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Industrial Engineering

 

Master | Industrial Engineering

Program Format:   
Entrance Exam: GRE

Industrial engineers are in the business of making things work better and every industry can benefit from that. The field gives its practitioners an education in engineering and business, and the opportunity to work in a variety of fields such as bio- and nano- as well as traditional manufacturing, health care, entertainment, shipping and logistics, public utilities, telecommunications and management consulting.

The Master of Industrial Engineering (MIE) is designed to be a professional degree for the professional, practitioner-oriented individual who seeks graduate-level breadth in the field. It is intended as a terminal degree for self-supported, military, part-time, and co-op students preparing for a career in industry, government or consulting. Thus students pursuing this degree normally would not be considered for assistantship awards. No final oral examination or thesis research is required for this degree. Project work (up to six credit hours) is optional. Thus this degree may be obtained by course work only.

Students should have an undergraduate degree in engineering or in the behavioral, physical, or mathematical sciences. It is a 33 credit hour degree program that does not require a thesis, final oral exam or on-campus residency.

ADMISSIONS REQUIREMENTS

  • Bachelor’s degree from an accredited college or university in an engineering or related discipline. The discipline does not have to be industrial engineering but it must have a strong engineering/mathematical curriculum.
  •   An overall undergraduate GPA of at least 3.0.
  •   Completion of the Graduate Record Exam (GRE) for all applicants.
  •   TOEFL or IELTS scores (no more than two years old) for international applicants unless they have completed one year of study at a university in the United States.
  •   Three letters of recommendation from persons able to comment on the applicant’s qualifications for graduate study.

PLAN OF STUDY

minimum of 33 credit hours is required, of which at least 21 hours must be in Industrial Engineering courses. At least 27 hours of the 33 must be at the 500 level or above, and at least one 700 or 800 level ISE course must be included in the Plan of Graduate Work. Project work for the degree is optional; up to 6 hours of credit for ISE 677(Industrial Engineering Projects) may be allowed toward the degree. As a breadth requirement, the student must elect one course from four of the five breadth requirement groups in ISE plus one course from Computer Science, Mathematics, or Statistics, for a total of 15 credit hours. No more than 6 hours of 400-level coursework are permitted on the Plan of Graduate Work from outside the Department of Industrial Engineering.

Breadth Requirement (15 hours)

This requirement is met by selecting:

  • One course from four of the following groups in the Breadth Requirement Course Listing (12 credit hours):
    1. Economic Analysis and Decision Making
    2. Human Factors and Ergonomics
    3. Manufacturing Systems
    4. Production Systems
    5. Systems Analysis and Optimization
  • One course from group F (Computer Science, Mathematics, and Statistics) in the Breadth Requirement Course Listing.

For students with an undergraduate degree in Industrial Engineering, these breadth requirements should be discussed with the Director of Graduate Programs.

Minor Requirements

There is no minor; however, the student may elect a "concentration" from another department.

Project Work

Project work is optional. Credit may be allowed, for example, for work pursued during a co-op experience. Proposals for project work should be prepared using the form shown in theAppendix G, and must be reviewed and approved by the student's degree advisor. It is recommended that all project work should be documented in a formal report with properly listed references, abstract, etc. Such efforts should represent scholarly work above and beyond that done for other purposes, such as course term papers. M.I.E. students must register for ISE 677 (or ISE 589) in order to obtain course credit toward the degree for project work.

Breadth Requirement Course Listings

Group A: Economic & Decision Analysis - choose 1 (advanced courses may be substituted with approval)

ISE 510 - Applied Engineering Economy

Units: 3

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

Offered in Fall Only

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2016 Spring Term

ISE 711 - Capital Investment Economic Analysis

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

ISE 712 - Bayesian Decision Analysis For Engineers and Managers

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

ISE 731 - Multi-Attribute Decision Analysis

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

Group B: Human Factors & Ergonomics - choose 1 (advanced courses may be substituted with approval)

ISE 540 - Human Factors In Systems Design

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

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2016 Spring Term

ISE 541 - Occupational Safety Engrg

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

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2016 Spring Term 2016 Summer Term 1

ISE 544 - Occupational Biomechanics

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

ISE 744 - Human Information Processing

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

ISE 745 - Human Performance Modeling

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.

Group C: Manufacturing Systems - choose 1 (advanced courses may be substituted with approval)

ISE 515 - Manufacturing Process Engineering

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 Only

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2016 Summer Term 1 2016 Fall Term

ISE 714 - Product Manufacturing Engineering for the Medical Device Industry

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

ISE 716 - Automated Systems Engineering

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 Spring Only

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2016 Spring Term 2016 Summer Term 1 2016 Fall Term

ISE 519 - Database Applications in Industrial and Systems Engineering

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

Group D: Production Systems - choose 1 (advanced courses may be substituted with approval)

ISE 723 - Production Planning, Scheduling and Inventory Control

Units: 3

An analysis of Production-Inventory systems. Discussion of commonly used planning and scheduling techniques. Introduction to use of math modeling for solution of planning and scheduling problems. Interface with quality control and information systems.

Offered in Fall and Spring

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2016 Spring Term 2016 Summer Term 1 2016 Fall Term

ISE 726 - Theory of Activity Networks

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

ISE 748 - Quality Engineering

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

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2016 Spring Term

ISE 754 - Logistics Engineering

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

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2016 Spring Term

Group E: Systems Analysis and Optimization - choose 1 (advanced courses may be substituted with approval)

ISE 501 - Introduction to Operations Research

Units: 3

OR Approach: modeling, constraints, objective and criterion. Problems of multiple criteria, optimization, model validation and systems design. OR Methodology: mathematical programming; optimum seeking; simulation, gaming; heuristic programming. Examples, OR Applications: theory of inventory; economic ordering under deterministic and stochastic demand. Production smoothing problem; linear and quadratic cost functions. Waiting line problems: single and multiple servers with Poisson input and output. Theory of games for two-person competitive situations. Project management through PERT-CPM.

Offered in Fall Spring Summer

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2016 Spring Term 2016 Fall Term

OR 504 - Introduction to Mathematical Programming

Units: 3

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

Offered in Fall Only

ISE 505 - Linear Programming

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

ISE 709 - Dynamic Programming

Units: 3

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

Offered in Spring Only

ISE 760 - Applied Stochastic Models in Industrial Engineering

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

ISE 761 - Queues and Stochastic Service Systems

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

ISE 762 - Computer Simulation Techniques

Units: 3

Basic discrete event simulation methodology: random number generators, simulation designs, validation, analysis of simulation output. Applications to various areas of scientific modeling. Simulation language such as SLAM and GPSS. Computer assignments and projects.

Offered in Fall Only

Group E: Computer Science, Mathematics, and Statistics - choose 1 (other graduate level CSC, Math, or Statistics courses may be substituted with approval)

CSC 513 - Electronic Commerce Technology

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

CSC 520 - Artificial Intelligence I

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 Summer

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2016 Spring Term

CSC 570 - Computer Networks

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 and Spring

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2016 Fall Term

CSC 742 - Database Management Systems

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

MA 520 - Linear Algebra

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 Only

MA 580 - Numerical Analysis I

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

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2016 Fall Term

ST 516 - Experimental Statistics For Engineers II

Units: 3

General statistical concepts and techniques useful to research workers in engineering, textiles, wood technology, etc. Probability distributions, measurement of precision, simple and multiple regression, tests of significance, analysis of variance, enumeration data and experimental designs.

Offered in Spring Only

ST 711 - Design Of Experiments

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

Tuition Level: Graduate - Engineering

Resident
Cost per Credit Hour: $445.66
Total Estimated Cost for 33 Credits Completed at NC State: $14,706.78

Non-resident
Cost per Credit Hour: $1,041.66
Total Estimated Cost for 33 Credits Completed at NC State: $34,374.78

Approximate cost per semester: $4,010.94 based on 9 credit hours

Note: There may be additional fees associated with Distance Education courses for verification of student identity for proctored examinations. These fees will be paid directly by the student to the proctor or facility and are not charged to your student account.

More about Online and Distance Education Tuition

Entry Semester Application Deadlines and Details
FallJun 25 (US); Mar 1 (Int)
SpringNov 25 (US); Jul 15 (Int)
Summer 1Mar 25 (US); Dec 15 (Int)
Summer 2May 10 (US); Dec 15 (Int)

Dr. Yahya Fathi

Director of Graduate Programs

919-515-6417
fathi@eos.ncsu.edu