required in the modeling of random
processes and uncertainty. Bayes' formula, Bayesian statistics, independent events;
random variables and their descriptive statistics; distribution functions; Bernoulli,
Binomial, Hypergeometric, Poisson, normal, exponential, gamma, Weibull and multinomial
distributions; Chebyshev's theorem; central limit theorem; joint distributions;
sampling distributions; point estimation; confidence intervals; student-t, x squared
and F distributions; hypothesis testing; contingency tables, goodness of fit, non-parametric
statistics, regression and correlation. Prerequisite: one year of calculus. Term offered
varies. 3 credits.
Levels: Graduate, Undergraduate
Global competition is serving as a catalyst for continuous process improvement
and the methodical enhancement of system-wide efficiencies. This is true in disciplines
ranging from the medical arena and service related systems to manufacturing. The underlying
science that contributes to the systematic analysis of complex enterprise-wide systems
is the focus of this course. Concepts that can be used in a synergistic manner to enhance
an enterprise's efficiency and profitability will be addressed. Prerequisite:
Graduate standing or permission of instructor. Term offered varies. 3 credits.
Levels: Graduate, Undergraduate
Stochastic processes, review of probability and statistics, covariance, input data
selection, random number generators, non-parametric tests for randomness, generation
of random variates, output data analysis, terminating and non-terminating simulations,
model validation, comparison of alternatives, variance reduction techniques, sensitivity
analysis, experimental design and predictive models. Prerequisite: SSIE 505 or equivalent.
Term offered varies. 3 credits.
Levels: Graduate, Undergraduate
Operations research (OR) is devoted to the determination of the best course of
action of a decision problem, given resource restrictions. Course provides the engineer
with a firm grounding in the use of OR (mathematical) techniques devoted to the modeling
and analysis of decision problems. Techniques include the following: decision modeling; linear, integer and dynamic
programming; emerging optimization techniques (e.g., genetic algorithms, simulated
annealing, etc.); game theory; and queueing theory. Problem areas include the following:
transportation models; project/production scheduling; inventory models; assignment
problems. Prerequisite: Graduate standing or permission of instructor. Term offered
varies. 3 credits.
Levels: Graduate, Undergraduate
Statistical quality control, designing for quality, process control, vendor and
customer quality issues, quality costs and production. Prerequisites: SSIE 505 or
permission of instructor. Offered in the Spring semester. 3 credits.
Levels: Graduate, Undergraduate
Thesis option:
4 electives (at least one at 600-level) plus 6 credits of thesis work followed by
oral presentation and defense.
Non-thesis option:
5 electives (at least one at 600-level) plus a project of at least 3 credits.
Coursework-only option:
10 courses (at least one at 600-level).
PhD in Industrial and Systems Engineering
Degree requirements include:
satisfaction of the learning contract, including proficiency in teaching and residence
requirements
pass a comprehensive exam
presentation of a colloquium on proposed research
acceptance of a prospectus outlining dissertation research
submission of a dissertation, and
defense of a dissertation at oral examination
Application Deadline
Admission to the program occurs on a rolling basis.