Data Science in Manufacturing Quality Control credit: 3 or

4 Hours

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. 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 .