Course Content

Science as a human activity. Engineering. History of engineering. Emerge of industrial engineering. Historical development of industrial engineering. Technology. Industrial engineering and technology. Topics in industrial engineering: History and prospects. Overview of IE curriculum at METU.

Course Content

Computer arithmetic; vectors and matrices; numerical, symbolic, and graphical capabilities of MATLAB; execution control and data structures,user-defined and built-in functions; developing algorithms and programming; recursion, searching and sorting; complexity of algorithms and performance analysis; function approximation, integration, and differentiation by numerical methods; solution of systems of equations; graph search and network algorithms; random number generation and statistical applications; visualization and plotting of results.

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Basics of financial accounting. Preparation of balance sheet, income statement and flow of funds statement. Inventory valuation and depreciation methods. Basics of accounting. Definition of costs. Absorbtion cost techniques, with an emphasis on allocation of overhead in manufacturing organizations. Budgeting. Variance Analysis. Cost-Volume-Profit Analysis. Pricing decisions, special decisions based on incremental analysis.

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History and methodology of operational research. Introduction to linear programming and graphical solution. Linear programming models and interpretation of solutions. Simplex method, sensitivity analysis and duality. Multi-criteria decision making. Game Theory.

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Transportation and network models. Solution algorithms. Project scheduling. Integer programming models. Weak and strong formulations. Cutting plane and branch and bound algorithms. Heuristic approaches to large-scale problems. Introduction to nonlinear programming. Karush-Kuhn-Tucker optimality conditions.

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Elements of probability. Random variables and distibutions. Two and higher dimensional random variables. Mathematical expectation. Generating functions. Limiting and sampling distributions.

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Descriptive statistics, statistical estimation, hypothesis testing, simple and multiple linear regression, introductory experimental design with emphasis on industrial engineering applications.

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A minimum of four weeks (20 working days) training in manufacturing involving observations of the production system and the discussion in detail of the various aspects of the production process. The training is based on the content of the Summer Practice Manual.

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Analysis and design of information systems with special emphasis given to production sub-systems. Basic information concepts, data processing technology and its applications. Information systems development methodology in terms of systems analysis, design and implementation. The information requirements of production systems in modular form.

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Introduction to production and service planning. Facilities location and layout. Manufacturing systems and related soft technologies. Inventory control. Forecasting.

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Systemic issues in supply chain management. Production planning with emphasis on APP, MPS, capacity planning and MRP. Machine scheduling, cyclic schedules and scheduling in services. Distribution systems and routing. Design and development of services and service delivery systems. Managing capacity and demand in service systems. Service productivity and measurement performance.

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Introduction to human work systems and layout. Systematic layout planning. Manual work design principles. Industrial safety and accident prevention. Material handling and werehousing. Computer-aided layout planning. Method study and work measurement techniques.

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Economic analysis for engineering and managerial decision making. Techniques for evaluating the worth of prospective projects, investment oppurtunities and design choices. Interest and time value of money, methods for evaluation of alternatives: present worth, annual equivalent worth, rate of return, benefit cost ratio method, and payback method. Replacement analysis, inflation and cost estimation. After tax economic analysis, and methods of financing. Sensitivity and risk analysis.

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Introduction to stochastic processes.Discrete-time Markov chains. Mean first passage times. Steady-state analysis. Basics of queueing theory. Types of queues. Deterministic and stochastic dynamic programming.
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Quality of products/services and quality characteristics. Concepts of quality of design and quality of conformance. Quality costs. Total quality management and quality standards. On-line and off-line quality control activities. Statistical process control. Control charts. Capability analysis. Measurement system analysis. Acceptance sampling. Six sigma programs. Development and design of quality products and processes. Basic reliability concepts and approaches.

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Discrete event simulation methodology and model building. Modeling with a simulation language. Selecting input probability distributions. Random number and random variate generation. Statistical analysis of the simulation output. Basic issues in the design, verification and validation of simulation models.

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A minimum of six weeks (30 working days) training in a manufacturing industry, involving the observation and discussion in detail of the various aspects of production. The student is also expected to identify, define, formulate and to offer a solution methodology for an industrial engineering problem. The training is based on the content of the Summer Practice Manual.

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Fundamental concepts and terminology. Formulation of employment contracts. Health and safety at work, occupational accidents, employers` liabilities. Collective bargaining, collective agreement. Conciliation and arbitration, strikes and lock-outs. Social security and legal provisions.

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Managerial function related to planning, organizing, staffing, directing and controlling engineering organizations. Techniques of management, the matrix system of management, motivation, appraisal systems, participative management.

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An introduction to the methodology of operational research. Survey and examples of OR models. Basics of linear programming. Networks, integer programming and queuing models. Dynamic programming. (Offered to non-IE students only).

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Systems theory and organizations. Goals, values and measures of effectiveness for manufacturing and service organizations in government and industry. The basic structure of an organization and its variations. Determinants of structure. The life cycle of an organization and management of change.

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Demand management decisions.Quantity-based revenue management, single-resource and multiple-resource capacity control, control mechanisms. Static and dynamic models for single-resource control. Exact and approximate models for multiple-resource control. Static and dynamic overbooking models.

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Defining the supply chain and components of the supply chain. Design issues in supply chain management. Logistics network design and inventory planning. Value of information. Competitive and collaborative relations among participants. Supply chain integration. Warehouse operations management.

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Structure of service producing systems. Basic design and operational concepts in service and process selection, capacity planning, facility planning, work design, aggregate service planning, scheduling, service quality and information systems.

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Definitions. Deterministic inventory problems. Deterministic inventory problems with constraints. Unconstrained, infinite horizon, stochastic demand continuous review problems. Single period, stochastic demand problems. (s,S) policies for periodic review, infinite horizon problems.

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Informing senior students about professional life in industrial engineering. Depending on lectures given by practicing industrial engineers, establishing the link between the courses the students have taken during their education and application of industrial engineering techniques and approaches in real-life cases.

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Scheduling and sequencing problems. Basic formulation. Single processor, multi processor scheduling procedures and solution approaches.

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Introduction to the planning and the design of manufacturing facilities. Organization of data for facilities design. Analysis of production plans and processes to compute equipment and manpower requirements. Identification of production support activities and computation of related facilities requirements. Design of layout and materials handling systems. Facilities location.

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Production line design. Just-in-time(JIT) production systems. Optimized production technology (OPT). Flexible manufacturing systems (FMS). Cellular Manufacturing Systems

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Automated manufacturing and production management in automated manufacturing. Performance issues and stochastic modeling of automated manufacturing. Factory dynamics in production lines.

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Work system, task and job demand will be analyzed in different systems to establish adequate guidelines for work design to minimize stress and strain in the work environment.

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The human element in information systems design. Information theory, decision making process and human communication. Introduction to cybernetics.

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The effect of thermal factors, noise, vibration, illumination, control display design, age and shift work on the performance of human beings will be explored.

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Ergonomical issues of modern industrial society are introduced. Problems of automation, humanization of work environment, shift work, disabled and aged workers in industry are discussed.

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Modeling economic factors bearing on design and decision-making. Basic time value models. Methods of evaluating alternatives. The effect of taxes and depreciation on investment decisions. The impact of inflation. Measuring costs in industry. Analysis of public projects. Risk and sensitivity analysis in engineering economic analysis. (Offered to non-IE students only).

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Investment and financing decisions of the firm. Cost of capital and selection of a minimum attractive rate of return. Economic analysis under risk and uncertainty. Effects of inflation and construction and use of index numbers.

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Kuhn-Tucker optimality conditions and review of LP duality. Optimization models to study problems of auctions, decentralization, vertical integration in the firm, industrial programming and activity analysis in a partial equilibrium framework and financial planning.

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Maximizing expected monetary value. Utility theory. Judgmental probabilities. Value of information. Normal form of analysis. Risk sharing. Multi attribute utility theory.

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The aim of this course is to develop better skills in building and understanding mathematical modeling. Deterministic models in the areas of transportation, distribution, location, production and economic planning are analyzed.

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Advanced techniques which are not covered in elementary operational research courses are covered. Linear, nonlinear, integer and dynamic programming algorithms.

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Basic network flow problems such as shortest path, minimal spanning tree and maximal flow problems. Principles of project management. Network representation and terminology. Network planning with respect to costs and durations. Resource constrained network planning. Financial planning and cost control. Project scheduling with probabilistic networks.

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The objectives of this course are to introduce the students combinatorial reasoning and modeling; to show how to make systematic analysis of different possibilities; to equip them with the roadmap for the exploration of the logical structure of a decision problem; and to expose them to applications to many real life decision problems from algorithmic viewpoint.

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Models and basic solution methods for the network flows motivated by transportation applications. Traveling salesman problem. Arc routing problem. Vehicle rounting problem. Extentions and applications.

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Introduction to data mining .Data types. Classification Analysis: Rule Based, Nearest-Neighbour and Bayesian Classifiers, Support Vector Machines. Association Analysis: Rule Generation. Cluster Analysis: Center-based Clustering, Hiearchial , Density-based and Fuzzy Clustering. Cluster Validation, Anomaly Detection, Case studies.

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An overview of forecasting. Available methodologies, comparing individual methodologies, selecting a methodology and designing a forecasting system that fits the specific management - decision making requirements of the organization. Smoothing techniques, adaptive filtering, simple and multiple regression and correlation analysis, time series forecasting, Box-Jenkins methods, Input-Output and Econometric models.

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Reliability, failure rate, mean time to failure; lifetime distributions, expected remaining lifetime; structure functions for different system configurations; fault tree analysis; improving/optimizing system reliability with cost considerations including warranty problems; network reliability; reliability bounds; maintenance and replacement policies for Markovian aging equipment.

Course Content

Framework for stochastic optimization. Application areas. Structural properties of the policies. Decision criteria. Computational methods: value iteration, policy improvement, linear programming. Real-life case studies.

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Definition of technology concept in production and service sectors. History of technological developments on a sectoral basis. Relationships with science and engineering. Models for technology development: techno-parks, science parks, research institutes. Organizations and media toward technology surveys and technology transfer. Role of technology in national economic development and global competition.

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Retail business models; retail supply chain design; assortment optimization; markdown pricing and promotion management, customer relationship management; multi-channel management and electronic retailing.

Course Content

Inquiry and research. Methods of science. Fundamental systems concepts and notions. Systems thinking as a mode of inquiry; historical and methodological account. Contrasting and clarifying the systems position vis-à-vis science. The relation between systems thinking and operational research. Principal stains of systems thinking and the systems approaches.

Course Content

Inter-enterprise relations, theories of the firm and external cooperation, boundaries of the firm, organization and structure of networks, scientific an technological collaboration, production networks, strategic alliances, innovation networks, complex networks, theories of regional economy, clusters, cluster analysis, development.

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Introducing the rapidly proliferating applications of decision theory in health services sector - a fast growing sector itself. Measurement of costs & value of health outcomes; health-related quality of life issues; evaluations; modeling value & time preferences(patient, physician, provider) and uncertainty in medical decision making – for research policy purposes.

Course Content

Macroeconomic framework of industrial activity. Key macro indicators. Classification schemes for economic activity. Long-term trends in major sectors. Surveys and censuses for industrial activity. Key industry indicators. Sources for monitoring developments in industries. Analysis of selected industries. Brief remarks on history and future of industry. Knowledge of principles of economics and statistics is required.

Course Content

The total quality concept. Continuous quality improvement. Quality control activities (off-line, on-line). Quality loss. System design. Parameter design. Taguchi method. Tolerance design. Quality function deployment. Quality standards. Quality awards.

Course Content

Basic concepts in modern finance. Fixed income securities, yield curve and interest rate models. Financial risk management, derivative instruments, option pricing, value-at-risk.

Course Content

Systems design and design issues in industrial engineering. Team experience in design projects. The conception, structuring and formulation of a real-life system design problem that draws upon and synthesizes knowledge accumulated throughout the IE degree program, underlying ethical and other social aspects.

Course Content

The second of a two-course sequence in system design project. Analysis, formulation, modeling, validation and implementation stages of system design.

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Principles of sustainability. Industrial, economic, environmental, agricultural, and urban sustainability. Sustainable development. System view of sustainability. Decision making and sustainability.

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Program of research leading to M.S. degree, arranged between student and a faculty member. Students register to this course in all semesters starting from the beginning of their third semester while the research program or write-up of thesis is in progress. (F?S)*

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Heuristic search approaches for solving difficult combinatorial problems. Categorization of heuristic search techniques. Traditional heuristics for combinatorial optimization problems. Meta heuristics including simulate annealing, tabu search and evolutionary algorithms. Constraint handling techniques. Computational complexity of heuristics.

Course Content

Methods and techniques of strategic management, that is, formulation, implementation and evaluation of actions that enable an organization to achieve its mission and objectives. Strategic Choice and Decision Making, Strategy Implementation Process Structure and Planning Style, Strategy Review, Evaluation and Control.

Course Content

Price-response function, price response with competition, price differentiation, volume discounts, opportunity cost, variable pricing, markdown pricing, first-price auctions, second-price Auctions, English suctions, vickrey auctions, booking control, protection levels, network bid price control.

Course Content

The major difference between closed-loop supply chains and traditional (forward) supply chains is for a forward supply chain, the customer is at the end of the processes, and for a closed-loop supply chain there is a value to be recovered from the end-user. There are many different types of closed-loop supply chains in practice: production, distribution, commercial returns, repair/replacement, end-of-use/life closed-loop supply chains. The basic drivers for companies to consider closing their supply chains are legislation, environmental consciousness, profit, and customer expectations. Many closed-loop supply chains have a number of characteristics making their design, planning and control requirements different from those of traditional supply chains. Network design and operation, inventory and production planning and disassembly scheduling and sequencing are the fundamental issues for closed-loop supply chain design and operation.

Course Content

Decision-making and information management issues in supply chains with emphasis on integrating procurement, operations, and logistics; stages from raw materials to customer demand, with emphasis on quantitative models of supply chain.

Course Content

Analysis of some specific problem areas within the context of planning and scheduling of production activities. Definition, formulation and available solution procedures for aggregate planning, lot sizing. Scheduling in manufacturing systems, scheduling in service systems, design and operation of scheduling systems.

Course Content

Principles of project management. Representation of project operations: project breakdown, network representation and terminology, network data. Network planning with respect to costs and durations: critical path analysis, linear time cost trade-off analysis. Resource-constrained network planning, resource scheduling, resource leveling. Financial planning and cost control in project systems. Project scheduling with probabilistic networks.(R)

Course Content

Formal and heuristic techniques of layout and location analysis, philosophical aspects of facilities planning in general. Special topics such as design of non-manufacturing facilities and warehouse automation.(R)

Course Content

Structure of production-inventory systems. Deterministic and stochastic ordering decision models in continuous and periodic review systems. Coordinated replenishment of multiple items.(R)

Course Content

Physical distribution, after-sale services (product repair and maintenance), procurement, logistic performance and cost control, and logistic concepts of product systems design. Overview of material handling. Packaging facilities repair and maintenance and automation in logistics.(R)

Course Content

This course is designed to promote interest in modern manufacturing systems. Various papers and references are presented related to FMS and CIM. State of-the-art papers are discussed. (R)

Course Content

Displays and controls. Human decision making process. Information theory. Human communication essentials. Cybernetics. Control systems. Behavioral control theory.(R)

Course Content

Fatigue and its relations with work load stress and strain, objective determination of physical and mental work load; laboratory testing procedures and their field applications, use of radio telemetry instrumentation for fatigue assessment. (R)

Course Content

Ergonomical issues of modern industrial society are introduced. Problems of automation humanization of work environment, shift work, disabled and aged workers in industry are discussed.(R)

Course Content

Introduction to Quality Engineering. Parameter design by Taguchi design of experiment, Taguchi's Loss Function. Tolerance design and tolerancing. Online feedback quality control. Online process parameter control.(R)

Course Content

A review of quantitative microeconomics theory covering demand, production and market structures. A selection of medium -to -long term issues such as competition and pricing. Concepts of equilibrium and welfare. Modern topics in industrial economics such as the transaction cost and property rights approaches and government regulation.

Course Content

Total quality concept. Total quality management decision. Customer focus. Quality organization. Team formation and problem solving. Policy deployment. Quality through planning. Design and control. Quality standards and award models. Real life applications and cases.

Course Content

Linear programming in matrix form. The revised, dual, and primal-dual simplex methods. Bounded variables. Duality and sensitivity analysis. The transportation and assignment algorithms. Basic concepts of decomposition.(F/S)

Course Content

The linear minimal cost flow problem and its solution by the network simplex algorithm. Maximal flow, shortest route and circulation problems. The integer programming problem and its solution by branch and bound and decomposition methods. Lagrangian relaxation.(R)

Course Content

Review of convex sets and functions. Local and global optima. Basic methods of constrained optimization. Lagragian duality.(R)

Course Content

Formulation of the general multiobjective programming problem, classification of multiobjective programming methods; generating techniques, preference oriented methods, multiple-decision-maker methods. Multiobjective analysis of certain problems in public sector.(R)

Course Content

Introduction to modeling under uncertainty. Basic properties of two-stage stochastic linear programs. Stage-wise and scenario-wise decomposition methods for solving two-stage stochastic linear programs. Value of capturing uncertainty. Chance-constrained stochastic programs. Multi-stage stochastic linear programs. Stochastic integer programs. Bounding and sampling methods.

Course Content

Markov chains: Transient and steady state behavior, First Passage times. Markov process: Transient and steady state behavior, First Passage times and phase type distributions. Queuing networks. Markov decision process (MDP): Continuous and discreet time models, MDP as linear programs, MDP under constraints, Maintenance applications. Reliability and maintenance problems: Definition, System configurations, Reliability improvements with cost considerations, Reliability bounds.

Course Content

Probability spaces and classification of stochastic processes. Markov chains with discrete and continuous parameter spaces; characterization and limiting behaviour. Birth and death processes and their application to queuing theory. (F/S)

Course Content

The way in which information is used in inference making will be discussed by covering linear statistical models, multiparameter hypotheses, incomplete block designs. Random and mixed models.(R)

Course Content

Computer aided exploration, analysis and classification of data and empirical model building in engineering through the use of descriptive statistics, random sampling, probability distribution fitting, analysis of variance, regression analysis, discrimination and classification and clustering

Course Content

Simulation methodology and its comparison with other techniques, discrete change simulation concepts. Selecting input distributions, random variate generation, statistical analysis of output. Selected applications of simulation.(R)

Course Content

The course concentrates on engineering of organizational processes and systems. The focus is on fundamental redesign of strategic and value-adding business processes. Organizations are modelled as systems in order to gain insight into their structure, processes and performance. This knowledge is used in engineering more effective organizations and information systems to provide value-added support for organizational evolution.

Course Content

Qualitative research methods serving as means to understand complex socio-economic systems. Models and techniques employed for gaining a better understanding and change of human interactions. Theory, methodology and research design in qualitative research. Qualitative performance evaluation in organizations. System dynamics and Delphi technique.

Course Content

The course dwells on the fundamental forces that are expected to shape the industrial engineering in the near future. It is a mostly qualitative umbrella course that combines many diverse topics within a framework of industrial and systems engineering. Brief history of sustainability. Principles of sustainability. Industrial, economic, environmental, agricultural and urban sustainability. Sustainable development. Environmental ethics. Systems view of sustainability. Techniques for modelling complex systems. Criticism and the more negative connotations of sustainability. Globalization and issues of the post-globalized world.

Course Content

This seminar is designed to promote research interest in various areas of IE. Masters students must register and fulfill departmental requirements of the seminar. (R)

Course Content

Program of research leading to Ph.D. degree, arranged between student and a faculty member. Students register to this course in all semesters starting from the beginning of their fifth semester while the research program or write-up of thesis is in progress. (F?S)

Course Content

This course is designed to promote research interest in various areas of IE. References and state-of-the-art papers are discussed. (R)

Course Content

This seminar course is designed to promote research interest in various areas of Industrial Engineering (IE) and Operations Research (OR) including the scientific research methods. It aims to make the students familiar with the IE/OR practice and contemporary issues and create awareness on the ethics in academia and engineering ethics in practice. The PhD students must register and fulfill departmental requirements of the seminar.

Course Content

Course Content

Logic of propositions, discrete variables and 0-1 inequalities. Logic-based modeling of combinatorial optimization problems. Constraint programming, constraint generation, consistency, domain reduction. Search strategies to solve constraint programming models. Integration of constrain programming and mathematical programming, integrated methods to solve combinatorial optimization problems.

Course Content

Qualitative research in understanding what clusters (industrial and service) are, why they exist, how to identify them, how they matter for regional economic development. Clusters as key organizational units for understanding and improving the performance of regional economies. Diagnosis of regional economic strengths and challenges and identification of clusters to shape the region’s economic future. Multidimensional approach for characterizing different types of clusters. Cluster research as a creative and informative mixture of art and science and connecting research with action.

Course Content

Research design in the field of industrial engineering following ethical standards, ethical issues in scientific research, how to write a thesis with ethics, journal types, publication types, citations, plagiarism, how to be a graduate student, how to be a researcher.

Course Content

These code numbers will be used for technical elective courses which are not listed regularly in the catalog. The course contents will be announced before the semester commences.

Course Content

Analytical thinking about designing organizational systems, principles of organizational architecture, understanding of the human and organizational contexts, organizational configuration and complexity, information flow and processing, coordination and control, task design, organizing for innovation and socio-technical context.

Course Content

Course Content

Optimization with multiple objectives. Introduction to Multi-objective Combinatorial Optimization (MOCO). Properties of MOCO problems. Exact Solution Methods for MOCO Problems. Multi-objective Heuristics and Metaheuristics. Interactive Methods.

Course Content

Introduction to humanitarian logistics. Disaster preparedness and response. Humanitarian applications of facility location, inventory prepositioning, and routing. Long term development issues. Modeling for equity and fairness. Soft issues in humanitarian logistics.

Course Content

Risk-Return Analysis, Financial Option Analysis, Real Option Analysis, Linear Programming in Asset/Liabilitiy and Asset Pricing, Integer Programming in Finance, Stochastic Programming in Finance

Course Content

Introduction to game theory, Discussion of different classes of games, Theory and applications of static/dynamic games of complete information games, Applications, Discussion of rationality.

Course Content