| Category | Program | Course/English | Credits |
|---|---|---|---|
| Major, Required | Major, Elective | Special Study of Quality Management | 3 |
| Major, Required | Major, Elective | Theory of Inspection Control | 3 |
| Major, Required | Major, Elective | Advanced Human Factors Engineering | 3 |
| Major, Required | Major, Elective | Applied Design and Analysis of Experiments | 3 |
| Major, Required | Major, Elective | Stochastic Process and its Application | 3 |
| Major, Required | Major, Elective | Reliability Engineering | 3 |
| Major, Required | Major, Elective | Advanced Decisinon Analysis | 3 |
| Major, Required | Major, Elective | Advanced Statistics | 3 |
| Major, Required | Major, Elective | Queueing Theory | 3 |
| Major, Required | Major, Elective | Forecasting Theory and Application | 3 |
| Major, Required | Major, Elective | Decision Support Systems | 3 |
| Major, Required | Major, Elective | Advanced Production System Design | 3 |
| Major, Required | Major, Elective | Advanced Simulation Modelling and Application | 3 |
| Major, Required | Major, Elective | Advanced Production Automation | 3 |
| Major, Required | Major, Elective | Human Reliability | 3 |
| Major, Required | Major, Elective | Advanced Logistics Management | 3 |
| Major, Required | Major, Elective | Applied Linear Programming | 3 |
| Major, Required | Major, Elective | Applied Linear Programming | 3 |
| Major, Required | Major, Elective | Special Study of Statistics | 3 |
| Major, Required | Major, Elective | Manufacturing System Modelling | 3 |
| Major, Required | Major, Elective | System Safety Engineering | 3 |
| Major, Required | Major, Elective | Advanced Aesthetic Engineering | 3 |
| Major, Required | Major, Elective | Advanced Electronic Commerce | 3 |
| Major, Required | Major, Elective | Application of Information and Telecommunications | 3 |
| Major, Required | Major, Elective | Application of Management Information System | 3 |
| Major, Required | Major, Elective | ERP Application | 3 |
| Major, Required | Major, Elective | Supply Chain Management | 3 |
| Major, Required | Major, Elective | Advanced Biological Informatics | 3 |
| Major, Required | Major, Elective | Statistical Analysis and Evaluation | 3 |
| Major, Required | Major, Elective | Theory of Management Strategy | 3 |
| Major, Required | Major, Elective | Product Design Process and Methodology | 3 |
| Major, Required | Major, Elective | Advanced Management of Technology | 3 |
| Major, Required | Major, Elective | Multivariate Analysis | 3 |
| Major, Required | Major, Elective | Academic Writing For Engineering Researchers | 3 |
| Major, Required | Major, Elective | Data Science | 3 |
| Major, Required | Major, Elective | Master Thesis Research 2 | 3 |
| Major, Required | Major, Elective | Advanced Programming | 3 |
| Major, Required | Major, Elective | Machine Learning | 3 |
| Major, Required | Major, Elective | Entrepreneurship | 1 |
| Major, Required | Major, Elective | Introduction of Digital Manufacturing System | 3 |
| Major, Required | Major, Elective | Industry-Academia Collaborative R&D Project 1 | 3 |
| Major, Required | Major, Elective | Industry-Academia Collaborative R&D Project 2 | 3 |
| Major, Required | Major, Elective | Industry-Academia Collaborative R&D Project 3 | 3 |
| Major, Required | Major, Elective | Production System Design and Simulation | 3 |
| Major, Required | Major, Elective | Master Thesis Research 1 | 3 |
| Major, Required | Major, Elective | Operation & Maintenance Systems | 3 |
| Major, Required | Major, Elective | Applied Design of Experiments | 3 |
| Major, Required | Major, Elective | Internship 1 | 3 |
| Major, Required | Major, Elective | Internship 2 | 3 |
| Major, Required | Major, Elective | Manufacturing Process Optimization | 3 |
| Major, Required | Major, Elective | Seminars in Manufacturing Innovation | 1 |
| Major, Required | Major, Elective | Quality Control and Management System | 3 |
| Prerequisite | Major, Elective | Statistics for Engineers | 3 |
| Prerequisite | Major, Elective | Operation Research | 3 |
| Prerequisite | Major, Elective | Production and Operations Management | 3 |
| Prerequisite | Major, Elective | Introduction to Quality Management | 3 |
| Prerequisite | Major, Elective | Introduction to Management of Technology | 3 |
| Prerequisite | Major, Elective | Human Factors | 3 |
In this course, students will study a wide range of management models to plan and rationally manage quality in the design of products and services so that they meet the needs of users and suitability for use.
Students will gain an understanding of sampling and inspection methods according to incoming inspection, in-process inspection, etc., design reliable and economical inspection methods, and ensure rational management across inspections.
Students will measure, analyze, evaluate, and apply human factors relationship variables for the design of man-machine systems.
As an application field of statistics, this course is designed to teach students how to plan experiments in a way that would yield the maximum amount of information for cost-effectiveness and how to determine the optimal working conditions by statistically analyzing the data obtained from the experiments.
The goal is to understand different types of stochastic processes and learn techniques to apply them to measuring and evaluating system performance.
This course is a study of mathematical models and analysis methods for reliability problems, and it covers reliability concepts, reliability functions, and system reliability measurement, prediction, and optimization.
This course is a study of rational decision-making under uncertainty, and aims to provide students with a chance to study various methodologies such as influence diagrams, subjective probability methods, and utility functions and apply them to real-world industrial problems.
The goal is to understand the exploratory data analysis method and cultivate the ability to make optimal decisions using new and advanced analytical techniques by acquiring comprehensive theoretical and practical skills through application examples.
By identifying the analysis method of queueing model, students will examine system evaluation and improvement measures.
In this course, students will study the application of various advanced techniques for forecasting medium- and long-term time series and the design of forecasting systems.
This course covers advanced-level techniques that can be used to relate the value of systems, products, and services to their costs, so that you can understand the operations and operational feasibility based on a technical background.
To support rational corporate decision-making, we focus on the entire process of data collection, storage, preprocessing, and analysis from a data science perspective, learning various decision-making methodologies.
This course discusses theories and techniques for systems for effectively planning, organizing, conducting, and controlling production activities such as production, inventory management, quality control, and the purchase and transportation of materials.
Statistical analysis of input and output data for simulation and statistical techniques and modelling such as variance reduction method and experimental design method are the basic topics in this course. Students will learn network modelling using simulation languages (SLAM, Simscript, etc.) and examples of simulation of discrete events.
The goal is to understand and apply concepts and methods for analyzing and evaluating human error and reliability.
Students will learn concepts, issues, and solutions related to logistics across procurement, production, sales, distribution, consumption, disposal, and recycling
The goal is to understand and apply mathematical modelling of advanced linear planning problems to obtain optimal solutions.
Students will analyze data using statistical methods and study theories and techniques that can be used to apply the results of the analysis in the field.
Students will learn techniques related to modelling manufacturing systems as a step in the analysis to optimize the performance of manufacturing systems.
This course focuses on how to conduct qualitative and quantitative evaluations of various risk factors such as FMEA, FTA, HAZOP, PHA, FHA, MORT, Decision Tree, THERP, etc. and take countermeasures to minimize injuries and losses to humans and damage to equipment and facilities under the constraints related to the man-machine system function, time, cost, etc.
In this course, students will study the engineering techniques applied to design products or systems used by humans through the quantification of human aesthetics or emotions.
Students will learn about the planning, design, construction, and operation of e-commerce, which will drive the economy in the e-business era, and develop the ability to apply e-commerce in practice by focusing on actual cases.
Students will learn to apply various techniques of industrial and management engineering to optimize traffic-related performance in various information and communication systems and networks such as computer, Internet, and mobile communications.
Based on the basic concepts of management information systems, students are given the opportunity to develop the ability to apply or improve MIS by learning MIS architecture and operation case examples of companies and other organizations.
The aim of supply chain management is to reduce the risk of uncertainty by effectively and efficiently managing the flow of materials, etc. This is made possible by managing the flow of materials, services, and information from the supplier, through the process of change within the enterprise and through the distribution chain, to the end user using a total systems approach.
This course concerns a study of engineering techniques required to quantitatively measure and evaluate the characteristics of human sensory functions based on an understanding of biological phenomena, structures, and components from the engineering perspective.
This course covers procedures and methods for statistically processing various data, analyzing and evaluating the results, and applying them in practice. Students will thus obtain knowledge of statistical processing and analysis methods required for writing papers and reports.
This course introduces management innovation techniques (reengineering, benchmarking, SIS, DSS, etc.) and cooperation with other companies in response to rapid changes in the business environment, and cultivates practical application skills necessary for the establishment of management strategies in an actual corporate environment.
This course introduces strategic R&D management methods such as technology forecasting and project management techniques, and systematically teaches the basic concepts and methodologies for the management of technology. Actual technology management cases of ventures and tech companies will be examined and analyzed.
This course provides students with an understanding of the basic concepts of product design, the product design process, and the techniques required for product design. Students will also learn procedures, methods, and analytical techniques to reflect consumer needs and ergonomic considerations in the product design process.
Learn the theory and practical application of data analysis, a core competency in digital manufacturing. You'll practice analyzing and interpreting multivariate data based on multidimensional data.
Researchers in engineering fields must publish their research results in the form of academic papers. Writing a well-structured paper that appropriately reflects the topic and content is crucial for clarifying one's argument and communicating with other researchers. This course focuses on writing appropriately and using basic Korean and English writing techniques to develop a method for writing papers that reflect the required elements of an academic paper. Specifically, students will learn the principles of citing others' knowledge and arguments, and utilize bibliographic information programs like Mendeley to manage and append references to the text.
It's an interdisciplinary discipline that utilizes scientific methods, procedures, and algorithms to derive knowledge and insights from diverse data. In other words, it integrates related methodologies like statistics, data analysis, and machine learning to understand and analyze real-world phenomena through data.
Understand the composition of digital manufacturing systems, the roles and interactions of their components, and learn about research and development trends in element technologies for building digital manufacturing systems, as well as representative implementation cases.
Learn the design and analysis of system simulators for digital manufacturing system operation, as well as programming techniques for data analysis. You'll also practice developing the software necessary for manufacturing system operation using various algorithms and a GUI(Graphical User Interface).
Learn the basic concepts of machine learning and the theoretical principles of advanced algorithms such as "Neural Network, Deep Learning, Support Vector Machine, Hidden Markov Models, Bayesian Networks, and Gaussian Process."
Learn about systems and simulation-based analysis techniques to effectively plan, organize, perform, and control production activities such as production, inventory, quality, material purchasing, and transportation.
Understand manufacturing processes, learn the theory of selecting optimization factors, and cover comprehensive production operation management skills in manufacturing sites.
This course explores quality management challenges and solutions in digital manufacturing systems and teaches design methodologies for reliable and cost-effective quality management systems.
Learn about statistical-based equipment failure and anomaly detection and analysis techniques in digital manufacturing systems, and research intelligent predictive maintenance methodologies based on IoT sensors and various algorithms.
Learn to apply your knowledge and solve practical problems by writing a master's thesis.
Learn to apply your knowledge and solve practical problems by writing a master's thesis.
This course covers fundamental management knowledge, including organizational management and marketing, essential for startup entrepreneurs and business owners, as well as the use of intellectual property rights and a collaborative business mindset through theoretical and practical business case studies.
Through field experts, you will learn about various cases related to manufacturing innovation by learning about manufacturing site-required technologies and requirements, problem identification, and resolution cases.
This course trains human resources through joint research tailored to the needs of the field, based on a joint industry-academia project lab.
This course trains human resources through joint research tailored to the needs of the field, based on a joint industry-academia project lab.
This course trains human resources through joint research tailored to the needs of the field, based on a joint industry-academia project lab.
Acquire work experience and practical skills in industrial settings.
Acquire work experience and practical skills in industrial settings.
Statistics is a core competency in industrial engineering. The ability to collect, organize, and statistically analyze data is essential for industrial engineers who interpret and solve problems. This course focuses on learning the fundamentals of statistical theory and how to apply it through programming languages and statistical programs.
In this course, we study the basic concepts, solutions, application methods, and cases of various mathematical programming models that are deterministic models among the optimization models of Operations Research, and learn how to obtain and analyze optimal solutions using various online/offline programs related to optimization techniques.
This course covers key concepts and various techniques for the overall operations management of production systems. Specifically, it divides the functional aspects of production operations management into process, production capacity, inventory, and quality, focusing on issues related to production capacity and inventory.
For machines and structures, selecting the right material for the right location has a significant impact on reliability and economy, so this course provides a method for evaluating and applying the qualitative and quantitative mechanical properties of materials.
This course covers cutting-edge technology management issues, including product/service innovation based on innovative technologies, startups, intellectual property management, pricing policy, and open innovation.
In this invention, we will focus on the necessary methods and fires to safely and cooler machine products used in the work environment or human life by considering the main components such as human physiology and collage in the "Man-Machine System" under an appropriate environment.
| Category | Program | Course/English | Credits |
|---|---|---|---|
| Major, Required | Master’s degree | Ph.D Thesis | 3 |
| Major, Required | Major, Elective | Advanced System Safety Engineering | 3 |
| Major, Required | Major, Elective | Research methodology | 3 |
| Major, Required | Major, Elective | Quality Improvement Seminar | 3 |
| Major, Required | Major, Elective | Intelligent Manufacturing System | 3 |
| Major, Required | Major, Elective | Application of Probability Theory and Statistics | 3 |
| Major, Required | Major, Elective | Design and Analysis of Information Systems | 3 |
| Major, Required | Major, Elective | Game and Decision Theory | 3 |
| Major, Required | Major, Elective | Advanced Universal Design | 3 |
| Major, Required | Major, Elective | Customer Relationship Management | 3 |
| Major, Required | Major, Elective | Advanced Topics in Data Mining | 3 |
| Major, Required | Major, Elective | Seminar in Project Management | 3 |
| Major, Required | Major, Elective | Advanced Production Management | 3 |
| Major, Required | Major, Elective | Advanced Topics in Computer Aided Design/Computer Aided Manufacturing | 3 |
| Major, Required | Major, Elective | Service Science | 3 |
| Major, Required | Major, Elective | Applications of Queueing theory | 3 |
| Major, Required | Major, Elective | Fuzzy Theory | 3 |
| Major, Required | Major, Elective | Financial Engineering | 3 |
| Major, Required | Major, Elective | Development of Ubiquitous Systems | 3 |
| Major, Required | Major, Elective | Advanced Topics in SCM | 3 |
| Major, Required | Major, Elective | Knowledge-based Expert Systems | 3 |
| Major, Required | Major, Elective | Advanced Topics in Project Management | 3 |
| Major, Required | Major, Elective | Network Optimization | 3 |
| Major, Required | Major, Elective | Advanced Topics in Reliability Engineering | 3 |
| Major, Required | Major, Elective | Computer-Integrated Manufacturing | 3 |
| Major, Required | Major, Elective | Seminar in Industrial and Management Engineering | 3 |
| Major, Required | Major, Elective | Modeling and Simulation | 3 |
| Major, Required | Major, Elective | Mathematical Modeling & Optimization | 3 |
| Major, Required | Major, Elective | Meta-heuristics | 3 |
| Major, Required | Major, Elective | Technical paper writing | 3 |
| Major, Required | Major, Elective | Nonlinear Programming | 3 |
| Major, Required | Major, Elective | Multi Criteria Decision Analysis | 3 |
| Major, Required | Major, Elective | Theory of stochastic proces | |
| Major, Required | Major, Elective | Advanced Industrial Safety Management | 3 |
| Major, Required | Major, Elective | Design of Occupational Safety and Health System | 3 |
| Major, Required | Major, Elective | Risk Assessment Analysis | 3 |
There are always risks in a company’s production flowchart, and task analysis and risk analysis are necessary to eliminate these risks in advance and ensure safety.
This course deals with the process and method of research and projects. A research project is visualized as a journey where you pass certain landmarks along your way. Every research project needs to start with a clear problem formulation. As you develop your project, you will find critical junctions where you will make choices about how to proceed. This course will help so that you can make wise decision on these junctions such as sampling, measurement, experimental design, analysis and theories of validity.
By analyzing quality improvement cases occurring on industrial sites, students are able to develop the ability to identify problems and improvements in both hardware and software and solve on-site problems in quality, production, cost, delivery, safety, etc.
This course establishes the basic concepts of process, management, and information systems in production, and provides a wide range of theories and techniques for building automated production systems and integrated systems. In particular, it covers methodologies to reduce human intervention and realize small batch production by modeling the human knowledge and experience necessary for manufacturing activities.
Students will learn estimation and testing methods to analyze the characteristics of a population based on the probability theory for decision-making. They will also learn how to represent various data and techniques for statistical processing and analysis (regression analysis, correlation analysis) and apply them when writing research papers and reports.
With the advent of the mobile era, information systems for systematically managing and analyzing data generated in tremendous amounts throughout society enhance the competitiveness of the company and provide the basis for proposing a roadmap for the company. With the growing importance of information systems, the process of designing and analyzing information systems is the most crucial step in the operation of information systems in the future. This course covers software development methodologies, documentation techniques, and project management, and introduces way to applies the knowledge and techniques obtained in the course to real-world problems using various tools.
This course is a study of human judgment and behavior, and explores new and advanced theories of games and decision-making, including traditional game models and decision-making models.
Universal design is a creative paradigm for the 21st century that will enable us to promote human dignity and equality. Considering that design is about making people’s lives fuller and more convenient, universal design is a design concept that revitalizes the meaning of “for human beings.” It stems from the recognition that products, buildings, and environments should be designed to meet the needs and activities of a wide range of people, including the elderly, people with disabilities, and children. In recent years, especially in the United States, research in this area has been actively conducted, and universal design has become an increasingly important topic of interest for industrial designers, architects, environmental designers, and others. As such, universal design aims to make products and environments accessible to all, with little or no additional cost.
This is a course on how businesses manage customer relationships, acquire and retain customers, and analyze and store information about customers, sellers, and partners.
This course examines how to systematically and automatically identify statistical rules or patterns in large amounts of stored data or apply them.
In order to effectively manage various projects, students will study the latest techniques and principles for efficiently performing various aspects of project management, including project conceptualization and planning, schedule and cost management, resource management, team formation and operation, risk management and decision making, and utilization of related software and the Internet.
This is a course on how businesses plan, organize, and control production in order to carry out production activities rationally and efficiently.
This course is a study of computer-aided design and manufacturing and systems that use computers to design a product and automatically produce the product by creating a numerical control (NC) tape to operate machine tools based on the design.
It aims to identify the essence of the service industry by combining various disciplines such as science, business administration, social sciences, and computer science, and to revolutionize service levels.
This course covers stochastic models and modeling processes, queueing systems, Markovian queueing systems, generalized arrival queueing systems, queueing networks, and discrete-time queueing systems.
This is a mathematical theory of how the brain makes judgments and decisions in ambiguous and unclear situations, with applications in a wide range of fields, including control engineering and artificial intelligence.
This course is aimed at building the framework for understanding investment decision-making. In this course, students will study key concepts such as efficient markets, asset allocation, and investment analysis, examine some of the recent changes that have occurred in the investment climate and conditions, and examine the main concerns of investors and the tools needed to assess and address these challenges.
Students will examine the strategic importance of the strategy, design, planning, and operations of supply chains and develop analytical skills to mathematically model and solve problems that arise in the supply chain.
While learning the overall contents of building a knowledge expert system (language, method, software utilization, etc.), students will select an application field and research and develop a system that can be applied in practice.
Students will examine a new paradigm of business management techniques for projects with high risks that are unpredictable.
The goal is to develop product reliability requirements, establish appropriate reliability programs, and perform appropriate analysis and work to ensure that the product meets those requirements.
This is a field where computers are used to build an integrated system from technology development, design, production, and sales. When customers demand a new product, a new product that meets the needs is quickly designed, and production drawings and product specifications are immediately transmitted to production staff through a computer to prepare for production. The manufacturing location, delivery date, specifications, and quantity are automatically sent to the production site from the sales department through a network. The information on production status is reviewed not only at the production site but also by the sales department at the same time, so that the entire company has an integrated production and sales system.
Students will examine issues related to each area of industrial and management engineering, especially those related to their respective dissertation topics.
This is a course on testing or analyzing how objects or phenomena in a particular system behave/work by running a model.
This is a course on analyzing the conditions under which a real value, function, or integer is maximized or minimized for a given set of real values, functions, or integers defined over a given set, and is used to address the problem of allocating limited resources in the most efficient manner.
This course introduces metaheuristic methods such as genetic algorithms, tabu search, and simulated annealing to solve complex real-world optimization problems that are difficult to deal with using traditional optimization algorithms, and covers the theoretical background and real-world applications of these methods.
This course concerns a method of solving problems using a mathematical approach and deals with optimization problems, allocation problems, etc.
This is a course on the process of selecting the best option by systematically analyzing and examining the advantages and disadvantages of various options in relation to costs, benefits, gains, and losses to achieve a goal.
In this course, students will learn various stochastic processes such as birth-death process, renewal process, Poisson process, Markov process, etc. and learn how to apply them in the real world.
This course focuses on the application and methodology of discovering information about human behavior, abilities, limitations, and characteristics. This information is then applied to the design of tools, machines, systems, tasks, jobs, and environments to enable humans to work in productive, safe, and comfortable conditions and to use objects effectively.
Students explore methods to optimize vehicle and process routes and improve material flow efficiency. This course covers how network models and algorithms provide optimal solutions to transportation problems, suggest optimal process routes, and enable the smooth flow of materials. Through this, students develop the ability to understand and effectively utilize network flows.
This course focuses on learning a methodology that approaches the entire thesis writing process as a systematic procedure. From selecting a research topic to conducting literature reviews, formulating hypotheses, collecting and analyzing data, and writing logically, it emphasizes systematically executing all steps to complete a highly coherent thesis.
With the implementation of the Serious Accidents Punishment Act, learn key safety management and system safety techniques to assess a company's current safety management status and develop improvement measures.
This course comprehensively covers the legal, technical, and managerial aspects necessary for establishing and operating a corporate safety and health management system, developing practical skills to design efficient systems.
This course covers methods for identifying various risk factors in industrial settings, evaluating them using quantitative and qualitative methods, and developing strategies to prevent accidents and improve safety.