• IE62389 Special Topics in Industrial Engineering
  Introduction to the newly emerging issues in the industrial engineering field.
• IE62888 Thesis Research
  Ability required for making a draft, research methodologies, and writting an English paper will be dealt with.Evaluate based on the progress of paper.
• IE63145 System Simulation
  This course introduces the discrete-event simulation and fathoms a simulation-based operations analytics. Topics covered will include discrete-event simulation for modeling and analysis, development of simulations using a high-level programming language, probabilistic and statistical aspects of simulation, and connections to stochastic models and queueing. Applications in services and manufacturing learn the components of process and flow variability, how to measure them, and how to use models to predict their influence on manufacturing performance.
• IE64023 Applications in Artificial Intelligence
  This course covers a variety of artificial intelligence techniques to solve industrial problems. In particular, students will practice the methodology to increase the productivity of the logistics and manufacturing industries using deep learning and reinforcement learning based on artificial neural networks.
• IE64110 Operations Scheduling
  Single machine processing. Constructive algorithms for flowshops and jobshops. Dynamic programming approaches. Branch and bound methods. Integer programming formulations. Hard problems and NP- Completeness. Heuristic methods. Worst case bounds.
• IE65178 Statistical Quality Control
  Theories and applications of statistical Quality Control Techniques: sampling theory, acceptance sampling, control charts, process capability analysis and screening theory.
• IE65388 Supply Chain Management
  "Find out what decisions are needed for supply chain design and management. Learn mathematical models and related theories necessary for effective decision-making from an individual company's viewpoint, and find out how to maximize the value creation of the entire supply chain by control the relationship of various companies from the viewpoint of the supply chain. Furthermore, through thesis research on the latest trends in supply chain management (globalization and sustainability, and technological innovation (blockchain, IoT)), it helps master's and doctoral students explore related research topics."
• IE68717 Mathematical Programming (I)
  This course assumes elementary background in multivariate differential calculus and in linear algebra, plus familiarity with vector/matrix notation and arithmetic. Most students will also have had an introductory course in deterministic operations research that includes at least formulation of mathematical program.
• IE68722 Statistical Models and Analysis
  To learn statistical skill of analyzing real-data using various statistical models, especially regressioin models.
• IE68726 Manufacturing System Design and Analysis
  Various types and characteristics of production planning and control systems. Methodologies to design the structures and the algorithms for the production management system, Difficulties for the implementation of the theories in practices. Topics includes material requirement planning, just-in-time, Toyoda production system, capacity planning, shop floor control, master production scheduling production planning, scheduling, etc..
• IE68728 Facilities Planning
  Analytic methodologies and practical considerations for the facilities design, Location theory for the factory, design procedure for the factory, analytical methodologies, and other considerations such as workers, materials, material handling, storage, equipments, office layout, etc..
• IE68729 Network Theory
  Survey of Solution techniques and problems that have formulations in terms of flows in networks. Max-flow min-cut theorem. Minimum cost flows. Multiterminal and multicommodity flows. Complexity analysis of algorithms and it's drawbacks. polyhedral optimization: branch and bound and lagrangean relaxation.
• IE68730 Investment Decision Analysis
  Economic evaluation of engineering decisions: costs, criteria, time value of money, interest, and equivalence. Economic life analysis. Investment analysis of alternatives with and without constraints. Decision making under uncertainty and risk. Decision tree analysis. Applicable operations research models.
• IE68731 Mathematical Programming (II)
  To find the optimal solution of the nonlinear planning model, understand various search methods, and improve the understanding of the search method by the recent meta-heuristics methods and through various cases.
• IE68731 IE69551 Logistics Systems
  Introduction to the problem definition for various practical problems and the derivation process of decision models for the defined problem. Factory material flow system. Transportation system. Automated material handling systems,etc.
• IE69552 Advanced Manufacturing Process
  Basic concept for machining and assembly process. Integration of production and technology information. Systematization for select of optimal manufacturing process.
• IE72385 Computational Intelligence
  Computational intelligence deals with problems that are difficult to solve with existing mathematical models or methodologies, and refers to a problem-solving methodology developed with inspiration from the intelligence and behavior of various animals and plants, including humans. Its main fields include fuzzy logic, artificial neural networks, evolutionary computation, and swarm intelligence. Recently, it has been used to solve various problems related to industrial engineering, such as a combination optimization problem. This course focuses on various meta-heuristics based on computational intelligence with a focus on solving optimization problems.
• IE73847 Seminar
  Special topics in overall areas of Industrial Engineering such as production planning and control, logistics, operations research, quality assurance. Case studies based on applications to the actual production/service systems.
• IE74411 Data Analytics
  This course provides understanding of basic theory of data processing, data analytics and students learn skills about methodology for data anaytics in their research fields.
• IE74412 Manufacturing Systems Analysis
  Various types and characteristics of production planning and control systems. Methodologies to design the structures and the algorithms for the production management system, Difficulties for the implementation of the theories in practices. Topics includes material requirement planning, just-in-time, Toyoda production system, capacity planning, shop floor control, master production scheduling production planning, scheduling, etc..
• IE74414 Occupational Safety
  This course enables studentes to learn theories of chemical safety, explosion-proof engineering, machine safety, electrical safety, structural safety, system safety engineering, and industrial safety regulations necessary for industrial safety management.
• IE75413 Mathematical Statistics
  "This course will cover various theoretical topics such as basic probability theories, discrete and continuous distributions, conditional distributions, bivariate distributions, approximation technique, point estimates, interval estimates, sampling techniques, statistical hypothesis testing, R language."
• IE75414 Material Handling System
  This course enables students to establish the advanced concepts of operations analysis and optimization in material-handling: 1) travel-distance analsysis and operational time analysis; 2) zoning and coollaboration; 3) batching theory and optimization; and sequence theory and optimzation. The course introduces the quantitative models of material handling operations, quantifies their impacts on the operations performance, and studies a large-scale optimzation and a dynamic optimization on virtual manufacturing environments.
• IE75415 Intelligent Manufacturing Systems Engineering
  Survey of human factors engineering emphasizing the systems approach to workplace and machine design. Discussion of basic human factors research and design methods, visual processes and design methods, selection of statistical techniques for application to human factors data, visual and auditory processes, display and control design, and effects of environmental stressors on humans.
• IE75416 Smart Factory Technology
  Cultivates the ability to implement production systems to be constructed in virtual reality according to the purpose of use of the manufacturing system, products to be produced, and production conditions. For this purpose, makes the components of the production system modeled and selected according to the purpose of use in the cyber environment. And conducts case studies on the use of IT technology.
• IE75417 Advanced Process Planning
  Process design of machining parts, analysis of precision of machining, work design of machining parts processing, group technology, and approaches of automatic process planning are identified. And learn about algorithm, knowledge base process plan, and integration of process plan and schedule plan.
• IE75418 Reliability & Safety Management
  ◦ The data based reliability covers the various analysis methods of reliability and maintenance optimization and the main topics studied
       as follows;
    - Basicsofstatisticalanalysis,maximumlikelihoodestimation,statisticalanalysiswithR
    - Analysisofreliabilitydata
    - Designandanalysisofacceleratedlifeanddegradationtests
    - Analysisoffileddataandmaintenanceoptimization
  
• IE75419 Probability Models and Analysis
  Poisson process, regeneration process, and Markov process are studied, and based on this, the Markovian atmospheric system, M/G/1 and G/M/1 related systems, and atmospheric network are studied.
• IE75421 Big Data System
  The class provide theory of recent information system design based on concepts, and give opportunities to exercise real system design.
• IE75422 Process Analytics
  This course enables students to learn how to take a process approach to systematically managing and improving business processes and manufacturing processes, and with this approach, develop the ability to manage the entire process life cycle, such as modeling, execution, and management of processes, and deal with process analysis techniques.
• IE75423 Operational Intelligence
  This course enables students to learn how to manage data accumulated in the process of operation and process such as manufacturing and logistics in data of corporate, and through this, cultivate the ability to enable the corporate information system to more intelligently create corporate competitiveness.
• IE75424 Intelligent Interface
  When designing intelligent interfaces such as self-driving cars, aircraft auto cockpit systems, and AI-based process design, this class enable students learn human-robot system design methodologies that can allocate optimal roles between humans and computers, and practices interface design methodologies.
• IE75425 Biomechanics
  This course enables students to learn about the capabilities and limitations of each body part to acquire quantitative evaluation methods for each body part, and learn theories of anthropometrics, static body modeling, dynamic body modeling, workload evaluation method, anatomy, etc..
• IE75426 Design Practicum in Ergonomics
  This course enables students to learn the experimental methodologies necessary for ergonomic experiments, and learn how to operate equipment such as electromyography, motion analysis equipment, and muscle strength meter and analyze data.
• IE75427 Production and Operations Management
  This course introduces various problems in service/production operations within a firm such as inventory management, demand forecasting, and revenue management, and discusses quantitative/qualitative solutions for them.
• IE75429 System Engineering of Remanufacturing
  Analysis of reusing of old product, Procedure of Analysis of reverse design, Analysis of materials and geometrical properties, Grasping of production processes and total life cycle of products, Grasping of reverse steps of remanufacturing.
• DE76010 Intelligent Interface Design
  Survey of human factors engineering emphasizing the systems approach to workplace and machine design. Discussion of basic human factors research and design methods, visual processes and design methods, selection of statistical techniques for application to human factors data, visual and auditory processes, display and control design, and effects of environmental stressors on humans.
• DE76013 Simulation Aanlytics
  This course introduces the discrete-event simulation and fathoms a simulation-based operations analytics. Topics covered will include discrete-event simulation for modeling and analysis, development of simulations using a high-level programming language, probabilistic and statistical aspects of simulation, and connections to stochastic models and queueing. Applications in services and manufacturing learn the components of process and flow variability, how to measure them, and how to use models to predict their influence on manufacturing performance.
• DE76014 Material Handling Analytics
  This course enables students to establish the advanced concepts of operations analysis and optimization in material-handling: 1) travel-distance analsysis and operational time analysis; 2) zoning and coollaboration; 3) batching theory and optimization; and sequence theory and optimzation. The course introduces the quantitative models of material handling operations, quantifies their impacts on the operations performance, and studies a large-scale optimzation and a dynamic optimization on virtual manufacturing environments.
• DE76015 Data Based Reliability
  ◦ The data based reliability covers the various analysis methods of reliability and maintenance optimization and the main topics studied
       as follows;
    - Basicsofstatisticalanalysis,maximumlikelihoodestimation,statisticalanalysiswithR
    - Analysisofreliabilitydata
    - Designandanalysisofacceleratedlifeanddegradationtests
    - Analysisoffileddataandmaintenanceoptimization
  
• DE76016 Industrial AI
  This course covers a variety of artificial intelligence techniques to solve industrial problems. In particular, students will practice the methodology to increase the productivity of the logistics and manufacturing industries using deep learning and reinforcement learning based on artificial neural networks.
• DE76017 Industrial Data Analytics
  This course provides understanding of basic theory of data processing, data analytics and students learn skills about methodology for data anaytics in their research fields.
• DE76019 Operations Management Analytics
  This course introduces various problems in service/production operations within a firm such as inventory management, demand forecasting, and revenue management, and discusses quantitative/qualitative solutions for them.
• DE76019 Operations Management Analytics
  This course introduces various problems in service/production operations within a firm such as inventory management, demand forecasting, and revenue management, and discusses quantitative/qualitative solutions for them.
• DE76023 Seminar in Big Data I
  Throughout this course, a series of seminars will be given by invited speakers on issues of big datas. We invite speakers from local business and industries. The subjects cover supply chain management, maritime industry, aerospace industry, ternimals, road, energy, and railroad systems.
• DE76024 Seminar in Big Data II
  Throughout this course, a series of seminars will be given by invited speakers on issues of big datas. We invite speakers from local business and industries. The subjects cover supply chain management, maritime industry, aerospace industry, ternimals, road, energy, and railroad systems.
• DE76025 Global Supply Chain Management
  Throughout this course, a series of seminars will be given by invited speakers on issues of big datas. We invite speakers from local business and industries. The subjects cover supply chain management, maritime industry, aerospace industry, ternimals, road, energy, and railroad systems.
• DE76026 Process Analytics and Mining
  In order to implement an efficient business process model, all processes for design and tracking, analysis and improvement are studied through relevant methodologies and tools.
• DE76027 Deep Learning and Reinforcement Learning
  Focused study of problem solving using deep neural networks among artificial intelligence. This course looks at deep learning models and application examples, and learn how to solve problems through reinforcement learning.
• DE76030 Patent Data Engineering
  This course covers how to understand technological trends, derive technological implications, and discover new technological opportunities based on multi-dimensional analysis of patent data. It improves the students’ ability to conduct quantitative patent analysis with the application of various data mining and machine learning techniques.
• DE76031 Machine Learning
  This lecture covers basic theory about machine learning. Student will be introduced to the theory of statistical learning that is a fundamental theory for machine learning as well as address basic process for applying machine learning methods to the data. Student also will be introduced to various machine learning models such as linear models, support vector machine, decision tree and ensemble techniques (random forest). Student will practice the machine learning theory with python library.
• DE76033 Operations Modeling and Scheduling
  This course provides an overview of current methods for modeling, scheduling, and analyzing discrete event systems. From the course the students will learn exact and approximate techniques to solve scheduling problems from a variety of manufacturing and service applications.
• DE76034 Regional Industry Innovation
  This course aims to enhance business competitiveness through innovative changes in the local industry and approach to successful transformation of tranditional industries. Students will learn business development models that take into account the regional and industrial characteristics of Busan, and propose their own innovation plans through an in-depth analysis.
• DE76035 Business Model Innovation
  Learn how to create new business through innovation in traditional business. Learn the basic concept of innovation theory and improve understanding of future business innovation plans through representative case studies.
• DE76036 Quality Planning and Analysis
  In-depth learning of the overall process for systematic design and management of quality, improvement and assurance are conducted.Learning based on field cases together with theoretical background research are covered.
• DE76042 Big Data System
  The class provide theory of recent information system design based on concepts, and give opportunities to exercise real system design.
• DE76043 Mathematical Programming
  This course assumes elementary background in multivariate differential calculus and in linear algebra, plus familiarity with vector/matrix notation and arithmetic. Most students will also have had an introductory course in deterministic operations research that includes at least formulation of mathematical program.
• DE76044 Mathematical Statistics
  This course will cover various theoretical topics such as basic probability theories, discreteandcontinuousdistributions,conditionaldistributions,bivariatedistributions,approximationtechnique,pointestimates,intervalestimates,samplingtechniques,statisticalhypothesistesting,Rlanguage.
• DE76045 Statistical Models and Analysis
  To learn statistical skill of analyzing real-data using various statistical models, especially regressioin models.
• DE76046 Thesis Research
  Ability required for making a draft, research methodologies, and writting an English paper will be dealt with.Evaluate based on the progress of paper.
• DE76394 Mobile Intelligence
  Understand the web and internet technologies that are the basic environment for the execution and control of modern business, and solve real-world problems using relevant technology standards and learn about the next generation of web technologies that will come in the future.
• DE76395 Data Driven UX Design
  This course deals with the application of user-generated data in the design process. Specifically, the course introduces the techniques which can acquire and analyze qualitative or quantitative data from user to improve the user experience of product or system. The topics covered include: Semantic Network Analysis, Anthropometric design, A/B testing, human state inference.