Course Websites
ME 453 - Data Science in Manufacturing Quality Control
Last offered Fall 2023
Official Description
Manufacturing quality management in the big data era; quality improvement philosophies; statistical modeling of process quality; inferences about quality; statistical process control; control charts; machine learning and applications in quality engineering; quality classification/prediction with machine learning; design and implementation of quality monitoring systems based on supervised learning; measurement system analysis (gage R&R study); design of experiments. Course Information: 3 or 4 undergraduate hours. 3 or 4 graduate hours. Prerequisite: ME 270; either IE 300 or STAT 400; either MATH 257 or MATH 415.
Subject Area
- Mechanical Science and Engineering
Course Description
This course covers manufacturing quality management in the big data era; quality improvement philosophies; statistical modeling of process quality; inferences about quality; statistical process control; control charts; machine learning and applications in quality engineering; quality classification/prediction with machine learning; design and implementation of quality monitoring systems based on supervised learning; measurement system analysis (gage R&R study); and design of experiments.
Credit Hours
3 or 4 hours
| Title | Section | CRN | Type | Hours | Times | Days | Location | Instructor |
|---|---|---|---|---|---|---|---|---|
| Data Sci in Mfg Quality Cntrl | DSG | 73109 | LCD | 3 | 1300 - 1420 | M W | 106B1 Engineering Hall | Chenhui Shao Sixian Jia |
| Data Sci in Mfg Quality Cntrl | DSU | 73108 | LCD | 3 | 1300 - 1420 | M W | 106B1 Engineering Hall | Chenhui Shao Sixian Jia |
| Data Sci in Mfg Quality Cntrl | ZJ1 | 78784 | LCD | 3 | - | Chenhui Shao |