Statistical Process Control for Fabs

Students will learn to apply statistical methods to analyze process data, identify sources of variation, and implement control strategies in a fab environment. Key topics include control charts, process capability analysis, and design of experiments. The course emphasizes practical application through real-world case studies relevant to semiconductor fabrication.

Course outline

Lectures, virtual labs, and graded assignments — completed in your browser.

01Introduction to Statistical Process Control in Semiconductor Manufacturinglecture

02Fundamentals of Statistics: Data Types, Distributions, and Variabilitylecture

03Understanding Process Variation and Its Impact in Fabslecture

04Control Charts for Variable Data: X-bar and R Chartslecture

05Control Charts for Variable Data: X-bar and S Chartslecture

06Control Charts for Individual Measurements (I-MR Charts)lecture

07Control Charts for Attribute Data: p and np Chartslecture

08Control Charts for Attribute Data: c and u Chartslecture

09Process Capability Analysis: Cp, Cpk, Pp, Ppklecture

10Measurement System Analysis (MSA): Gage R&Rlecture

11Introduction to Design of Experiments (DOE) for Process Optimizationlecture

12Advanced SPC Topics: Short Run SPC and EWMA Chartslecture

13Implementing SPC in a Fab: Software Tools and Best Practiceslecture

14Final Project Presentations and Course Reviewlecture

Syllabus

Each week will feature lectures, readings, and problem sets, culminating in a lab exercise or case study for practical application. Expect active participation in online discussions and timely submission of assignments. Quizzes will be given periodically, and a final project applying SPC to a semiconductor process will be required. All assignments must be completed independently unless group work is explicitly authorized. Academic integrity is paramount and will be strictly enforced.