Course Pages
Credit Information: 3
Description:
The basic concept of strategic thinking, formulation of strategies for sustainable competitive advantage, the measurement of corporate as well as individual performance in implementation of the strategies. Theoretical overview enriched by success and failure stories. Workshops and assigment for enhancing understanding
web: http://moodle.ie.boun.edu.tr/
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Credit Information: 3
Description:
Safety engineering is devoted to the application of scientific and engineering principles and methods to the elimination and control of hazards. This course covers the following: fundamentals of safety; scientific and engineering bases of safety; safety analysis methods; systems safety; hazards and their control methods; managing safety and health; case studies.
web: http://moodle.ie.boun.edu.tr/
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Credit Information: (3+1+0) 3
Description:
Introduction and orientation to IE: concepts and approaches; process analysis and modeling through cases; production and service systems; basic data analytics; engineering ethics.
web: http://moodle.ie.boun.edu.tr/course/view.php?id=11
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Credit Information: (2+0+2) 3
Description:
Introduction to object-oriented analysis and design: data encapsulation, inheritance, polymorphism, software engineering methodologies, UML; introduction to C++ programming language: class, inheritance, polymophism, 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.
web: http://moodle.ie.boun.edu.tr/
Offered by:
Z. Caner Taşkın
Syllabus:
Credit Information: (3+0+2) 4
Description:
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; integer linear programming: modeling
Prerequisite: MATH 201.
web: http://moodle.ie.boun.edu.tr/course/view.php?id=4
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Credit Information: (3+0+2) 4
Description:
Integer programming: modelling, branch-and-bound method, cutting plane algorithm, linearization, preprocessing and node/variable selection in branch-and-bound; deterministic dynamic programming; nonlinear programming: modeling and examples, unconstrained and constrained optimization; Markov chains; Poisson process and exponential distribution; queueing theory.
Prerequisite: IE 202, IE 255
web: http://moodle.ie.boun.edu.tr/
Offered by:
Z. Caner Taşkın
Syllabus:
Credit Information: (3+1+1) 4
Description:
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
Prerequisite: PHYS 121, CHEM 105.
web: http://moodle.ie.boun.edu.tr/
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Credit Information: (3+1+0) 3
Description:
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.
web: http://moodle.ie.boun.edu.tr/course/view.php?id=42
Offered by:
Wolfgang Hörmann
Syllabus:
Credit Information: (3+0+0) 3
Description:
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.
web: http://moodle.ie.boun.edu.tr/course/view.php?id=140
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Credit Information: (3+0+2) 4
Description:
Dynamic programming; introduction to stochastic processes; queueing models; reliability models; Markov decision processors; value iteration method; successive approximations and policy improvement algorithms; maintenance and reliability models; game theory.
Prerequisite: IE 255 or equivalent.
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Credit Information: (3+0+2) 4
Description:
Basic concepts of discrete-event simulation modeling/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.
web: http://moodle.ie.boun.edu.tr/course/view.php?id=110
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Credit Information: (3+0+2) 4
Description:
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.
Offered by:
Hakan Yaşarcan
Syllabus:
Credit Information: (3+0+2) 4
Description:
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.
Prerequisite: IE 256 and IE 202.
web: http://moodle.ie.boun.edu.tr/course/view.php?id=96
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Credit Information: (3+0+2) 4
Description:
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.
web: http://moodle.ie.boun.edu.tr/course/view.php?id=41
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Credit Information: (3+0+2) 4
Description:
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.
web: http://moodle.ie.boun.edu.tr/course/view.php?id=59
Offered by:
Hakan Yaşarcan
Syllabus:
Credit Information: (3+1+0) 3
Description:
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
web: http://moodle.ie.boun.edu.tr/
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Credit Information: (3+1+0) 3
Description:
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.
web: http://moodle.ie.boun.edu.tr/
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Credit Information: (2+0+2) 3 ECTS 6
Description:
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, cyber-physical systems, connected smart factories. Lab applications including CAD/CAM integration, 3D printing, robot programming, modelling, simulation and real-time operational control of advanced manufacturing systems.
Prerequisite: IE 306 or equivalent (co-requisite)
web: http://moodle.ie.boun.edu.tr/
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Credit Information: (2+0+2) 3
Description:
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.
Credit Information: (2+0+2) 3
Description:
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.
web: http://moodle.ie.boun.edu.tr/course/view.php?id=2
Offered by:
Könül Bayramoğlu Kavlak
Syllabus:
Credit Information: (2+0+2) 3
Description:
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.
Credit Information: 3
Description:
This course will examine methods that proved to be useful in recognizing patterns and making predictions. We will review applications and provide an opportunity for hand-on experimentation with data mining algorithms. At the end of the course students will have developed an understanding of the strengths and limitations of popular methods to solve regression and classification problems in data mining.
web: https://moodle.bogazici.edu.tr/
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Credit Information: (3+0+1) 3
Description:
Principles of ergonomics and human factors; their applications to the design and management of industrial systems. Human performance; human-technology interaction; job, work environment and product design; occupational safety and health. Methods development, work measurement and work standards. Productivity and quality improvement; cost reduction. Industrial applications.
web: http://moodle.ie.boun.edu.tr/course/view.php?id=38
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Description:
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 305
web: http://moodle.ie.boun.edu.tr/course/view.php?id=130
Offered by:
İ. Kuban Altınel
Syllabus:
Credit Information: (3+0+1) 3
Description:
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.
Credit Information: (2+0+2) 3
Description:
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.
Description:
The objective of this course is to give an intermediate level of understanding in modeling and optimization of systems presenting stochastic behavior. To this end first the general modeling tools are presented. Then discrete and continuous time Markov chains are discussed in detail and Markov decision processes are introduced. In the second phase of the course Markovian analysis and optimization applications in queueing and inventory systems are studied.
Prerequisite: IE 305 or equivalent
web: http://moodle.ie.boun.edu.tr/
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Credit Information: (3+0+0) 3
Description:
Human capital concept; people, productivity and the quality of working life; evaluation of human resources management; legal and social contexts of personnel decisions; analyzing and designing jobs; determining human resources requirement; recruiting; screening and selecting employees; orienting and training employees; identifying and developing management talent; appraising employee performance; managing careers; compensation management; assessing the costs and benefits of personnel activities; international dimensions of human resources management.
Description:
The primary objective of this course is to provide necessary tools of graph theory in order to handle various engineering problems. Students are expected to acquire the ability of modeling real life problems as graph theory problems and expressing their ideas using graph theory terminology.
web: http://moodle.ie.boun.edu.tr/course/view.php?id=129
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Description:
This course investigates the substance of essential energy policy issues and provides the necessary skills for their planning. Electricity market restructuring and climate change mitigation are addressed as today’s two distinct energy policy challenges. Fundamentals of electricity markets are explored in the first part of the course. The market clearing mechanism for electricity trading in a competitive environment is elaborated with focus on the underlying microeconomic theory. Short- and long-run equilibrium conditions in the electricity market are studied. The grid and reliability issues are explored together with the implied formulations for modeling power flow and auctions. An interactive power market simulation game is included to complement the understanding of theoretical issues. In the second part of the course, the basic concepts and different approaches used in energy and environmental policy modeling are explored ranging from technologically detailed bottom-up energy models to top-down policy models. Modeling energy flow, optimization and equilibrium, modeling the macroeconomy and representing energy-economy interactions form the learning objectives of this part. Particular emphasis is on the theory of production in general and constant elasticity of substitution (CES) type production functions in particular.
Prerequisite: IE 202
web: http://moodle.ie.boun.edu.tr/course/view.php?id=21
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Description:
This course focuses on modeling and simulation of flexible manufacturing systems and aims to introduce the students to the research conducted in BUFAIM- Flexible Automation and Intelligent Manufacturing Laboratory. After providing an understanding of the nature and context of flexible manufacturing systems, their components and the real-time operational decisions required for controlling such systems, the focus is set on the FMS simulator software developed and used in BUFAIM together with potential research areas. Using object oriented (OO) methodology the software is analyzed using reverse engineering approach and students are asked to design and implement some new features and enhancements that will give the software new directions for potential research.
Prerequisite: IE306, IE201
web: http://moodle.ie.boun.edu.tr/
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Credit Information: (3+0+0) 3
Description:
This special course focuses on real-time control of robotic manufacturing systems and aims to introduce the third and fourth grade IE students to the state-of the-art issues in the area of advanced manufacturing through hands-on experience in BUFAIM- Flexible Automation and Intelligent Manufacturing Laboratory. After getting introduced to several automation concepts such as industrial robots, 3D printers, automated guided vehicles and RFID, and gaining an understanding of flexible manufacturing and the real-time operational decisions required for controlling such systems, the focus is set on the usage of the robot arms in BUFAIM Model Factory, their controller software, and the interaction between the real-time Shop Floor Control (SFC) system and the robot controllers. During the project, students will design and implement robot control programs and their interface with the existing SFC software in BUFAIM, so that the Model Factory operates seamlessly and enables new directions for potential research within the context of the Industry 4.0 concept. The students (individually or in teams) are expected to analyze the given case, come up with a good design, implement, verify and document their solution, and present it.
Prerequisite: IE 201
web: http://moodle.ie.boun.edu.tr/
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Description:
This course is designed to provide students with the tools and knowledge necessary to conduct a simulation supported analysis of socio-technical problems using agent-based models (ABMs). Students will gain understanding and awareness of the fundamental differences of agent-based modeling from other simulation modeling approaches, and nature of problems/objectives that ABMs fit the best. Besides, students will develop competency in building ABMs, analyzing and interpreting results from these models, and communicating a complete simulation supported analysis cycle to peers/clients. Example models used during the semester will be drawn from social, economic, environmental, industrial, energy and logistic/transportation problems. For the term project, students will go through a model supported analysis process as they develop an ABM in order to analyze a problem from their own areas of interest.
web: http://moodle.ie.boun.edu.tr/
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Description:
This course is organized to introduce the students to Pricing and Revenue Management by focusing on the relationship between price, demand and supply. The scope of pricing and revenue optimization is to set and update the prices for each combination of product, customer segment, and channel. Main topics covered are segmenting customers according to their willingness-to-pay, allocating limited supply capacity, and customizing pricing offers to each customer segment to satisfy different objectives for the firm.
web: http://moodle.ie.boun.edu.tr/
Offered by:
Halil Ozan Gözbaşı
Syllabus:
Credit Information: (3+0+0) 3
Description:
Human-computer interaction (HCI) is concerned with the theory, research and practice of designing user experiences for all types of computerized systems. Topics include theories and models; interaction design process and principles; hardware, software and human aspects of interaction design; usability, user experience (UX) and interface design issues; prototyping and concrete design; evaluation methods; research methods in HCI; and some topics such as AI, IoT, ubiqutous computing and human-robot interaction.
web: http://moodle.ie.boun.edu.tr/
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Credit Information: ((1-3)+0+0) 3
Description:
Design or research projects will be the main topics. Students with special interest and qualifications may he permitted to take this course.
Credit Information: (0+0+8) 4
Description:
Listed under Engineering Core Courses.
Credit Information: (2+0+2) 3
Description:
Definition, perception, assessment, response dimensions of Risk Analysis and Management, as well as organizatonal aspects are focused. Assessment and analysis tools, such as, risk assessment matrices, fault trees, simulation and statistical models are elaborated. Case studies and discussion papers, especially on implementation issues, and selected from diverse applicaton areas are discussed.
Prerequisite: IE 256, IE306 (or equivalents)
web: http://moodle.ie.boun.edu.tr/course/view.php?id=92
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Description:
An overview on basic concepts of investment science including fixed income instruments, the classical Markowitz approach for stock portfolio selection and a very short introduction to forwards, futures and options. At the end of the course the students will be able to solve practical investment problems using the above mentioned classical approaches. The software used for the practical calculations is R.
Prerequisite: IE 341
web: http://moodle.ie.boun.edu.tr/course/view.php?id=149
Offered by:
Wolfgang Hörmann
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