Planning and Operations Engineering (3)
and operations models are used in a wide variety of applications. This course
focuses on developing problem formulations that are appropriate for the
situation at hand. The course will use a number of applications from
industrial, mechanical, civil and electrical engineering, financial
optimization models, health care systems, environmental ecology, and forestry.
The problems will span many types of solution methods, such as linear programming,
integer programming, quadratic assignment problem, nonlinear convex problems, and
black-box models. Multicriteria optimization will be discussed, and how to
incorporate randomness into optimization models, such as chance-constraint
programming and scenario-based stochastic programming.
Engineering Decision Making under Uncertainty (3)
This course is intended for first-year graduate students
with the objective of teaching them how to account for sources of short- and
long-term uncertainties in design, operation, and planning of engineering
systems; engineering applications in energy, transportation, and production
systems; the use of software packages for problem solving will be
emphasized. Two parts will be included: Part I deals with basics of probability
and stochastic processes, and Part II deals with risk and decision making under
Data Analytics in Engineering Systems (3)
Application of data analytics tools to the design and
improvement of engineering systems including semiconductor manufacturing,
energy systems, transportation systems, and others. Database access,
descriptive analytics, signal processing, classification, predictive analytics,
regression, and clustering analysis.
Deterministic Models in Industrial Engineering (3)
Deterministic models of operations research. Linear programming, the simplex method, duality, and dynamic programming.
Prerequisite: 16:540:501 or 14:540:311 (undergraduate introduction to operations research).
Stochastic Models in Industrial Engineering (3)
Stochastic models of operations research applied to queuing, reliability, inventory, supply chain, and other problems; Poisson processes; discrete-time and continuous-time Markov chains; renewal processes; and transient and steady-state analyses.
Prerequisite: Calculus-based course in probability.
Supply Chain and Logistics Engineering (3)
Methods and techniques of operations research applied to the design and analysis of marketing and distribution systems. Topics include sales forecasting, single- and multi-echelon inventory and distribution systems, routing and scheduling of product delivery.
Prerequisites: Calculus, some knowledge of probability.
Forecasting and Time Series Analysis (3)
Alternate linear and nonlinear, stationary and nonstationary time-series models for purposes of prediction. Smoothing techniques, estimating trend and seasonality, multivariate time series, and state-space models. Various estimation and forecasting techniques.
Prerequisites: Statistics and 16:540:515, or permission of instructor.
Network Applications in Industrial and Systems Engineering (3)
Flow problems in networks. Topics include shortest-route problems, critical path, and GERT.
Prerequisite: 14:540:311 (undergraduate introduction to operations research).
Computational Methods for Industrial Engineering (3)
Computational methods in modeling, planning, and control of production systems; numerical methods; artificial intelligence techniques; exact and heuristic search methods; and computational strategies for larger-scale systems.
Prerequisites: Programming in C helpful but not required.
Enterprise Integration (3)
Building and integrating information systems into manufacturing, engineering, and business functions in an enterprise. Methodological and practical aspects including client-server models, internet-based three-tiered system architecture, legacy systems, data transfer, and distributed computing. Project involves prototyping of small enterprise information systems from design to implementation.
Special Problems in Industrial Engineering (BA)
Investigations in selected areas of industrial and systems
engineering and operations research.
Prerequisite: Permission of instructor.
Manufacturing Project (3)
Understanding of the state of technology in discrete, batch, and continuous manufacturing; hands-on experience.
Prerequisite: Permission of instructor.
Simulation of Production Systems (3)
Discrete event simulation applied to problems in manufacturing, inventory control, and engineering economics. Topics include simulation languages, estimating production system operating characteristics, comparing alternative systems, and validating approximate analytical models.
Prerequisites: Probability and computer programming.
Production Analysis (3)
Analysis of production engineering, with emphasis on planning and control of manufacturing and service systems.
Prerequisites: Probability and linear programming.
Automation and Computer-Integrated Manufacturing I (3)
Design of automated and computer-integrated manufacturing systems using programmable automation. Modeling of discrete and continuous control systems, design and analysis of control architecture, implementation of programmable controllers, and shop floor data acquisition systems.
Prerequisite: 14:540:382 or permission of instructor.
Applications of Robotics in Manufacturing Systems (3)
Integration of robots in manufacturing systems, design of robot workstations, materials handling, and interactions among manufacturing cells. Economic feasibility and robot selection.
Prerequisites: 14:540:343, 453, and undergraduate course in computer control is helpful but not required.
Manufacturing Processes and Control (3)
Overview of manufacturing processes and computer numerically controlled machines, basic digital control theory, design and simulation of advanced controllers, tracking control in machine tools, precision engineering, sensors-based advanced monitoring of machine systems.
Prerequisites: 14:540:303, 382, or permission of instructor.
Advanced Manufacturing Processes (3)
Introduction to computational modeling and
optimization of manufacturing processes. Modeling and optimization of precision
manufacturing processes (micromachining), advanced manufacturing processes (laser and energy beam based), additive
manufacturing processes (selective laser sintering and melting). Emphasis on
process physics and analytical and computational methods to predict and
optimize process performance and product quality.
Prerequisite: 14:540:303 or permission of instructor.
Advanced Engineering Economics I (3)
Economic decision models for engineers involving allocation of resources; evaluation of strategic alternatives; advanced risk and uncertainty analysis; and weighing and evaluating nonmonetary factors.
Quality Management (3)
Quality management philosophies, Deming, Juran; quality planning, control, and improvement; quality systems; management organizations for quality assurance. Role of operations research.
Prerequisite: Permission of instructor.
System Reliability Engineering I (3)
Methods of measuring the reliability and effectiveness of complex engineering systems, including optimization theory, preventive maintenance models, and statistical analysis.
Prerequisites: 16:960:580 required; a course in stochastic modeling helpful.
Maintenance Modeling and Optimization (3)
Maintenance issues; technical foundations for modeling such large-scale systems; approaches for
condition maintenance; and optimization methodologies for optimum inspection, repair, and maintenance schedules.
Risk Analysis and Mitigation (3)
Concept of risk and
probabilistic models for risk analysis. Expert judgment elicitation and incorporation into risk models. Causal
chain, fault-tree, consequence analysis, risk management, and communication. Case studies in transportation,
homeland security, health care systems, supply chain systems, and natural
Prerequisites: Simulation and probability.
Software Reliability I (3)
Software-reliability issues; software errors, faults, and failures; software design for reliability; data collection; formal methods for reliability; software fault tolerance; modeling growth in software reliability; cost modeling and estimation; and software quality management.
Prerequisite: 16:540:515 or 16:960:580.
Training Future ISE Faculty Members (0)
Topics include learning styles, teaching
methodology. Students will
also intern in industrial and systems engineering introductory laboratories.
Required of all doctoral students.
Advanced Stochastic Modeling in ISE (3)
Stochastic modeling and control fundamentals of complex systems;
renewal theory, Markov decision processes, martingales, and Brownian
motion. Applications in reliability,
transportation, telecommunication, and supply chains are emphasized.
Discrete Event Dynamic Systems (3)
Supervisory control of discrete event dynamic systems, process monitoring, Petri nets, functional analysis, performance analysis, control specification, and control verification and validation.
Performance Analysis of Manufacturing Systems (3)
Modeling of manufacturing systems such as flow shops, job shops, transfer lines, and flexible manufacturing systems. Topics include problems of failures and repairs, the role of buffer inventories, capacity allocation, and machine interface problems.
Inventory Control (3)
Modeling of supply chain and logistic systems
with stochastic demand and lead times. Characterization of optimal control
policies via stochastic dynamic programming, Markov decision processes,
stochastic games, and analysis of single as well as multi-item systems with
single and multiple echelons, multiple retailers. Recent research issues are investigated.
Theory of Scheduling (3)
Advanced topics in sequencing and scheduling for manufacturing and service systems; flow shop, job shop-static, and dynamic models; multiprocessor parallel machining; preempt-resume algorithms; optimal due-date problems; probabilistic sequencing; simulation and applied operations research models.
Prerequisites: Undergraduate production course and advanced calculus.
Automation and Computer-Integrated Manufacturing II (3)
Design of automated and computer-integrated manufacturing systems using programmable automation. Modeling, specification, and implementation of factory information systems. Reference models and control architecture for discrete parts manufacturing, batch process manufacturing, and semiconductor manufacturing industries.
Prerequisite: 14:540:486 or permission of instructor.
Laser-Based Micromanufacturing (3)
Introduction to laser materials processing, micromanufacturing, and MEMS. Advances and opportunities made possible by the application of laser-based micromanufacturing processes. Applications of laser micromachining, laser thin-film processing, laser microheat treatment, laser microwelding, and laser microrapid prototyping. Process modeling, planning, and integration issues.
Advanced Engineering Economics II (3)
Focuses on engineering economic decision making. Application of analytical techniques to the evaluation of industrial projects, the relationship of project selection to long-range planning, and the relationship between the economics of technical choice and industrial productivity.
Prerequisite: 16:540:575 or permission of instructor.
Optimization and Performance Models in Service Systems (3)
Optimization and stochastic models for design and operation of service systems including health care and emergency services, security,
warehousing, and call centers. Multiobjective optimization, location models,
queueing systems, scheduling, resource allocation, workforce management.
Prerequisites: Optimization (e.g., 16:540:510) and stochastic processes (e.g., 16:540:515).
Production and Quality Engineering (3)
Doctoral seminar course employing journal articles in
quality engineering, production systems, and topics relevant to the participating
students including data mining, process control, energy, reliability,
maintenance, security, sensor technology, and health care.
Prerequisites: Open only to doctoral students in industrial and systems engineering, statistics, or operations research.
Process Modeling and Control (3)
Linear stationary (ARMA) and nonstationary (ARIMA), nonlinear (ARCH, GARCH) time-series models for process control; Kalman filters; various automatic process control (APC) strategies; statistical process control (SPC) methods and integration of APC and SPC.
Prerequisites: 16:540:515 and 568.
System Reliability Engineering II (3)
Advanced topics in reliability theory and engineering; availability models of multistate devices; theory of preventive maintenance, replacement, and inspection; accelerated life reliability models.
Component Reliability (3)
Emphasizes reliability estimation of components stressed under different conditions of thermal, electric field, humidity, vibration, and fatigue. Burn-in testing, reliability estimation from degradation data, and relationships between accelerated stresses and normal operating conditions.
Seminar in Industrial and Systems Engineering (0,0)
Speakers from industry and academia describe their current research.
Advanced Topics in Industrial Engineering (3)
Seminar for doctoral students in a selected area of industrial engineering. Based on current literature.
Prerequisite: Permission of instructor.
Software Reliability II (3)
Advanced topics in software reliability modeling, calibrating models, software-related problems, software-hardware reliability modeling, software cost models, optimum release policies, and fault-tolerant software modeling.
Prerequisite: 16:540:595 or permission of instructor.
Research in Industrial and Systems Engineering (BA,BA)