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품질 공학 (학부 과목)

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Course Description

Application of statistical methods to the design and operation of quality control/assurance systems.
Major Topics in Quality Engineering (Big Picture)

Syllabus (2014, Fall) (Download)

Syllabus (2014, Fall)
Instructor Professor Kwang-Jae Kim, Room 4-201, 279-2208, kjk@postech.ac.kr
Class Meetings MW 9:30 am ~ 10:45 am , Room 4-302
Teaching Assistant Mr. Ki-Hun Kim, Room 4-316, 279-8249, kh_kim@postech.ac.kr
Class Homepage POVIS Learning Management System ( http://lms.postech.ac.kr )
Office Hours MW 10:45 am ~ 12 noon (Professor Kim)
TTh 10:45 am ~ 12 noon (Mr. Kim)
(or by appointment)
Prerequisite IMEN 272 (Probability and Statistics for Engineers)
or MATH 230 (Probability and Statistics): Strictly enforced;
IMEN261 (Introduction to OR): strongly recommended
Bulletin Description Application of statistical methods to the design and operation of quality control/assurance systems.
Text : (optional) Amitava Mitra, Fundamentals of Quality Control and Improvement , 3 rd Ed, Wiley, 2008
References Montgomery, Introduction to Statistical Quality Control , 5 th Ed, Wiley, 2005.
DeVor, Chang, & Sutherland, Statistical Quality Design and Control ,
2 nd Ed, Prentice Hall, 2006.
Grading System 25%     Quizzes
35%     Final Examination
30%     Assignments and Term Project
10%     Class Participation
Quizzes Quizzes will be given with books/notes closed. The lowest score will be dropped, and no make-ups will be given.
Final Examination The final examination will be comprehensive, covering the entire classes. Examination policies will be announced prior to the exam.
Assignments Small case problems will be given as assignments. A term project will also be given. A detailed schedule will be announced later.
Class Participation Students are expected to actively participate in class discussions.

Topic Outline

Topic Outline
  • Class Overview
  • Strategic Importance of Quality
Quality Function Deployment
  • New Product Development Process
  • House of Quality Chart
Process Capability
  • Inherent Variations and Tolerancing
  • Design Specifications vs. Natural Variation
  • Process Capability Index and Process Performance Index
Statistical Process Control
  • Process Improvement vs. Process Control
  • Chance Causes vs. Assignable Causes
  • Control Charts: X_bar and R, X_bar and S, X and Moving Range
Loss Function
  • Traditional vs. Taguchi Loss Function
  • Expected Loss
  • Comparison of Processes
Design of Experiments
  • Optimal Settings of Parameters
  • Designs: Single Factor, Factorial Design
  • Taguchi Methods: Robust Design
Other Selected Topics in Modern Quality Engineering
  • 6 sigma Quality
  • Service Quality
  • New Trends in Quality Engineering