In this course, students will gain a basic understanding of the core technologies of the Fourth Industrial Revolution and the competencies that students should gain, according to industry experts.
This course aims to introduce students to electronic systems composed of electronic components and the programming that controls them using Arduino and to allow students to experience the fun side of engineering in creating controlled electronic systems.
This course introduces industrial engineering as a field that identifies, analyzes, and solves real-world issues across various industrial sectors. Students are introduced to the types of problems addressed in industrial engineering and the methods used to solve them. Through this process, students also gain an understanding of the overview and characteristics of the major courses they will take in the program and begin to develop their identity as industrial engineers.
Students will be able to understand the basic concepts of smart factory and the main technologies used.
This course aims to help students understand mathematical logic and notation, which are the foundation of scientific tools, especially basic logic in computer programming. Mathematics is the most fundamental scientific language, and engineering students must be able to translate real-world problems into scientific language. Through learning and practicing various tools included in discrete mathematics, such as logic and graphs, students will develop the ability to express phenomena in mathematical terms as industrial engineers.
Students will be able to understand and apply the principles and techniques related to research on methods and work measurements for the design and operation of efficient work systems.
Statistics is considered a core competency in industrial engineering. The ability to collect, organize, and analyze data statistically is essential for interpreting and solving problems in the field. This course provides students with fundamental statistical theories and emphasizes their application through programming languages and statistical software tools.
Students will be able to understand the algorithms used in data mining and how to utilize them to make data-driven decisions.
It covers various theories of human psychophysical cognition and engineering methods of measurement and analysis.
This course introduces quality management as a management strategy and activity centered on quality as a core value. It covers both quantitative approaches, such as statistical quality control, and qualitative methods, such as the structure and operation of organizations. Students will learn the fundamental concepts and key methodologies of quality management through hands-on activities and case studies.
This course provides an overview of the techniques and applications required for economic assessments of various entrepreneurial and investment opportunities in the era of the Fourth Industrial Revolution and to make decisions based on them.
This course covers the fundamental concepts and applications of linear algebra. Key topics include vector spaces, matrix theory and computation, and linear systems. The content of linear algebra is widely applicable across mathematics, science, and engineering. This course provides foundational knowledge of linear programming, which is essential in management science.
This course introduces the concepts and theories of object-oriented programming. Through various hands-on exercises and assignments, students develop their problem-solving skills. In particular, the course helps students build a foundation in simulation modeling based on their understanding of object-oriented principles.
This course focuses on advanced statistical theories required for professional competency in industrial engineering. Building on previously learned statistical concepts, students further develop their statistical skills by learning and practicing a variety of statistical models.
Rapidly evolving technologies have significantly impacted business models and operational strategies through the development of new products and services. Key topics covered include technology-driven product and service innovation, startups, intellectual property management, pricing strategies, and open innovation—core issues in the field of modern technology management.
Optimization methodologies are applied to a wide range of problems aimed at maximizing profit or minimizing cost. The basic model of optimization can be considered the linear programming model with real-valued variables. This course covers the fundamental concepts of linear programming and the process of formulating optimization problems. Students will also learn solution methods for linear programming models and basic techniques for implementing them.
Sensitive engineering involves reflecting the characteristics of the human body and human emotions as much as possible in product design. In this course, students will learn the engineering approach to incorporate the hopes of humans or human emotions into a concrete product design.
In this course, students will study the basic concepts, solutions, applications, and examples of various mathematical planning models that fall under the deterministic model among the optimization models of operations research and learn how to obtain and analyze optimal solutions using various online and offline programs for optimization techniques.
The aim is to understand the concepts and structure of database management systems and acquire the basic knowledge to design and implement them based on related principles and application methods.
The goal is to understand the supply and demand relationships in the supply chain and study various network or systematic methodologies to establish optimal inventory management policies.
Ensuring product quality and reliability at a targeted level is a critical competency for companies. This course covers statistical quality control using techniques such as sampling inspection and control charts, and introduces reliability engineering, which involves the probabilistic analysis of system and product failures and their distributions.
In this course, students will learn how to process different types of data from the field using statistical software and analyze the results to draw conclusions.
In this course, students will study the basic concepts, solutions, applications, and examples of various mathematical planning models that fall under the deterministic model among the optimization models of operations research and learn how to obtain and analyze optimal solutions using various online and offline programs for optimization techniques.
Students will select factors that affect the characteristics of the product, plan experiments, obtain data, and analyze them to determine the optimal manufacturing conditions for the product.
This course focuses on the methods and theories necessary to safely and effectively design machines and products used in work environments or human life by considering major factors such as human physiology and physical traits in man-machine systems under appropriate conditions.
In this course, students will learn about the purpose of using various information systems such as MIS, ERP, SCM, CRM, and BI that are being utilized in companies in the era of the Fourth Industrial Revolution. They will learn how to collect and analyze user requirements in the development process of information systems, derive functions, and use creative methods to improve the business processes of companies.
Among the methods of modeling problems, probabilistic models can be considered more realistic than deterministic models. In this course, students learn the various properties of random variables and modeling techniques used to represent random situations. The course deals with basic theories and applications for modeling or describing the characteristics of systems that change based on probability.
This course is a Capstone Design class aimed at achieving a comprehensive understanding and application of the Innovation Curriculum in Industrial and Management Engineering. Students form small teams, identify real-world problems, and work on solving them, thereby developing practical problem-solving skills as industrial engineering professionals. The course focuses not only on integrating theoretical knowledge acquired through the innovation curriculum, but also on demonstrating problem-solving processes using hands-on practice and experimental facilities.
The goal is to gain an understanding of statistical methodologies and analysis methods for conducting surveys and analyses such as rating scales and survey composition.
In this course, students will utilize and grasp different techniques for making data-driven decisions, learn algorithms used in data mining and how to utilize them, configure the environment for big data analytics, apply big data analysis methods, and utilize big data in decision-making.
This course provides students with a general understanding of how to improve and efficiently utilize facilities through understanding and acquiring techniques related to allocation of plant resources for customized production, decision-making on capital expenditure, and equipment utilization and conservation activities. Through group activities, students will identify items that need to be analyzed, improved, and developed in the resource management system and derive effective ways to make improvements.
This course explores human characteristics such as vision, hearing, information processing, and muscle function, and teaches how to design environments related to human interaction based on these characteristics. Students will learn experimental methods for quantitatively measuring and analyzing human factors. The course also discusses the fundamental principles for applying quantified human data to work environment design, and introduces techniques for improving physical compatibility, worker satisfaction, and productivity. The experimental component includes training in measuring neural response time, human task and motor performance, fatigue using EMG and bio signal processing, and evaluating work environments through noise and illumination measurements. Students will also learn how to statistically analyze this data and apply it to product and workplace design.
This course identifies different theories and applications of optimal decision making.
In response to rapidly evolving technologies and social environments, companies continuously adapt and update their future strategies. This course examines current trends across various industries and explores how development strategies are shifting in relation to both technological advancements and social changes.
This course introduces the key concepts and techniques related to the overall management of production systems. It focuses on the functional aspects of production and operations management, specifically in the areas of process design, capacity planning, inventory control, and quality management. Special emphasis is placed on issues related to production capacity and inventory management.
Decision-making is a fundamental activity that occurs in all areas, including production, management, economics, healthcare, and national defense. However, decisions are often made without sufficient information, and in many cases, under conditions of uncertainty. This course introduces decision-making methodologies for both probabilistic situations, where some probability information is available, and non-probabilistic situations, where such information is lacking. Students will learn the basic concepts and applications of decision-making theories such as utility theory and game theory.
This course provides engineering students with essential foundational knowledge in economic concepts and accounting principles required for practical work. In particular, it focuses on understanding basic accounting theories and practicing how to analyze a company's financial status using financial statements.
Quality management refers to a management strategy that considers quality as a core value. Students have learned the concepts and methodologies of quality management through various courses. This course aims to bridge the gap between theory and practice by preparing students to apply this knowledge in real-world settings. Specifically, students will review the content covered in courses related to the Quality Management Engineer Certification and strengthen their practical skills through exercises linked to real-world competency assessments.
In this course, students will analyze the causes of various accidents and understand the various safety management techniques to reduce the frequency of industrial accidents and improve productivity.
This course aims to provide an understanding of the concepts of product design and the overall product development process, along with the techniques required at each stage. Students will comprehensively apply key methods previously learned such as concept development, system architecture design, prototyping, process design, and testing to practical product development projects.
This course introduces investment options, including various financial instruments such as stocks, bonds, and derivatives, and the economic theory behind rational investing (utility function, portfolio theory, option pricing theory).
Students will learn about R&D organization design and operation, personnel, budget and accounting, information, and intellectual property management, R&D MIS, directions of the economy in the future, technological development, values of the future society and R&D, introduction and transfer technology, R&D commercialization strategies, laboratory culture and productivity, and research organization reengineering.
Based on the knowledge and experience acquired throughout the curriculum, students carry out a semester-long project in an industrial setting to develop practical adaptability and technical competence. Six academic credits are awarded based on the performance and outcomes of the field assignment.
Based on the knowledge and experience acquired throughout the curriculum, students carry out a semester-long project in an industrial setting to develop practical adaptability and technical competence. Nine academic credits are awarded based on the performance and outcomes of the field assignment.
Based on the knowledge acquired in each field, students learn the process from product development to production by directly carrying out the design process of products, etc. That is, they will be able to hone their creativity, practical skills, teamwork skills, and leadership skills by designing, producing, and evaluating works that are needed by local industries.
Based on the knowledge acquired in each field, students learn the process from product development to production by directly carrying out the design process of products, etc. That is, they will be able to hone their creativity, practical skills, teamwork skills, and leadership skills by designing, producing, and evaluating works that are needed by local industries.
Students apply the theories and practices learned in their studies in the workplace and analyze problems to develop the ability to apply them in the field.
Through exchanges with overseas universities in regard to a wide variety of topics, this course helps students build their global competence and cultivate a interdisciplinary mindset.
This course helps students understand how businesses operate and develop practical skills by applying fundamental and applied knowledge learned at school to real-world industrial settings.
Students learn business operation practices and develop practical skills by applying fundamental and applied knowledge from their major to real industrial settings.
Students learn business operation practices and develop practical skills by applying fundamental and applied knowledge from their major to real industrial settings.
Students apply the theories and practical skills acquired at school to real-world workplace situations, analyze problems encountered in the field, and develop their ability to effectively implement these skills in professional settings.
In this integrated bachelor’s and master’s program, students apply the knowledge acquired in their respective fields by directly carrying out the design process of products. Through this hands-on experience, they learn the entire process from product development to production. By independently designing, manufacturing, and evaluating products that meet the actual needs of local industries, students cultivate creativity, practical skills, teamwork, and leadership.
In this integrated bachelor’s and master’s program, students apply the knowledge acquired in their respective fields by directly carrying out the design process of products. Through this hands-on experience, they learn the entire process from product development to production. By independently designing, manufacturing, and evaluating products that meet the actual needs of local industries, students cultivate creativity, practical skills, teamwork, and leadership.
This course provides a fundamental understanding of additive manufacturing technology, a core component of smart factories and future manufacturing environments. Students also engage in hands-on practice using 3D modeling tools.
This course focuses on the design and simulation of various components for smart factories using additive manufacturing technology.
Data gains meaning through analysis and interpretation, and visualization is one of the most fundamental and effective ways to understand and interpret data. This course introduces various visualization techniques and tools that are appropriate for understanding the characteristics of given datasets. Students will learn how to select and construct basic charts correctly and explore a range of visualization methods through hands-on practice using various applications and programming languages.
Recent technological innovations driven by convergence across various fields have significantly influenced not only new product development and production methods, but also the evolution of diverse marketing methodologies. This course introduces fundamental marketing concepts and explores how technological advancements are transforming customer data collection and analysis, as well as the measurement of strategic marketing performance.
In production activities, one of the most important elements is the human operator. Therefore, not only production facilities but also modern products must be designed with full consideration of human physical and cognitive characteristics and limitations. This course covers human systems engineering, a field that focuses on understanding these limitations and characteristics and applying them to product and production system design. It emphasizes both the physical and cognitive aspects from a systems design perspective and teaches students how to apply these principles in practice. The course is also designed to support students preparing for the Human Factors Professional Engineer Certification (practical exam).
In production activities, one of the most important elements is the human operator. Therefore, not only production facilities but also modern products must be designed with full consideration of human physical and cognitive characteristics and limitations. This course covers human systems engineering, a field that focuses on understanding these limitations and characteristics and applying them to product and production system design. It emphasizes both the physical and cognitive aspects from a systems design perspective and teaches students how to apply these principles in practice. This course is designed to support students in preparing for the practical exam of the Human Factors Professional Engineer Certification (practical exam).
Advances in computing have enabled artificial intelligence to support human decision-making and problem-solving. This course covers the fundamental concepts of artificial intelligence, along with methodologies based on machine learning theory. Special emphasis is placed on identifying AI-related problems in industrial settings and developing problem-solving skills through practical exercises.
Manufacturing encompasses all activities involved in producing goods and has become a core value-generating activity since the onset of industrialization. This course introduces the fundamental concepts of manufacturing and provides theoretical foundations for various unit manufacturing processes. For selected key processes, hands-on practice is included. Based on this, students will gain an understanding of the structure and characteristics of manufacturing systems.
Due to the unique circumstances of national division and armistice, national defense is a critical area not only in terms of national policy but also from industrial and academic perspectives in Korea. As weapon systems and the technologies used to operate them continue to advance, the level of scientific and technological support required has also increased. This course introduces various technical and managerial issues in the defense sector and explores the scientific methodologies applied to address these challenges.
Advances in computing have enabled artificial intelligence to assist human decision-making and problem-solving. This course covers the fundamental concepts of artificial intelligence, including methodologies based on machine learning theory. Special emphasis is placed on identifying AI-related problems in industrial settings and enhancing problem-solving skills through practical exercises.
Intellectual property (IP) is increasingly recognized as a strategic asset in modern business. In the first part of this course, students learn the concepts of knowledge management and intellectual property rights, along with the procedures for acquiring such rights. The latter part focuses on managing IP effectively and leveraging it for commercialization and early market development strategies. Students will gain foundational knowledge and case-based insights into technology marketing, technology transfer, investment, and validation—all critical to successful technology commercialization. In the advanced section of the course, students will explore frameworks for identifying and evaluating commercialization opportunities from the perspectives of entrepreneurs and technology assessors, focusing on marketability, technical feasibility, business potential, and real-world applications.
With the advancement of cutting-edge technologies such as IoT, big data, and AI, companies are now able to collect a vast amount of customer data. This course focuses on analyzing increasingly personalized customer behaviors based on diverse customer datasets and developing effective communication strategies accordingly. Students will learn how to use AI and statistical techniques to analyze customer data, understand how personalized customers make purchasing decisions, and design step-by-step approaches for targeted marketing strategies.
This course introduces electronic systems composed of electronic components and the programming used to control them through Arduino in an accessible way for students in the Convergence and Autonomous Engineering Program. It aims to provide students with enjoyable industrial and systems engineering experience by enabling them to design and build their own controllable electronic systems.
Industrial and Management Engineering is a discipline that identifies, analyzes, and solves practical problems across various industrial sectors. This course introduces students in the Convergence and Autonomous Engineering Program to the wide range of issues addressed in the field and the methods used to solve them. Through this process, students will gain an overview of the courses offered in the Industrial and Management Engineering major and understand the characteristics of the curriculum. The course also helps students explore and build their identity as future industrial and management engineers.