For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| ESM2018 | Manufacturing Engineering/Smart Factory | 3 | 6 | Major | Bachelor | 2-3 | Korean | Yes | |
| This course is offered to learn engineering materials, manufacturing processes, and how to design and operate production systems. Also, concepts, theories and core technologies of smart factory will also be included. This is a basic course for engineering in manufacturing fields, taking this course will ensure you a solid foundation for manufacturing engineering. | |||||||||
| ESM3001 | Operations Research and Practice II | 3 | 6 | Major | Bachelor | 3-4 | Korean,English | Yes | |
| This is a continuation of OR/MS I.Topics include inventory models.Markov decision process.Posson process.Exponential distribution.Birth-death process models and queneingmodels.Review on basic one semester of basic probablity theory or probability theory orprobaility and statistics.OR/MS Imay be a prerequisite but not a must.Students who want totake simulations are strongly advised to take this course. | |||||||||
| ESM3004 | Management Innovation | 3 | 6 | Major | Bachelor | 3-4 | Korean | Yes | |
| This course examines various management innovation approaches such as Strategic Management, BPR, Six Sigma, and TQM. Special emphasis is placed on basic concept of the management innovation, key successful factors, popular approaches, performance measurements, and real world case studies. | |||||||||
| ESM3013 | Technology Strategy | 3 | 6 | Major | Bachelor | 3-4 | - | No | |
| This lecture focuses on the problems related to planing of R&D activity at corporate strategy level. Therefore, major topics in this lecture are as follows; R&D and management strategy, R&D and strategic planning, R&D strategy setting, R&D and new business strategy, R&D and new product development strategy, organization of R&D, management of researcher, resource allocation of R&D, evaluation of R&D, etc. | |||||||||
| ESM3016 | Database theories and practices | 3 | 6 | Major | Bachelor | 3-4 | - | No | |
| This course aims at the acquisition of theoretical and practical knowledge of database systems which will enable the students to apply their knowledge directly to the real world application developments. A through understanding of the concepts and techniques about conceptual, logical, and physical modeling is emphasized in the earlier stage. Entity-relationship model and object oriented model are discussed as the practical backbone of the database systems development knowledge. In the last stage of the course, students will learn about the theoretical aspects of normalization and will do some practices with SQL(structured query language). MS Access, MS-SQL, and ProcessQ are some of the tools to be used for the lab activities and team based term project. | |||||||||
| ESM3019 | Operations Management | 3 | 6 | Major | Bachelor | 3-4 | English | Yes | |
| This course deals with the design and operations of production systems. major topics include decisions in operations management, concept of operations strategy, demand forecasting, production planning, operations scheduling, PERT/CPM for project management, line balancing. | |||||||||
| ESM3020 | Production Information Systems | 3 | 6 | Major | Bachelor | 3-4 | - | No | |
| Understanding basic elements such as value chain, network system, POP system,distributed database system, data flow diagram, and adaptive organization for integrating production information. Core concepts, and related information technology for design, implementation and operation of CIMS, SCM, TOC, CALS and BPMS are the major topics. | |||||||||
| ESM3023 | Simulation: Modeling and Practice | 3 | 6 | Major | Bachelor | 3-4 | English | Yes | |
| Simulation is a powerful OR/MS tool for scientific decision making in various fields. In this course, we learn the simulation methodologies, such as Random Number Generation, Output Analysis techniques, Variance Reduction Techniques. We spend substantial amount of class hours to learn a computer simulation language, ARENA. Basic concepts of Queueing Theory and Statistics are required, but not mandatory. Students are asked to participate several simulation projects, out of text and/or real situation. | |||||||||
| ESM3026 | Applied Statistics II : Theory and Practice | 3 | 6 | Major | Bachelor | 3-4 | Korean | Yes | |
| This is a sequel to Applied Statistics I, introduces basic concepts of probability and statistics, statistic, estimation and hypothesis test, analysis of correlation, simple regression model. This course is a second gateway course to all the courses offered by School of System Management Engineering. Students taking this course are required to participate a computer software practice session one hour per week. The prerequisite of this course is Applied Statistics I: Theory and Practice | |||||||||
| ESM3027 | Strategic Decision Analysis | 3 | 6 | Major | Bachelor | 3-4 | - | No | |
| This course is concerned with modeling of stochastic systems. Models and application problem in OR/MS Ⅱ will be covered in depth. Basics on conditional probability, conditional expectation and total probability will be reviewed intensively. Topics will also include birth-death models continuous time Markov chain (CTMC), queueing models and reliability models. Renewal theory and renewal-reward theorem will be introduced to cover the probabilistic optimization models. | |||||||||
| ESM3035 | Knowledge Engineering | 3 | 6 | Major | Bachelor | 3-4 | - | No | |
| As the progress of Artificial Intelligence and Expert Systems (AI/ES) technologies, the MIS managers need to understand not only the fundamentals of AI/ES, but also their relationships with the existing information systems technologies such as database and mathematical models. To meet this need, this course teaches the basic concepts and development tools of AI/ES and applies them to the managerial decision support. The discussing cases and performing project are encouraged to learn the real world experience of developing intelligent information systems. | |||||||||
| ESM3038 | Analysis of Stochastic Systems | 3 | 6 | Major | Bachelor | 3-4 | - | No | |
| This course is concerned with modeling of stochastic systems. Models and application problem in OR/MS Ⅱ will be covered in depth. Basics on conditional probability, conditional expectation and total probability will be reviewed intensively. Topics will also include birth-death models continuous time Markov chain (CTMC), queueing models and reliability models. Renewal theory and renewal-reward theorem will be introduced to cover the probabilistic optimization models. | |||||||||
| ESM3044 | SME Industry Co-operative Program 3 | 3 | 6 | Major | Bachelor | 2-4 | Korean | Yes | |
| This is an industry co-operative program of Department of Systems Management Engineering. By participating in solving real world problems in industries, students can improve their problem solving skills and practice their knowledges. (participating period: 6 weeks) | |||||||||
| ESM3045 | SME Industry Co-operative Program 3A | 3 | 6 | Major | Bachelor | 2-4 | Korean | Yes | |
| This is an industry co-operative program of Department of Systems Management Engineering. By participating in solving real world problems in industries, students can improve their problem solving skills and practice their knowledges. (participating period: 6 weeks) | |||||||||
| ESM3046 | SME Industry Co-operative Program 3B | 3 | 6 | Major | Bachelor | 2-4 | Korean | Yes | |
| This is an industry co-operative program of Department of Systems Management Engineering. By participating in solving real world problems in industries, students can improve their problem solving skills and practice their knowledges. (participating period: 6 weeks) | |||||||||