Industrial Engineering

Units: 3

Engineering economy analysis of alternative projects including tax and inflation aspects, sensitivity analysis, risk assessment, decision criteria. Emphasis on applications.

Offered in Spring Only

Units: 3

Analysis of economic merits of alternatives including interest and income tax considerations. Risk and sensitivity exploration techniques. Introduction to analytical techniques for multiple objectives or criteria. Use of mathematical programming andcomputers for capital budgeting.

Offered in Fall Only

Units: 3

The Bayesian approach to decision making, with numerous applications in engineering and business. Expected value maximization, decision trees, Bayes' theorem, value of information, sequential procedures and optimal strategies. Axiomatic utility theory and controversies, utility of money, theoretical and empirical determination of utility functions and relationship to mean-variance analysis. Brief introduction to multi-attribute problems, time streams and group decisions.

Offered in Spring Only

Units: 3

Specification of attributes/criteria/objectives for complex decisions. Determination of alternatives, attribute weights and decision-making process. Graphical and weighted evaluation techniques. Multi-attribute utility, multi-objective/goal programming and analytic hierarchy process methodologies. Computer applications and case studies.

Offered in Spring Only

Units: 3

Introduction to problems of the systems development cycle, including human-machine function allocation, military specifications, display-control compatibility, the personnel sub-system concept and maintainability design. Detailed treatment given to people as information processing mechanisms.

Offered in Spring Only

Units: 3

Occupational accident-injury study; morbidity, mortality; investigation and analysis. Hazard control; energy countermeasure strategies; control technology. Impact biomechanics, trauma and survivability. Risk assessment; systems safety analysis. Product design, manufacturing defects, system failures and human error as causative factors. Safety program development. Near-accident reporting. OSHA compliance; standards. Accident, trauma and forensic case studies from manufacturing, motor carrier andconstruction industries.

Offered in Spring Only

Units: 3

Anatomical, physiological, and biomechanical bases of physical ergonomics. Strength of biomaterials, human motor capabilities, body mechanics, kinematics and anthropometry. Use of bioinstrumentation, active and passive industrial surveillance techniques and the NIOSH lifting guide. Acute injury and cumulative trauma disorders. Static and dynamic biomechanical modeling. Emphasis on low back, shoulder and hand/wrist biomechanics.

Offered in Fall Only

Units: 3

Fundamentals of human information processing basic to skilled operator performance and the design of displays, controls and complex systems. Treatment of topics such as channel capacity, working memory, long-term memory, decision making, attention and process monitoring. Problems of display and control design and evaluation, evaluation of textual material, and human-computer interaction.

Offered in Spring Only

YEAR: Offered Alternate Years

Units: 3

Advanced aspects of human performance research. Qualitative models of human information processing. Characteristics and role of memory in decision making and response execution. Sensory channel parameters, attention allocation, time-sharing of tasks. Situation awareness and workload responses in complext tasks. Limitations of human factors experimentation. Factors in human multiple task performance. Cognitive task analysis and computational cognitave modeling/simulation of user behavior in specific applications.

Units: 3

Manufacturing process engineering, primary, secondary, finishing and assembly processes. Traditional and non-traditional manufacturing processes, group technology, manufacturing analyses and application of economic analyses. Graduate standing in Engineering.

Offered in Fall and Summer

Units: 3

Product development course targeted toward the medical device industry. Product design and development, concept generation and selection, parametric feature-based CAD, design for manufacturability [DFM] and assembly [DFA], tolerancing, rapid prototyping, tool design, tool fabrication, and medical device fabrication.

Offered in Spring Only

Units: 3

General principles of operation and programming of automated systems. Automated assembly, automated manufacturing, and inspection systems. Control of automated manufacturing. Industrial logic systems and programmable logic controllers. Computer numerical control, industrial robotics, and computer integrated manufacturing.

Offered in Fall and Spring

Units: 3

Rapid application development [RAD] tools to design and implement database-based applications. This includes: SQL query language, Visual Basic for Applications in database application construction, a standard RAD environment and how to access information in a database, entity/attribute modeling of the database structure, anomalies of database structures that create problems for applications, modeling of application system's functionality, and integrating these tools together to design and implement engineering applications. Examples from manufacturing and production systems. Restricted to advanced undergraduates and graduate students.

Offered in Fall and Spring

Units: 3

An analysis of Production-Inventory systems. Modeling and Analysis of single and multi-product inventory systems for single and multi-period environments under deterministic and stochastic assumptions. Development of optimal and heuristics scheduling models for single and multi-resource systems under deterministic and stochastic assumptions.

Offered in Spring Only

Units: 3

Introduction to graph theory and network theory. In-depth discussion of theory underlying [1] deterministic activity networks [CPM]: optimal time-cost trade offs; the problem of scarce resources; [2] probabilistic activity networks [PERT]: critical evaluation of underlying assumptions; [3] generalized activity networks [GERT, GAN]: applications of signal flow graphs and semi-Markov process to probabilistic branching; relation to the theory of scheduling.

Offered in Spring Only

YEAR: Offered Alternate Years

Units: 3

Introduction to basic concepts of quality engineering. Statistical process control [SPC] methods, acceptance sampling techniques, concept of parameter design and statistical as well as analytical techniques for its implementation, tolerance analysisand design, components of cost of poor quality and an introduction to quality management.

Offered in Spring Only

YEAR: Offered Alternate Years

Units: 3

Elements of logistics networks. Supply chain design: facility location and allocation; great-circle distances; geocoding. Multi-echelon production and inventory systems; sourcing decision systems. Vehicle routing: exact, approximation, and heuristic procedures; traveling salesman problem; basic vehicle routing problem and extensions; backhauling; mixed-mode transportation system design.

Offered in Spring Only

Units: 3

The course aims to introduce the various types of operations research models and techniques. We will address how to formulate a wide range of decision problems using an appropriate mathematical programming model and solve them using an appropriate algorithm or solver. The emphasis will be given to Linear Programming, Network Models, and Integer Programming. Some example applications of mathematical programming to be covered in this class include production planning, network analysis, project scheduling, logistics network design, fixed charge problems, set covering problem, etc.

Offered in Fall Spring Summer

Units: 3

Basic concepts of linear, nonlinear and dynamic programming theory. Not for majors in OR at Ph.D. level.

Offered in Fall Only

Units: 3

Introduction including: applications to economics and engineering; the simplex and interior-point methods; parametric programming and post-optimality analysis; duality matrix games, linear systems solvability theory and linear systems duality theory; polyhedral sets and cones, including their convexity and separation properties and dual representations; equilibrium prices, Lagrange multipliers, subgradients and sensitivity analysis.

Offered in Fall Only

Units: 3

Introduction to theory and computational aspects of dynamic programming and its application to sequential decision problems.

Offered in Spring Only

Units: 3

Formulation and analysis of stochastic models with particular emphasis on applications in industrial engineering; univariate, multivariate and conditional probability distributions; unconditional and conditional expectations; elements of stochastic processes; moment-generating functions; concepts of stochastic convergence; limit theorems; homogeneous, nonhomogeneous and compound Poisson processes; basic renewal theory; transient and steady-state properties of Markov processes in discrete and continuous time.

Offered in Fall Only

Units: 3

Introduction of general concepts of stochastic processes. Poisson processes, Markov processes and renewal theory. Usage of these in analysis of queues, from with a completely memoryless queue to one with general parameters. Applications to many engineering problems.

Offered in Spring Only

Units: 3

Basic discrete event simulation methodology: random number generators, generating random objects, design of discrete event simulation, validation, analysis of simulation output, variance reduction techniques, Markov chain Monte Carlo, simulation optimization. The course has computer assignments and projects. This course is a sequel to ISE/OR 760 Stochastic Models which serves as a prerequisite. This is NOT a software based course! Students who are looking for a class on simulation software, such as Arena and Simio, are recommended to take ISE 562 [master-level simulation class].

Offered in Fall and Spring

Units: 3

Exploration of technological issues and challenges underlying electronic commerce. Distributed systems; network infrastructures; security, trust, and payment solutions; transaction and database systems; and presentation issues. Project required. No Audits.

Offered in Spring Only

Units: 3

Introduction to and overview of artificial intelligence. Study of AI programming language such as LISP or PROLOG. Elements of AI problem-solving technique. State spaces and search techniques. Logic, theorem proving and associative databases. Introduction to knowledge representation, expert systems and selected topics including natural language processing, vision and robotics.

Offered in Fall and Spring

Units: 3

General introduction to computer networks. Discussion of protocol principles, local area and wide area networking, OSI stack, TCP/IP and quality of service principles. Detailed discussion of topics in medium access control, error control coding, and flow control mechanisms. Introduction to networking simulation, security, wireless and optical networking.

Offered in Fall Spring Summer

Units: 3

Database concepts. Database design. Data models: entity-relationship and relational. Data manipulation languages including SQL. Data Dictionaries. Query processing. Concurrency. Software development environments using a database system. Expert, object-oriented, multimedia and distributed database systems. Database systems architecture. Use of a commercial database management system.

Offered in Spring Only

Units: 3

Vector spaces. Bases and dimension. Changes of basis. Linear transformations and their matrices. Linear functionals. Simultaneous triangularization and diagonalization. Rational and Jordan canonical forms. Bilinear forms.

Offered in Fall and Spring

Units: 3

Algorithm behavior and applicability. Effect of roundoff errors, systems of linear equations and direct methods, least squares via Givens and Householder transformations, stationary and Krylov iterative methods, the conjugate gradient and GMRES methods, convergence of method.

Offered in Fall and Spring

Units: 3

This course is intended to give students a background in the methods of statistical analysis and design of experiments that will assist them in conducting research and analyzing data in engineering. Concentration in this course will be on principles of the design of experiments and analysis of variance and regression including post-hoc tests, inference for simple regression, multiple regression, and curvilinear regression.

Offered in Fall and Spring

Units: 3

Review of completely randomized, randomized complete block and Latin square designs and basic concepts in the techniques of experimental design. Designs and analysis methods in factorial experiments, confounded factorials, response surface methodology, change-over design, split-plot experiments and incomplete block designs. Examples used to illustrate application and analysis of these designs.

Offered in Fall Only