Web Site of the Department

Head of Department: Zeki Caner Taşkın

Associate Department Heads: Aybek Korugan, Gönenç Yücel.

Professors : İsmail Kuban Altınel, Mustafa Necati Aras, Tınaz Ekim Aşıcı, Fikret Ümit Bilge, Taner Bilgiç, Mahmut Ekşioğlu, Ahmet Refik Güllü, Gürkan Kumbaroğlu, Zeki Caner Taşkın, Ali Rıza Kaylan†, İlhan Or*, Mustafa Akan*

Associate Professors : Mustafa Gökçe Baydoğan, Wolfgang Hoermann, Aybek Korugan, Ali Tamer Ünal*, Gönenç Yücel.

Assistant Professor : 

Instructors : Osman Gökhan Ersoy*, Kerem Can Özkısacık*

Assistants : Özge Coşkun,  Elvan Durdu, Burak Nur Erdem, Abdullah Kayacan,  Büşra Kobya, Ezgi Topuz, Halis Oğuz.

*Part-time

† Professor Emeritus

The academic program in the Industrial Engineering Department covers the core areas of the discipline: optimization, applied probability and statistics, manufacturing system design and management, systems modeling, design and analysis. The interdisciplinary nature of the program prepares the student for a wide range of planning and production positions in public and private enterprises as well as in the service and financial sectors.

Current research in the Industrial Engineering Department centers on the topics of manufacturing systems, supply chain management, financial engineering, simulation, statistical modeling, discrete optimization, stochastic processes, ergonomics, and the dynamics of socio-economic systems. Research and teaching activities involve extensive use of Flexible Automation and Intelligent Manufacturing (BUFAIM), Manufacturing Management Systems (MMS), Socio-Economic System Dynamics (SESDYN), Ergonomics (ErgoLab) and the general-purpose undergraduate and graduate computer laboratories, as well as the Engineering School Laboratories.

The course requirements for the Bachelor of Science Degree in Industrial Engineering total a minimum of 139 credit hours of formal course work. Students may choose departmental elective and specialization courses in Production/Manufacturing systems, Operations Research, Systems Modelling, Energy and Socio-economic Systems, Ergonomics, and Financial Engineering under the supervision of their advisors. Each student is also required to complete 70 workdays of industrial training during summers.

Established

1973

ISCED Code

Educational goals and objectives

1. Establish themselves as distinguished practicing industrial engineers or prospective academicians
at national and international levels,
2. Become accomplished professionals who will acquire leadership qualities and take decisionmaking
responsibilities in diverse fields,
3. Be able to adapt themselves to the changing conditions in their career paths with the help of
their lifelong learning traits,
4. Carry out their professional activities with the highest standards of ethical and social
responsibility.

Admission and special requirements

In Türkiye, student placement to universities and departments is carried out centrally through
exams administered by the ÖSYM. A two-phase standard centralized exam, called YKS is given once
a year. The first exam is called TYT and the second exam is called AYT. The Department has an
excellent academic reputation, attracting the most successful high school graduates in Turkey.
Acceptance to the freshmen class is very competitive. Admitted students are typically in the top
0.05% of those who take the National Student Selection and Placement Examination. The
Department consistently ranks number one over the years among all Industrial Engineering
programs in Turkey, according to the entrance scores of admitted students.

Acknowledgement of previous learning

Some courses taken from other institution may be transfered based on the grade and type of course
on approval.

Graduation requirements

The students are awarded a Bachelor of Science degree in Industrial Engineering when they satisfy
all graduation requirements. The coursework requirement for the Bachelor of Science Degree in
Industrial Engineering is a minimum of 140 credit hours (240 ECTS). Each student has to satisfy (i)
the coursework and (ii) internship requirement in order to graduate. The courses must be taken in
order that satisfies all prerequisities of all required courses. Elective courses must be taken from
specified pools of courses. Students are required to take two technical elective, three humanities
and social sciences elective and also one free elective courses and also complete a graduation
project as part of their curriculum.

Program learning outcomes

1. An ability to identify, formulate, and solve complex engineering problems by applying principles
   of engineering, science and mathematics
2. An ability to apply engineering design to produce solutions that meet specified needs with
   consideration of public health, safety, and welfare, as well as global, cultural, social,
   environmental and economic factors
3. An ability to communicate effectively with a range of audiences
4. An ability to recognize ethical and professional responsibilities in engineering situations and
   make informed judgments, which must consider the impact of engineering solutions in global,
   economic, environmental and societal contexts
5. An ability to function effectively on a team whose members together provide leadership, create
   a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives
6. An ability to develop and conduct appropriate experimentation, analyze and interpret data, and
   use engineering judgment to draw conclusions
7. An ability to acquire and apply new knowledge as needed, using appropriate learning strategies.

TYYÇ Ulusal Yeterlikler

TYYÇ Alan Yeterlikleri

UNDERGRADUATE PROGRAM

Total Credits 140 / ECTS 255

COURSE DESCRIPTIONS

IE 120 Industrial Engineering: Overview and Orientation   (3+1+0) 3 ECTS 5 
(Endüstri Mühendisliğine Giriş ve Ön Bilgilendirme)
Introduction and orientation to IE. Concepts and approaches; process analysis and modeling through cases; production and service systems; basic data analytics; engineering ethics.

IE 201 Intermediate Programming (2+0+2) 3 ECTS 6
(Orta Düzey Programlama)   
Introduction to object-oriented analysis and design: data encapsulation, inheritance, polymorphism, software engineering methodologies, UML; introduction to C++ programming language: class, inheritance, polymorphism, basic input/output, operator overloading, exception handling, templates; fundamental data structures: array, list, tree, binary tree; fundamental algorithms: searching, sorting, recursion.
Prerequisite: CMPE 150 or equivalent.

IE 202 Operations Research I (3+0+2) 4 ECTS 7
(Yöneylem Araştırması I)  
Modelling concepts; linear programming models; simplex and dual simplex methods; duality and sensitivity analysis; transportation, transshipment and assignment problems; basic problems in network theory: minimum spanning tree, shortest path, maximum flow, modeling using integer linear programming.
Prerequisite: MATH 201.

IE 203 Operations Research II (3+0+2) 4 ECTS 7
(Yöneylem Araştırması II)  
Integer programming: modelling, branch-and-bound method, cutting plane algorithm, linearization, processing and node/variable selection in branch-and-boun; deterministic dynamic programming; nonlinear programming: modeling and examples, unconstrained and constrained optimization; Markov chains; Poisson process and exponential distribution; queueing theory.
Prerequisites: IE 202 and IE 255.

IE 220 Materials and Processes in Manufacturing   (3+1+0) 3 ECTS 5
(İmalatta Malzemeler ve Süreçler)
Materials and properties; structure and manufacturing properties of metals; metal casting; bulk deformation processes (rolling, extrusion, forging); sheet-metal forming; machining processes (turning, drilling and milling); abrasive machining; processing of plastics.                                                                                                                    
Prerequisites: PHYS 121, CHEM 105 

IE 255 Probability for Industrial Engineers   (3+1+0) 3 ECTS 6
(Endüstri Mühendisleri için Olasılık)
Basic topics in probability theory; sample space, probability, and conditional probability; random variables, marginal, joint and conditional distributions; expectations and conditional expectations; hypergeometric, binomial, geometric distributions and their implications in IE/OR; Poisson, exponential, Erlang, gamma distributions and the Poisson arrival model; moment generating functions and Laplace transforms; law of large numbers, central limit theorem, and the Normal distribution; numerical and computational aspects of random variable generation.

IE 256 Statistics for Industrial Engineers   (3+1+0) 3 ECTS 6
(Endüstri Mühendisleri için İstatistik)
Basic topics in parametric statistics; estimation, confidence intervals, and hypothesis testing; analysis of variance, regression and correlation analysis; goodness of fit tests; application in statistical quality control, demand forecasting, and other IE/OR topics; elementary design of experiments and data collection; computer implementations using available up-to-date statistical software.
Prerequisite: IE 255 or equivalent.                                       
                                             
IE 306 Systems Simulation (3+0+2) 4 ECTS 7
(Sistem Benzetimi)
Basic concepts of discrete-event simulation modeling and analysis. Event-scheduling versus Process-interaction approach. Random number and random variate generation; inverse transformation and other selected techniques. Input data analysis and goodness of fit tests. Specific computer simulation languages. Analysis of simulation output and model validation.
Prerequisite: IE 256.

IE 310 Operations Research (3+0+2) 4 ECTS 5
(Yöneylem Araştırması)    
Economics and engineering decisions; principles of decision theory; generation and evaluation of alternatives; unconstrained and constrained optimization; duality and sensitivity analysis; application of LP; network models; simulation; case studies.
Prerequisite: MATH 201 or equivalent.

IE 312 Facilities Design and Planning   (3+0+2) 4 ECTS 7                        
(Tesis Tasarımı ve Planlama)
Nature and classification of production systems. Product design. Forecasting methods: simple linear regression, moving average and exponential smoothing methods. Capacity requirements planning. Design of discrete production systems: product-based layout and assembly line balancing; process-based layout and design of work stations; group technology and cell design; material handling and storage systems. Facility location: discrete and continuous space location models.
Prerequisites: IE 256 and IE 202.

IE 313 Supply Chain Management (3+0+2) 4 ECTS 7
(Tedarik Zinciri Yönetimi)     
Fundamentals of supply chain management and enterprise resources planning (ERP); aggregate production planning: static, dynamic, nonlinear and lot sizing models; operations scheduling: flow shops and job shops; materials management and materials requirement planning (MRP); capacity resources planning (CRP); distribution system management; implementation of manufacturing management strategies.
Prerequisite: IE 312 or equivalent

IE 341 Engineering Economics (3+0+2) 4 ECTS 7
(Mühendislik Ekonomisi)   
Economic analysis for engineering decision making; the finance function in an industrial enterprise, time value of money; basic interest formulas; annual cost comparison; present value analysis; rate of return; depreciation and taxes; multiple alternatives; mathematical models for equipment replacement; introduction to decision analysis; concepts of cost engineering.

IE 350 Systems Science and Engineering (3+1+0) 3 ECTS 6
(Sistem Bilimi ve Mühendisliği)
Introduction to systems science and systems engineering; fundamental concepts, philosophy and historical development of systems science. Analogical dynamic systems in electrical, hydraulic and mechanical fields; demonstration of general systems analogy on industrial, socio-economic and managerial models. Analysis tools for linear dynamic systems; non-linear model structures and inherent difficulties in their mathematical solution; equilibrium and stability analysis. Introduction to stock-flow modeling and formulation principles to represent socio-technical problems. Simulation method and software for large scale, time-delayed, non-linear dynamic models.
Prerequisite: MATH 202.

IE 360 Statistical Forecasting and Time Series (3+1+0) 3 ECTS 6
(İstatistiksel Tahminleme ve Zaman Serileri)
Exploring data patterns; moving averages, simple and double exponential smoothing, smoothing methods with seasonal data, Holt-Winter method; simple and multiple regression; regression with time series data; ARIMA models; Box-Jenkins method for forecasting; demand management and applications.
Prerequisite: IE 256 or consent of  the instructor.

ENG 380-399 / 480 - 499 Special Topics in Engineering (3+0+0)3 ECTS 5
(Mühendislikte Özel Konular)
Special topics of current interest in engineering and technology.

IE 414 Smart Manufacturing Systems  (2+0+2) 3 ECTS 6
(Akıllı İmalat Sistemleri)
Fundamentals of digital manufacturing technologies and automation:
Computer numerical control, additive manufacturing, industrial robotics, automated guided material handling vehicles, flexible manufacturing, real-time shop floor
control. Smart manufacturing concepts: Internet-of things, industrial data acquisition and communication networks, horizontal and vertical integration, cyberphysical
systems, connected smart factories. Lab applications including CAD/CAM integration, 3D printing, robot programming, modelling, simulation and realtime
operational control of advanced manufacturing systems.
Co-requisite: IE 306 or equivalent.

IE 420 Operations Research Modeling Applications   (2+0+2) 3 ECTS 6
(Yöneylem Araştırması Modelleme Uygulamaları)
Overview of optimization, simulation, stochastic and multiobjective models; various application areas, underlying assumptions, and critical technical considerations of optimization models; typical implementation problems, practical points and obstacles encountered in applying operations research models to real life problems.
Prerequisite: IE 202 or IE 310.

IE 423 Quality Engineering (3+1+0) 3 ECTS 6
(Kalite Mühendisliği)   
Principles of quality control systems; process control concepts; specification and tolerances; process capability studies; control charts; acceptance sampling plans; cost aspects of quality decisions; quality improvement programs; quality information systems.
Prerequisite: IE 256 or equivalent.

IE 424 Exploratory and Graphical Methods for Data Analysis  (2+0+2) 3 ECTS 6
(Veri Analizinde Açınsayıcı ve Grafiksel Yöntemler)
Portraying and comparing distributions, quantile plots, box plots, stem and leaf diagrams; transformations; smoothing; multivariate data, scatter plot matrices, Kleiner-Hartigan trees, Chernoff faces, star diagrams, glyphs; developing regression models, outlier detection, partial residual plots, Cp plots; ridge regression; robust regression.
Prerequisite: IE 256 or consent of the instructor.

IE 425 Data Mining (3+0+0) 3 ECTS 6
(Veri Madenciliği)
Fundamental principles and techniques of data mining. Supervised learning including similarity-based approaches, tree-based approaches and parallel  and serial ensemble methods. Unsupervised learning methods, including dimensionality reduction and association rule mining.
Prerequisite: IE 256 or consent of the instructor.

IE 430 Ergonomics and Human Factors Engineering    (3+0+1) 3 ECTS 6
(Ergonomi ve İnsan Faktörleri Mühendisliği)
Principles of ergonomics and human factors; their applications to the design and management of industrial systems. Physical and information ergonomics; human-machine systems; job, work environment and product design; industrial safety and health. Increasing productivity and quality through the implementation of method improvement and work measurement techniques. Cost reduction; worker performance, health and safety improvement. Industrial applications.

IE 440 Nonlinear Models in Operations Research (3+0+0) 3 ECTS 6
(Yöneylem Araştırmasında Doğrusal Olmayan Modeller)
Nonlinear programming; methods for one dimensional optimization, convex sets and functions, unconstrained optimization, constrained optimization, first and second order optimality conditions, derivative free methods, basic descent algorithms, convex optimization. Machine learning; perceptrons, self-organizing maps, classification, clustering, support vector machines for classification and regression.
Prerequisite: IE 203.

IE 441 Planning for Engineers (3+1+0) 3 ECTS 6      
(Mühendisler için Planlama) 
Analysis of the planning process. Multiple objective and goal programming; identification and discussion of the efficient frontier. Data envelopment analysis. Project management; critical path based methods; random activity times; mathematical programming formulation; renewable and non-renewable resource constraints; risk analysis. Case studies.
Prerequisite: IE 202.

IE 442 Enterprise Information Systems Modeling (3+0+0) 3 ECTS 6
(Kurumsal Bilişim Sistemleri Modellemesi)
Competitive business environment and information systems; enterprise reference architectures. Business analysis methodologies and modeling languages; database management systems and SQL. Basic application architectures such as client-server, N-tier, XML and web services, and application integration.
Prerequisite: IE 201.

IE 443 Engineering Investment Decisions (2+0+2) 3 ECTS 6
(Mühendislik Yatırım Kararları)
Description of the organization and management, market study, choice of production capacity, project engineering, cost and revenue estimation, financing and preparation of financial tableaus, economic analysis, case studies.
Prerequisite: IE 341 or consent of the instructor.

IE 450 Stochastic Models in Operations Research (3+1+0) 3 ECTS 6
(Yöneylem Araştırmasında Rassal Modeller)
Markov chains; state dependent distribution, transition matrix, transient and steady-state analysis. Poisson process; interarrival and waiting time distributions, conditional arrival time distribution. Markov processes; steady-state analyis. Markov decision processes; infinite horizon analyis, exhaustive enumeration, policy iteration. Queueing models; Markovian analyis, non-Markovian service systems, performance measures. Inventory models.
Prerequisite: IE 305.

IE 456 Graph Algorithms and Applications (3+0+0) 3 ECTS 6
(Çizge Algoritmaları ve Uygulamaları)
Graph representation, graph search, shortest paths, minimum spanning tree, Eulerian graphs, Hamiltonian graphs, Traveling Salesman Problem, network flows, Ford-Fulkerson algorithm for maximum flow, maximum flow at minimum cost, feasible flows, Menger’s connectivity theorems, maximum matching and minimum vertex cover, assignment problem, stable matchings, edge and vertex coloring with applications, perfect graphs, planar graphs, Brook’s theorem, heuristics for vertex coloring.

IE 461 Energy Policy and Planning  (3+0+0) 3 ECTS 6                         
(Enerji Politikaları ve Planlaması)
Investigation of essential energy policy issues and the development of necessary skills for planning. Energy market restructuring and climate change mitigation. Real options theory based on dynamic programming to address uncertainty in a competitive marketing environment. Basic concepts and approaches in energy and environmental policy modeling. Methodological difficulties in the integration of the top-down and bottom-up approaches with strengths and weaknesses of hybrid equilibrium models. Case studies using the General Algebraic Modeling System (GAMS) software.
Prerequisite: IE 202 or equivalent.

IE 480 -IE 489 Special Topics in Industrial Engineering (3+0+0) 3 ECTS 6
(Endüstri Mühendisliğinde Özel Konular)
Special topics in Industrial Engineering selected to suit research interests of the faculty.

IE 490, IE 493 - IE 499 Special Studies (3+0+0) 3 ECTS 6
(Özel Çalışmalar) 
Special topics in Industrial Engineering selected to suit the interests of the individual students. The course is designed to give student an opportunity to do independent work at an advanced level.

IE 491 Special Projects (0+0+6) 3 ECTS 6
(Özel Proje)   
Design or research projects will be the main topics. Students with special interest and qualifications may be permitted to take this course.

IE 492 Project (0+0+8) 4 ECTS 8
(Bitirme Projesi)  
Listed under Engineering Core Courses.