Master’s Programs & Curriculum
Please note: GRE is not required for both master and PhD Winter & Fall 2022 admissions
A master’s degree in Industrial and Operations Engineering enables students from quantitative disciplines, including engineering, science, economics, mathematics, and statistics, to align their interests to one or more focus areas offered by the department, or to personalize the selection of classes and projects from other departments, to match individual interests and career goals.
| BUSINESS OPERATIONS ENGINEERING
Learn about analytical approaches to production, storage, and distribution of goods and services from sources to customers. Develop the analytical skills needed for data-driven engineering of modern business operations and processes, including business-critical activities such as supply chain analytics, warehousing, distribution logistics, production operations, transportation systems, financial, and risk management.
Key Topics: Data-Driven Modeling, Enterprise Planning and Scheduling, Financial Engineering, Lean Thinking, Manufacturing and Service Facilities, Supply Chain Analytics, Service Operations
| DATA ANALYTICS & APPLIED STATISTICS
Learn the essential methods used to translate raw data into informed decisions for a wide range of industry applications. Develop the skills and knowledge to collect, manage, and analyze data to create mathematical and statistical models for inference, prediction, machine learning, and data-driven decision-making to improve the performance of complex systems.
Key Topics: Data-driven Optimization and Decision Making, Design of Experiments, Machine Learning, Predictive Modeling, Risk Analysis, Simulation, Uncertainty Quantification
| HEALTH & HUMAN SAFETY
Learn about key topics relevant to health and human safety that affect people’s lives, including the management of expensive resources in health systems, medical decisions, and the design of safe environments for people to live and work. Learn to harness data from electronic health records and use new technologies such as wearable sensors to improve health and safety. The U-M Center for Healthcare Engineering & Patient Safety offers additional opportunities for selected students to work in close partnership with the U-M Health System.
Key Topics: Applied Optimization, Data Analytics, Healthcare Operations, Medical Decision Making, Statistics, Stochastic Systems Modeling, Workplace Safety
| HUMAN SYSTEMS INTEGRATION
Learn to analyze and supporting the critical role humans (as operators, designers, developers, and regulators) play in optimizing performance, health, and safety in a wide range of sociotechnical systems. Develop the skills to evaluate human cognitive and physical abilities and limitations throughout the entire process of system design and development to achieve effective human-machine teaming, minimize errors and the risk of injury, illness or disability in the workplace. Application domains include transportation, healthcare, manufacturing and military applications where autonomous vehicles, robots and other technologies play an important role.
Key Topics: Biomechanics, Cognitive Ergonomics, Human-Robot Interaction, Occupational Safety, Physical Ergonomics, Robotics
| OPERATIONS RESEARCH & ANALYTICS
This area covers advanced methods for describing, predicting, and optimizing decision making to improve system performance. Discover how to leverage techniques at the intersection of math, statistics, and computation to build data-driven models fundamental to decision-making in many contexts. Apply mathematical and algorithmic techniques and principles to improve decision-making in a wide range of industries.
Key Topics: Algorithm Design, Computational Modeling, Decision Analysis, Optimization, Queueing Theory, Simulation, Stochastic Systems
| QUALITY CONTROL & RELIABILITY ENGINEERING
This area of study prepares you to apply data-driven modeling, simulation, quality control, and reliability techniques for making cost-effective quality improvement and maintenance decisions in the context of a broad range of service and manufacturing enterprises. Develop the skills to cope with uncertainty and variations in the design and operation of all types of engineering systems.
Key Topics: Design of Experiments, Fault Diagnosis, Process Control and Reliability, Prognostics Statistical Monitoring, Quality Control, Time Series Modeling.
Industry Project Opportunities and Research Experiences
Many IOE master’s students engage in projects through industry internships, team projects, or research experiences in faculty laboratories and research groups. These experiences help students develop the professional skills needed to successfully launch their career in industry or to progress to a PhD to further prepare for academic or industry research careers.