School of Engineering - Industrial Engineering Department
- Bopaya Bidanda, PhD, Chair
- Web site:http://ie.pitt.edu/graduate/
The Industrial Engineering Department offers graduate programs leading to both master's and doctoral degrees. The department provides several choices of concentration areas including:
Operations Research
Information Systems Engineering
Product Realization and Manufacturing Systems
Engineering Management
The master's program is flexible and students may choose to focus on one of the concentration areas or opt for a more broad-based curriculum with course work spanning all areas. Courses are designed so that students who have a basic foundation in engineering, computers, and basic sciences can develop the capability for more effective technical and management proficiency. All graduates of the program are prepared to assume responsible positions in industry, government, and service organizations; in addition, doctoral graduates are also qualified for academic or research careers.
Admission Requirements
Applications are encouraged from candidates who possess an undergraduate or graduate degree from an ABET-accredited program in any engineering discipline, or a degree in a complementary technical discipline, such as mathematics, physics, chemistry, computer science, or information science. An undergraduate knowledge of probability and statistics, calculus, differential equations, linear algebra, and proficiency in computer programming is required. Students who cannot demonstrate these skills upon matriculation will be placed in appropriate undergraduate courses in order to acquire this knowledge. These undergraduate courses do not count towards a graduate degree.
All students should take the GRE, and foreign students also must take the TOEFL examination. It is desirable for PhD applicants to have an interview with a faculty member, although this is not a requirement for admission.
Master of Science in Industrial Engineering
The Master of Science in Industrial Engineering program requires either 30 credits of graduate study without the thesis option (Professional MS), or 24 credits of graduate study plus a six-credit thesis (Research MS).
Non-thesis option: With this option, the student is required to take IE 2005 and at least two of the five courses in the basic core. The remainder of the student's program can be focused in a concentration area or broad-based in conjunction with the student's interests and the approval of the advisor. With the permission of the student's advisor, the student may also take two courses from other graduate offerings within the University.
Thesis option:The thesis option also includes IE 2005 and at least two of the five courses in the core. In addition, the student must complete a six-to-eight credit thesis. With this option, all course work must come from departmental offerings and no out-of-department electives are permitted. The master's thesis must show marked attainment in one of the departmental concentration areas. Acquisition of the methods and techniques of scientific investigation must also be demonstrated. A faculty member knowledgeable in the student's area of interest must supervise the thesis.
Concentration Areas: Students may choose to focus on a specific concentration area such as the four listed above. If a student opts to focus on a concentration area, the program must include (in addition to IE 2005) a minimum of five courses from the area. Appropriate core courses may be counted among these five courses.
Normally the program can be completed in 12 months of full-time study or two to three years of part-time study. Many graduate courses are offered in the evening for the convenience of working professionals. Courses also are offered in the summer term.
Students with undergraduate degrees from ABET-accredited Industrial Engineering Programs are encouraged to bypass any or all core courses in which they have a strong background and substitute more advanced elective courses.
Doctoral Program in Industrial Engineering
The doctoral program prepares the student for the rigorous demands of developing and implementing effective operational and management systems. The student is educated at the frontiers of knowledge in technical management, systems design, and decision-making concepts. This work requires a strong background in mathematics, probability theory, optimization techniques, systems management, and behavioral systems. The PhD student is expected to be a full-time student. Although it is possible to seek candidacy as a part-time student, the PhD candidate must spend at least one academic year full-time on campus. The graduate faculty typically works closely with individual doctoral students to create a more flexible program tailored to individual needs.
Entrance to the PhD Program
To be accepted for the doctoral program, a graduate student must have a superior graduate scholastic record and show promise for independent research. To be admitted to the doctoral program, a prospective doctoral student must have a cumulative quality point average of 3.30 or better in graduate course work. A graduate student who has completed the equivalent of a master's degree program, including all of the core courses, is eligible for entrance into the doctoral program. The student must seek faculty approval to take the PhD preliminary examination. This preliminary examination is given once a year and encompasses IE 2005, the five courses in the basic core, and an unstructured problem that the student is required to formulate and solve. The student must pass both the written and oral part of the examination. The examination allows the department to assess the student's academic preparation and creative ability to conduct doctoral-level research. All students must take the examination by January of the second year in which they are in residence, although it is acceptable to take the examination earlier.
Doctoral Course and Dissertation Credit Requirements
In addition to the basic core courses, the doctoral student will take any courses that may be required in preparation for the PhD comprehensive examination and the student's dissertation topic. These courses are selected in conjunction with a program approved by the student's advisor. According to University regulations, the PhD requires at least 72 credits beyond the bachelor's degree or 42 credits beyond the master's degree, including 18 credits for dissertation research. Course credits typically include the following:
- IE 2005 3 credits
- Core courses 15 credits
- Additional course work 36 credits
- Dissertation Credits 18 credits
Additional Doctoral Requirements
All full-time students must enroll in and attend IE 3095, the Graduate Seminar, and all full-time students in their second year of study are required to register for IE 2093, Graduate Journal Seminar. The credits for these courses do not count towards the 72-credit requirement.
The comprehensive examination is taken by students after completing the course work in their concentration. The PhD comprehensive exam has a three-fold purpose: (1) test the student's proficiency (knowledge and skills) in his or her major area of interest; (2) identify deficiencies in the student's background and suggest remedial work; and (3) test the student's ability to prepare an acceptable dissertation in the student's area of concentration.
All doctoral students are expected to pursue research by working with individual faculty in areas that can lead to a potential doctoral dissertation. A PhD candidate must demonstrate the ability to conduct research of an original nature by completing a dissertation and preparing a paper of publishable quality. The dissertation topic is selected by the student in some theoretical or applied area of interest in consultation with a faculty advisor. A faculty committee must approve the dissertation proposal before the student embarks on dissertation research.
Graduate Industrial Engineering Courses
| Required |
| IE 2005 |
Probability and Statistics for Engineers |
3 cr. |
| Basic Core |
| IE 2001 |
Operations Research |
3 cr. |
| IE 2003 |
Systems Management |
3 cr. |
| IE 2004 |
Information Systems |
3 cr. |
| IE 2006 |
Introduction to Manufacturing Systems |
3 cr. |
| IE 2007 |
Statistics for Engineers II |
3 cr. |
| Elective Courses |
| IE 2018 |
Engineering Tools for E-commerce |
3 cr. |
| IE 2025 |
Facility Layout and Material Handling |
3 cr. |
| IE 2030 |
Behavioral Systems Engineering |
3 cr. |
| IE 2032 |
Cases in Systems Management |
3 cr. |
| IE 2037 |
Cost Management for Advanced Manufacturing |
3 cr. |
| IE 2040 |
Advanced Engineering Economy |
3 cr. |
| IE 2051 |
Computer Aided Manufacturing |
3 cr. |
| IE 2054 |
Industrial Robotic Applications |
3 cr. |
| IE 2055 |
Automation in Manufacturing and Product Design |
3 cr. |
| IE 2057 |
Manufacturing Information Systems |
3 cr. |
| IE 2061 |
Ergonomics and Occupational Biomechanics |
3 cr. |
| IE 2073 |
Design of Experiments |
3 cr. |
| IE 2076 |
Total Quality Management |
3 cr. |
| IE 2081 |
Nonlinear Optimization |
3 cr. |
| IE 2082 |
Linear Optimization |
3 cr. |
| IE 2083 |
Production and Inventory Control |
3 cr. |
| IE 2084 |
Stochastic Processes |
3 cr. |
| IE 2086 |
Decision Models |
3 cr. |
| IE 2087 |
Simulation Modeling Using Siman/Cinema |
3 cr. |
| IE 2088 |
Digital Systems Simulation |
3 cr. |
| IE 2089 |
Rapid Prototyping and Reverse Engineering |
3 cr. |
| IE 2090 |
MS Project |
3 cr. |
| IE 2093 |
Graduate Journal Seminar |
3 cr. |
| IE 2997 |
Research, MS |
Var. cr. |
| IE 2999 |
MS Thesis |
Var. cr. |
| IE 3030 |
Advanced Topics in Engineering Management |
3 cr. |
| IE 3031 |
Project Management |
3 cr. |
| IE 3033 |
Neural Networks and Industrial Applications |
3 cr. |
| IE 3034 |
Management of Technological Innovation |
3 cr. |
| IE 3050 |
Advanced Topics in Manufacturing |
3 cr. |
| IE 3052 |
Computer Graphics and Machine Vision |
3 cr. |
| IE 3062 |
Advanced Ergonomics |
3 cr. |
| IE 3082 |
Mathematical Theory of Scheduling Models |
3 cr. |
| IE 3085 |
Queuing Theory |
3 cr. |
| IE 3086 |
Introduction to Integer and Dynamic Programming |
3 cr. |
| IE 3087 |
Network-Based Optimization |
3 cr. |
| IE 3091 |
Heuristic Optimization |
3 cr. |
| IE 3095 |
Graduate Seminar |
3 cr. |
| IE 3997 |
Research, PhD |
Var. cr. |
| IE 3998 |
Independent Study |
Var. cr. |
| IE 3999 |
Dissertation |
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