| Course Name |
(中) 機械製造分析(5133) |
| (Eng.) Analysis of Mechanical Manufacturing |
| Offering Dept |
Department of Mechanical Engineering |
| Course Type |
Elective |
Credits |
3 |
Teacher |
FANN, KUANG-JAU |
| Department |
Department of Mechanical Engineering/Graduate |
Language |
English |
Semester |
2024-FALL |
| Course Description |
This course is taught in a 16+2 and PBL format, using the analysis of variation in mechanical manufacturing processes to introduce the principles of inferential statistics, statistical process control, regression, and design of experiments, to enable students to understand the ways in which variation in mechanical manufacturing processes can be reduced, so that they can build research and analyzing skills using inferential statistics to reduce variation in mechanical manufacturing. |
| Prerequisites |
|
self-directed learning in the course |
N |
| Relevance of Course Objectives and Core Learning Outcomes(%) |
Teaching and Assessment Methods for Course Objectives |
| Course Objectives |
Competency Indicators |
Ratio(%) |
Teaching Methods |
Assessment Methods |
1. be able to classify the mechanical manufacturing processes
2. be able to describe the principles of the target manufacturing process
3. be able to explain the causality of process parameters and results
4. be able to explain the causes of variations in manufacturing results
5. be able to derive principles for minimizing manufacturing variation
6. be able to explain the statistical principles and inference methods for analysis of manufacturing variation
7. be able to explain the background principles of statistical process control, linear regression, and experimental design |
| 1.The ability to solve engineering problems independently with professional knowledge in mechanical engineering. |
| 2.The ability to think innovatively, to design and conduct researches, as well as to present research outcomes. |
| 3.The ability to manage multi-disciplinary teams and to integrate cross-field technologies.. |
| 4.A broader view of international competition/co-operation of industry. |
| 5.The ability to lead, to manage and to plan life-long learning. |
|
|
| topic Discussion/Production |
| Networking/Distance Education |
| Discussion |
| Lecturing |
|
| Written Presentation |
| Attendance |
| Oral Presentation |
| Assignment |
| Quiz |
|
| Course Content and Homework/Schedule/Tests Schedule |
| Week |
Course Content |
| Week 1 |
Introduction & Project for Self-Directed Learning: Case Study Statistical Analysis in Manufacturing Mechanical Parts for Sustainable Development (Self-Directed Learning 6 Hours Extra Separately) |
| Week 2 |
Category of Mechanical Manufacturing Processes
|
| Week 3 |
Process Parameters in Mechanical Manufacturing |
| Week 4 |
Sources of Variation in Mechanical Manufacturing |
| Week 5 |
Nature of Variation: Equation of Variation |
| Week 6 |
Variation Description: Probability and Random Variables |
| Week 7 |
Descriptive Statistics and Central Limit Theorem |
| Week 8 |
Inference Statistics |
| Week 9 |
Mid-Term |
| Week 10 |
Shewhart Model of Manufacturing and Charting |
| Week 11 |
Statistical Process Control and Process Capability |
| Week 12 |
Empirical Process Modeling and Testing |
| Week 13 |
Analysis of Variance (ANOVA)
|
| Week 14 |
Linear Regression and ANOVA |
| Week 15 |
Designed Experiments: Full Factorial Models and ANOVA |
| Week 16 |
Final Exam |
| Week 17 |
Project Report or Presentation for Self-Directed Learning 3 Hours happened during Weeks 1-16 |
| Week 18 |
Project Report or Presentation for Another Self-Directed Learning 3 Hours happened during Weeks 1-16 |
|
| Evaluation |
Textbook: Montgomery, D.C., Introduction to Statistical Quality Control, 6th Ed. John Wiley & Sons, Inc., 2009, ISBN 978-0- 470-16992-6
Reference: Handouts |
| Textbook & other References |
the course materials using textbooks, PPTs, and board lectures
iLearning dashboard |
| Teaching Aids & Teacher's Website |
the course materials using textbooks, PPTs, and board lectures
iLearning dashboard |
| Office Hours |
| Thursdays 8:10~9:00 and12:00~12:30 |
| Sustainable Development Goals, SDGs |
| 04.Quality Education 05.Gender Equality 08.Decent Work and Economic Growth 09.Industry, Innovation and Infrastructure 12.Responsible Consumption | include experience courses：N |
|