ME 453

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.