Course Syllabus

Course Information：

Year-Semester Course Number Course Name Phase Credits Hours Required/Elective Instructor Class Student NO. Withdraw Note

Spring Semester
Year 2023 313638 Time Series Analysis and Process Adjustment 1 3.0 3 ★ Shu-Kai Fan GIEM
CMGT 5 1 工管所和管理博班合開

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Spring Semester Year 2023	313638	Time Series Analysis and Process Adjustment	1	3.0	3	★	Shu-Kai Fan	GIEM CMGT	5	1	工管所和管理博班合開

Course Plan：

Instructor Shu-Kai Fan　Office Hours

Email morrisfan@ntut.edu.tw

Last Updated 2022-12-26 12:10:33

Course Objective 本課程主要目的在於教導學生如何利用時間序列分析、品質製程管制、工程製程控制等方法來達成先進製程控制的目的。課程講述之內容包含下列課題:製程監控、製程調整、離散動態製程、時間序列模型、轉換方程模型、最佳回饋控制器、指數加權移動平均控制、遞迴式估計與自適應控制等。 The purpose of this course is to provide students a modern treatment of discrete-time advanced process control (APC) methods based on time series analysis, statistical process control (SPC) and engineering process control (EPC) for Quality Engineering in manufacturing. From an engineering perspective, process control is gaining recognition in the semiconductor industry as a means to compensate for equipment changes due to inconsistent operation, process drifts and process shifts. So, practical and theoretical components that comprise the foundation for the APC will be addressed as well.

Course Schedule 1 Process monitoring (SPC) vs. process control (EPC/APC) 2 Process monitoring (SPC) vs. process control (EPC/APC); 3 ARIMA (Box-Jenkins) time series models 4 ARIMA (Box-Jenkins) time series models 5 ARIMA (Box-Jenkins) time series models 6 ARIMA (Box-Jenkins) time series models 7 Transfer function (TF, input/output) models 8 Transfer function (TF, input/output) models 9 Midterm Exam 10 Review of Midterm Exam 11 Optimal stochastic controller design 12 Optimal stochastic controller design 13 EWMA controllers and the run-to-run (R2R) control problem 14 EWMA controllers and the run-to-run (R2R) control problem 15 Recursive estimation & self-tuning (ST) quality control 16 Recursive estimation & self-tuning (ST) quality control 17 Term Project Presentations

Evaluation and grading policy Grading Policy: Midterm Exam (30%), Homework (30%), Journal Paper Reading (20%), and Term Project (20%) due in part throughout the semester.

Materials All right reserved. Do not reproduce without permission.

Foreign-language textbooks:Yes
[Textbook] E. del Castillo, Statistical Process Adjustment for Quality Control, John Wiley, 2002. [References] (1) Box, G. E. P., Jenkins, G. M., and Reinsel, G. C., Time Series Analysis, Forecasting, and Control, 4th ed., 2008. (2) Montgomery, D. C., Forecasting & Time Series Analysis, 2nd ed., 1990. (3) Box, G. E. P., and Luceo, A., Statistical Control by Monitoring and Feedback Adjustment, 1997.

The access to curricular consultation Office Hours:

Monday: 10-12AM

The course corresponds to the SDGs

Note
按照CDC中央疫情指揮中心指示，視疫情狀況需要可採線上同步教學。
本課程乃採用 Microsoft Teams 遠距同步軟體。

Instructor	Shu-Kai Fan　Office Hours
Email	morrisfan@ntut.edu.tw
Last Updated	2022-12-26 12:10:33
Course Objective	本課程主要目的在於教導學生如何利用時間序列分析、品質製程管制、工程製程控制等方法來達成先進製程控制的目的。課程講述之內容包含下列課題:製程監控、製程調整、離散動態製程、時間序列模型、轉換方程模型、最佳回饋控制器、指數加權移動平均控制、遞迴式估計與自適應控制等。 The purpose of this course is to provide students a modern treatment of discrete-time advanced process control (APC) methods based on time series analysis, statistical process control (SPC) and engineering process control (EPC) for Quality Engineering in manufacturing. From an engineering perspective, process control is gaining recognition in the semiconductor industry as a means to compensate for equipment changes due to inconsistent operation, process drifts and process shifts. So, practical and theoretical components that comprise the foundation for the APC will be addressed as well.
Course Schedule	1 Process monitoring (SPC) vs. process control (EPC/APC) 2 Process monitoring (SPC) vs. process control (EPC/APC); 3 ARIMA (Box-Jenkins) time series models 4 ARIMA (Box-Jenkins) time series models 5 ARIMA (Box-Jenkins) time series models 6 ARIMA (Box-Jenkins) time series models 7 Transfer function (TF, input/output) models 8 Transfer function (TF, input/output) models 9 Midterm Exam 10 Review of Midterm Exam 11 Optimal stochastic controller design 12 Optimal stochastic controller design 13 EWMA controllers and the run-to-run (R2R) control problem 14 EWMA controllers and the run-to-run (R2R) control problem 15 Recursive estimation & self-tuning (ST) quality control 16 Recursive estimation & self-tuning (ST) quality control 17 Term Project Presentations
Evaluation and grading policy	Grading Policy: Midterm Exam (30%), Homework (30%), Journal Paper Reading (20%), and Term Project (20%) due in part throughout the semester.
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:Yes [Textbook] E. del Castillo, Statistical Process Adjustment for Quality Control, John Wiley, 2002. [References] (1) Box, G. E. P., Jenkins, G. M., and Reinsel, G. C., Time Series Analysis, Forecasting, and Control, 4th ed., 2008. (2) Montgomery, D. C., Forecasting & Time Series Analysis, 2nd ed., 1990. (3) Box, G. E. P., and Luceo, A., Statistical Control by Monitoring and Feedback Adjustment, 1997.
The access to curricular consultation	Office Hours: Monday: 10-12AM
The course corresponds to the SDGs
Note	按照CDC中央疫情指揮中心指示，視疫情狀況需要可採線上同步教學。本課程乃採用 Microsoft Teams 遠距同步軟體。