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Course Catalog

INDUSTRIAL ENGINEERING - WITH THESIS MASTER'S PROGRAM (MSIE)

The graduate curriculum leading to M.Sc. and Ph.D. degrees in Industrial Engineering is designed to provide the students with computing, quantitative, analytical, and applications skills and to prepare them as entrepreneurs, problem solvers, effective decision-makers, and change agents in a competitive business environment or as prospective scientists in the academics. The program focuses on production and service systems, integrated manufacturing, supply chain management, product development process, modeling and analysis of manufacturing processes and equipment, and operations research approaches to telecommunication and energy systems.

SUMMARY OF DEGREE REQUIREMENTS

Course Category Min. ECTS Credits Min. SU Credits Min. Courses
Master Thesis - - 1
Required Courses - 9 6
Core Electives - 6 2
Area Electives - 6 2
Total 120 21 11
 

Master Thesis

  Course Name ECTS Credits SU Credits Faculty
     IE 590 Master Thesis 50 0 FENS
 

Required Courses

9 SU credits and 3 courses; (IE 501, IE 503 and ENS 505) are required. All non credit "Seminar" courses and "Scientific and Technical Communication" are required.
  Course Name ECTS Credits SU Credits Faculty
     ENS 505 Methods of Statistical Inference 10 3 FENS
     GR 555E Scientific and Technical Communication 7 0 FENS
     IE 501 Linear Programming and Extensions 10 3 FENS
     IE 503 Stochastic Processes 10 3 FENS
     IE 551 Graduate Seminar I 1 0 FENS
     IE 552 Graduate Seminar II 1 0 FENS
 

Core Electives

Minimum 6 SU credits from the pool below are required (max. 2 courses from Special Topics courses can be taken).

  Course Name ECTS Credits SU Credits Faculty
     IE 509 Nonlinear Programming 10 3 FENS
     IE 512 Graph Theory and Network Flows 10 3 FENS
     IE 514 Manufacturing Strategies 10 3 FENS
     IE 515 Dynamic Programming 10 3 FENS
     IE 518 Queuing Theory and Applications 10 3 FENS
     IE 522 Decision Analysis 10 3 FENS
     IE 524 System Simulation 10 3 FENS
     IE 525 Operations Research and Data Mining 10 3 FENS
     IE 527 System Dynamics 10 3 FENS
     IE 530 Logistics and Transportation Systems Planning 10 3 FENS
     IE 532 Stochastic Models in Finance 10 3 FENS
     IE 536 Monte Carlo Methods in Finance 10 3 FENS
     IE 545 Production Systems Planning and Design 10 3 FENS
     IE 550 Sequencing and Scheduling 10 3 FENS
     IE 553 Facility Design and Analysis 10 3 FENS
     IE 554 Supply Chain Management 10 3 FENS
     IE 567 Manufacturing Systems Modelling 10 3 FENS
     IE 58000 Special Topics in IE: Logistics and Transportation Planning 10 3 FENS
     IE 58001 Special Topics in IE: Simulation for Statistical Inference 10 3 FENS
     IE 58002 Special Topics in IE: Production Planning 10 3 FENS
     IE 58004 Special Topics in IE: Applications of Combinatorial Optimization 10 3 FENS
     IE 58005 Special Topics in IE: Advanced statistics with R 10 3 FENS
     IE 601 Optimization Theory 10 3 FENS
     IE 602 Stochastic Programming 10 3 FENS
     IE 604 Integer Programming 10 3 FENS
     IE 605 Advanced Topics in Stochastic Processes 10 3 FENS
     IE 606 Large Scale Optimization 10 3 FENS
     IE 640 Behavioral and Experimental Methods in Operations Management 10 3 FENS
 

Area Electives

Minimum 6 SU credits from FENS graduate courses. (By advisor's approval, at most 6 SU credits can be taken from FASS or FMAN graduate courses.)

Click For Area Electives

**Courses in more than one areas are listed in the area according to order of appearence in Summary of Degree Requirements list. That is, if a course is both area elective and core elective,then it is listed in core elective courses list.

***Undergraduate courses are not listed in graduate area requirements even if they are among them.

****Since graduation requirements may change dependent to the enrollment year to the University, we advise our students who enrolled at SU in previous years and still continue their education, to track their graduation requirements completion via Information System - Degree Evaluation.