Course Websites

ME 453 - Data Science in Manufacturing Quality Control

Last offered Fall 2022

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.

Related Faculty

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

Prerequisites

TitleSectionCRNTypeHoursTimesDaysLocationInstructor
Data Sci in Mfg Quality CntrlDSG73109LCD31300 - 1420 M W  106B1 Engineering Hall Chenhui Shao
Data Sci in Mfg Quality CntrlDSU73108LCD31300 - 1420 M W  106B1 Engineering Hall Chenhui Shao