Industrial and Systems Engineering

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
• MS in Industrial and Systems Engineering: Executive Health Systems concentration in Manhattan

Selected Research Topics

Required Course Descriptions, Electives

Master's in Industrial and Systems Engineering

Students must complete four required courses while maintaining at least a B average. Students will choose between SSIE 553 and SSIE 561

• SSIE 505 - Applied Probability & Statist.

  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

• SSIE 510 - Enterprise Systems Engineering

  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

• SSIE 520 - Modeling And Simulation

  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

• SSIE 553 - Operations Research

  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

• SSIE 561 - Quality Assurance For Engineer

  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.