Semiconductor Process Control

(3-0-0-3)

CMPE Degree: This course is Not Applicable for the CMPE degree.

EE Degree: This course is Not Applicable for the EE degree.

Lab Hours: 0 supervised lab hours and 0 unsupervised lab hours.

Technical Interest Group(s) / Course Type(s): Nanotechnology

Course Coordinator:

Prerequisites: CEE/ISYE/MATH 3770

Corequisites: None.

Catalog Description

This course is designed to explore methods of applying statistical process
control and statistical quality control to semiconductor manufacturing
processes. Students will be required to complete a design project.

Textbook(s)

Fundamentals of Semiconductor Manufacturing and Process Control, Introduction to Statistical Quality Control

Course Outcomes

Not Applicable

Student Outcomes

In the parentheses for each Student Outcome:
"P" for primary indicates the outcome is a major focus of the entire course.
“M” for moderate indicates the outcome is the focus of at least one component of the course, but not majority of course material.
“LN” for “little to none” indicates that the course does not contribute significantly to this outcome.

1. ( Not Applicable ) An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics

2. ( Not Applicable ) An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors

3. ( Not Applicable ) An ability to communicate effectively with a range of audiences

4. ( Not Applicable ) An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts

5. ( Not Applicable ) An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives

6. ( Not Applicable ) An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions

7. ( Not Applicable ) An ability to acquire and apply new knowledge as needed, using appropriate learning strategies.

Strategic Performance Indicators (SPIs)

Not Applicable

Course Objectives

Topical Outline

1. Relevant Statistical Distributions in Semiconductor Manufacturing
2. Sampling and Estimation
3. Hypothesis Testing
4. Attribute Control Charts for Defect Control
5. Variable Control Charts for Process Control
6. Advanced Control Charts (CUSUM, EWMA, Multivariate)
7. Time-Series Modeling of In-Situ Sensor Data
8. Experimental Design Methods for Characterizing IC Fabrication Processes
9. Analyzing Experimental Results
10. Statistical Software Packages
11. Analysis of Process Variation Using Principal Components
12. Response Surface Modeling of Unit Processes
13. Integrated Circuit Design for Manufacturability
14. Parametric and Catastrophic IC Yield Modeling