Industrial Engineering

Study mode:On campus Study type:Full-time Languages: English
 
401–500 place StudyQA ranking:4355 Duration:24 months

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Profitable design and operation of modern industrial systems requires integration of human, material, equipment and financial resources.

In recent years this integration has become tighter due to the inclusion of information technology, and resulted in more complex systems. Industrial Engineering research focuses on quantitative analysis, synthesis and management of such complex systems. The affiliated faculty members come from the Industrial Engineering department of the College of Engineering, the Operations and Information Systems group of the College of Administrative Sciences and Economics, and other related fields.

Our research areas are diverse, including Logistics, Supply Chain Management, Service Operations, Production Systems, Stochastic Processes, Financial Engineering, Mathematical Programming, Data Mining and Bioinformatics. The programs are built on the basic methodologies of operations research and their applications in manufacturing, distribution and service industries. Graduates of the M.Sc. program have been placed in respectable Ph.D. programs in North America, Europe and Turkey as well as various professional positions in industry.

Research Areas

* Bioinformatics (Ceyda Oguz, Metin Türkay)
* Data Mining (Özden Gür Ali, Sibel Salman, Serpil Sayin)
* Financial Engineering (Süleyman Özekici)
* Logistics (Deniz Aksen, Onur Kaya, Ceyda Oguz, Sibel Salman, Metin Türkay)
* Optimization Theory and Algorithms (Ceyda Oguz, Deniz Aksen, Metin Türkay, Sibel Salman, Serpil Sayin, Emre Alper Yildirim)
* Production Systems and Scheduling (Yaman Arkun, Selçuk Karabati, Fikri Karaesmen, Onur Kaya, Ceyda Oguz, Baris Tan, Metin Türkay)
* Service Operations (Zeynep Aksin, Evrim Günes, Fikri Karaesmen, Lerzan Örmeci)
* Supply Chain Management (Yalçin Akçay, Evrim Günes, Fikri Karaesmen, Onur Kaya, Lerzan Örmeci, Baris Tan, Metin Türkay)

Course Descriptions
INDR 501 Optimization Models and Algorithms (3 credits)

Convex analysis, optimality conditions, linear programming model formulation, simplex method, duality, dual simplex method, sensitivity analysis; assignment, transportation, and transshipment problems.

Prerequisite: An undergraduate level Operations Research course or consent of the instructor.

INDR 502 Logistics and Supply Chain Systems (3 credits)

Introduction to the concepts and terminology of logistics and supply chain management. Examination of components of logistics and supply chain systems such as purchasing, storage, production, inventory, and transportation systems. Analysis of interactions and trade-offs among these components using mathematical models and quantitative techniques.

Prerequisite: INDR 501 or consent of the instructor.

INDR 503 Stochastic Models and Their Applications (3 credits)

The basic theory of the Poisson process, renewal processes, Markov chains in discrete and continuous time, as well as Brownian motion and random walks are developed. Applications of these stochastic processes are emphasized by examples, which are drawn from inventory and queueing theory, reliability and replacement theory, finance, population dynamics and other biological models.

Prerequisite:An undergraduate level statistics course or consent of the instructor.

INDR 504 Advanced Engineering Materials Manufacturing (3 credits)

Advanced Engineering Material Manufacturing Processes will be studied for (i) metals and (ii) plastics and composites. Material removal, addition, and change of form processes will be studied for metals. In the plastics and composites part, similarities/differences, advantages/disadvantages, and proper selection of manufacturing processes such as Injection Molding, Compression Molding, Extrusion, Sheet Forming, Tow Placement, Pultrusion, Liquid Molding, Filament Winding, Pultrusion and Autoclave Processing will be illustrated with applications from aerospace, automotive, biomedical, sporting goods and civil infrastructure industries. Issues and their solutions with in-site sensing and on- and off-line control will be studied with examples.

Prerequisite: INDR 505 or consent of the instructor.

INDR 505 Manufacturing Systems (3 credits)

This course will cover the basic concepts and techniques in hierarchical design, planning, and control of manufacturing systems. Topics include flow line and assembly systems, group technology and cellular manufacturing, just-in-time, flexible manufacturing systems.

INDR 506 Computer Integrated Manufacturing and Automation (3 credits)

This course introduces Computer Aided Design and Manufacturing (CAD/CAM) Systems, Computer Numerical Control (CNC) Machine Tools, Modern Sensors in Manufacturing, Machining Processes, Rapid Prototyping, and Fundamentals of Industrial Robotics.

INDR 508 Discrete Event Simulation (3 credits)

Topics on distribution fitting and generating random numbers and random variates will be covered as well as the statistical analysis of simulation output including some well-known analysis methods and variance reduction techniques. Recent developments in the area will also be discussed.

Prerequisite: INDR 503 or consent of the instructor.

INDR 520 Network Models and Optimization (3 credits)

Network flow models and optimization problems. Algorithms and applications. Minimum spanning tree problem. Shortest path problems. Maximum flow problems, minimum cuts in undirected graphs and cut-trees. The minimum cost network flow problem. Matching problems. Generalized flows. Multicommodity flows and solution by Lagrangean relaxation, column generation and Dantzig-Wolfe decomposition. Network design problems including the Steiner tree problem and the multicommodity capacitated network design problem; formulations, branch-and-cut approaches and approximation algorithms.

Prerequisite: INDR 262 or consent of instructor.

INDR 530 Decision Analysis (3 credits)

Tools, techniques, and skills needed to analyze decision-making problems characterized by uncertainty, risk, and conflicting objectives. Methods for structuring and modeling decision problems and applications to problems in a variety of managerial decision-making contexts. Structuring decision problems: Decision trees, model building, solution methods and sensitivity analysis; Bayes' rule, the value of information and using decision analysis software. Uncertainty and its measurement: Probability assessment. Utility Theory: Risk attitudes, single- and multi-attribute utility theory, and risk management. Decision making with multiple objectives.

Prerequisite: ENG 200 or consent of instructor.

INDR 551 Advanced Optimization Methods (3 credits)

Combinatorial optimization, structure of integer programs, pure integer and mixed integer programming problems, branch and bound methods, cutting plane and polyhedral approach, convexity, local and global optima, Newton-type, and conjugate gradient methods for unconstrained optimization, Karush-Kuhn-Tucker conditions for optimality, algorithms for constrained nonlinear programming problems, applications in combinatorial and nonlinear optimization.

Prerequisite: INDR 501 or consent of the instructor.

INDR 553 Advanced Stochastic Processes (3 credits)

Brief review of basic processes like Poisson, Markov and renewal processes; Markov renewal processes and theory, regenerative and semi-regenerative processes; random walk, Wiener process and Brownian motion; martingales; stochastic differential equations and integrals; applications in queueing, inventory, reliability and financial systems.

Prerequisite: INDR 503 or consent of the instructor.

INDR 566 Scheduling (3 credits)

Introduction to scheduling: examples of scheduling problems, role of scheduling, terminology, concepts, classifications; solution methods: enumerative methods, heuristic and approximation algorithms; single machine completion time, lateness and tardiness models; single machine sequence dependent setup models; parallel machine models; flow-shop models; flexible flow-shop models; job-shop models; shifting bottleneck heuristic; open-shop models; models in computer systems; survey of other scheduling problems; advanced concepts.

Prerequisite: Consent of instructor.

INDR 568 Heuristic Methods (3 Credits)

Constructive heuristics; improving heuristics; metaheuristics: simulated annealing, genetic algorithms, tabu search, scatter search, path relinking, ant colony optimization, variable neighborhood search, and their hybrids; heuristic methods based on relaxation and decomposition; applications: routing, scheduling, cutting and packing, inventory and production management, location, assignment of resources, bioinformatics, and telecommunications. Prerequisite: INDR 501 or consent of the instructor.

INDR 578 Advanced Models in Supply Chain Management (3 credits)

Dynamic inventory policies for single-stage inventory systems: concepts of optimality and optimal policies. Multi-Echelon Systems: uncapacitated models and optimal policies, capacitated models: different control mechanisms. Multiple locations and multiple items: inventory and capacity allocation. Decentralized control and the effects of competition on the supply chain: coordination and contracting issues.

Prerequisite: INDR 503, INDR 505 or consent of the instructor.

OPSM 502 Operations Management (3 credits)

Fundamental decisions and tradeoffs in control of a firms operations: obtaining and controlling the flow of materilas through a production facility and distributing them to customers. Four modules: process fundamentals; cross functional integration, coordination, and control; improving the perfermance of productive systems; and competing through technology and operations.

OPSM 602 Advanced Models in Supply Chain Management (3 credits)

Dynamic inventory policies for single-stage inventory systems: concepts of optimality and optimal policies. Multi-Echelon Systems: uncapacitated models and optimal policies, capacitated models: different control mechanisms. Multiple locations and multiple items: inventory and capacity allocation. Decentralized control and the effects of competition on the supply chain: coordination and contracting issues.

Prerequisite: INDR 503, INDR505 or consent of the instructor.

QMBU 632 Introduction to Management Science (3 credits)

Fundamental quantitative methods used in business decision-making: mathematical programming, stochastic modeling, and simulation, with emphasis on formulation, analysis, and implementation.

OPSM 637 Operations Strategy (3 credits)

Coordination of marketing, operations, and finance functions within a framework designed to meet the competitive requirements of the marketplace. Interface issues between corporate strategy and the management of the operations function.

OPSM 638 Supply Chain Management (3 credits)

Process-oriented, integrated approach to procuring, producing, and delivering products and services to customers. Strategic and operational issues, such as sharing information and joint planning, reduction in supplier base, channel-wide inventory management, channel-wide total cost approach, supply chain competitiveness, compatibility of corporate philosophies.

OPSM 639 Project Management (3 credits)

Managerial skills and competencies for project management, defining a project, setting goals, defining the scope, planning the activities, managing the resources, organizing for project management, implementing the project, monitoring and controlling, and closing out the project.

OPSM 650 Selected Topics in Operations Management(3 credits)

Topics will be announced when offered.

MGIS 501 Introduction to Management Information Systems (3 credits)

The technological and institutional factors that influence the choice of hardware and software components of a management information system; introduction to systems analysis through teamwork on an actual business analysis problem.

MGIS 641 Database Management Systems (3 credits)

Database concepts for management, planning, and conceptual design, design and administration, classical systems, relational and distributed systems, implementation of database management systems.

MGIS 650 Selected Topics in Management Information Systems (3 credits)

Topics will be announced when offered.

INDR/ OPSM 590 Seminar

A series of lectures given by faculty or outside speakers. Participating students must also make presentations during the semester.

INDR 591 Project

Independent research towards M.S. degree without thesis option.

INDR 595 M.S. Thesis

Independent research towards M.S. degree with thesis option.

TEAC 500 Teaching Experience

Provides hands-on teaching experience to graduate students in undergraduate courses. Reinforces students' understanding of basic concepts and allows them to communicate and apply their knowledge of the subject matter.

ENGL 500 Graduate Writing

This is a writing course specifically designed to improve academic writing skills as well as critical reading and thinking. The course objectives will be met through extensive reading, writing and discussion both in and out of class. Student performance will be assessed and graded by Satisfactory/Unsatisfactory

* Personal and Educational Background Information (CV) * Recommendation Letters (2 for MSc, 3 for Ph.D) (3 for MS in Molecular Biology and Genetics) * (Recommendation Letters for Electrical and Electronics Engineering should be sent directly from referee with signature through e-mail. ) * TOEFL , IELTS or UDS&KPDS Requirement (for those whose native language is not English) * New Internet Based: Minimum Score 80 * Computer Based: Minimum Score 213 * Paper Based: Minimum Score 550 * IELTS: Minimum Score 6,5 * UDS / KPDS / YDS: 87 * ALES scores (required for all Turkish nationals) * GRE scores (required from Foreign students; optional for Turkish students) * Official transcripts from all the universities attended * Statement of Purpose English Language Requirements IELTS band: 6.5 TOEFL paper-based test score : 550 TOEFL iBT® test: 80

Financial Aid
The students who get the KU full-scholarship, will be supported with one of thepackages below;

For MS Students (Thesis Programs):
* Students admitted with a BS/BA degree will have the folowfing offer: * Tuition waiver (33,500 TL/year) plus 1,150 TL monthly stipend, housing.



For PhD Students:
* Students admitted with a BS/BA degree will have the following offer: * Tuition waiver (33,500 TL/year) plus 1,150 TL monthly stipend, housing. The monthly stipend increases to 1,600 TL after the student passes the PhD qualifier.


* Students admitted with a MS/MA degree will have the following offer: * Tuition waiver (33,500 TL/year) plus 1, 400 TL monthly stipend. The monthly stipend increases to 1,600 TL after the student passes the PhD qualifier



Additional Benefits:
* All students receive a laptop computer and private health insurance.
* Students with successful standing receive travel funds to attend scientific conferences and meetings.
* PhD students with higher GPA degrees may be offered super scholarship up to 2,500 TL .
* Students who receive their stipend from other sources (like TÜBITAK scholarships or externally funded research grants and projects) are eligible for the following benefits provided by the university:

* Research Award: 1,300 TL
* Free Housing: This includes all costs except telephone expenses.
* Research Award for PhD students: 2,000 TL/year after they pass the qualifier.

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