|Program||Bachelor [학사과정]||Course Type||Major Elective [ 전공선택 ]|
|Course Code||31.436||Course No||IE436|
- Tue: 09:00~11:45
|Course Title||Case Studies for Industrial & Systems Engineering [ 산업 및 시스템공학 사례연구 ]|
Tue: 09:00~10:30 / (E11)Creative Learning Bldg. [ (E11)창의학습관 ] (407)
Thu: 09:00~10:30 / (E11)Creative Learning Bldg. [ (E11)창의학습관 ] (407)
|Name||장영재(JANG, Young Jae)|
|Department||산업및시스템공학과(Department of Industrial & Systems Engineering)|
|Syllabus File||Case Study for Industrial - Syllabus-2019.docx|
|Summary of Lecture||Course Objectives:
In this course, you will
- Learn actual cases that have created meaningful results with Industrial & Systems Engineering approaches in various industries such as sports, healthcare, finance, manufacturing, advertisement, government, military, transportation, and IT industries.
- Gain understanding of Industrial & Systems Engineering methods applied in real-life.
- Understand how to apply I&SE techniques to various industry functions including marketing, engineering, business operations, product design, and strategic planning.
This course is highly recommended to students who are pursuing a career in business analystics, big data analytics, business consulting, project management, manufacturing engineering, business operations/planning, and other fields requiring strong analytical skills.
It is a case-oriented class that covers major Industrial and Systems Engineering topics with various actual industry cases. This class is intended to address the growing demand in I&Systems Engineering students for real-life cases. To address this need, the class topics are selected a diverse, yet fundamental, set of cases from which to cover a number of major methods that are central to an introductory Industrial & Systems Engineering. The cases introduced in this class, for the most part, are somewhat longer and more complex than the typical short cases introduced in other theory-oriented classes.
Since this class deals with actual cases in various areas, industry specialists/practitioners will be often invited to address the real-life issues.
|Material for Teaching||No textbook required|
|Evaluation Criteria||Quizzes & Reading Assignments 50%
Course participation 10%
|Lecture Schedule||Topics (Tentative)
- 1(st) Week : Introduction
- 2(nd) Week : Optimization modeling and Micron Technology case - Investment Strategy
- 3(rd) Week : Optimization modeling and Micron Technology case - Investment Strategy
- 4(th) Week : Production Planning and Scheduling - Woongjin Chemical
- 5(th) Week : Production Planning and Scheduling - Woongjin Chemical
- 6(th) Week : Fast Fashion - Zata - Allocation modeling
- 7(th) Week : Fast Fashion - Zata - Allocation modeling
- 8(th) Week : Electric vehicle charging stations - Optimal investment modeling
- 9(th) Week : Electric vehicle charging stations - Optimal investment modeling
- 10(th) Week : Big Data Analytics - Data mining and optimization - Wall Mart case
- 11(th) Week: Big Data Analytics - Data mining and optimization - Wall Mart case