| |
Nov 21, 2024
|
|
|
|
|
IE 300 - Engineering Data Analysis and Process Improvement3 Credit Hours
Engineering statistical methods as applied to modern engineering and business environments, process improvement, inferences about process output and behavior, and measurement systems. Content includes engineering and statistical tolerances; tools for creative problem solving and process analysis; statistical process control including capability analyses and measurement studies, including gauge R&R studies; quality control in lean environments including short runs and mixed model environments; service applications including non-normality and autocorrelation; an overview of the theory of constraints; one-way analysis of variance; design of experiments including screening, two-factor, and fractional designs; and Six Sigma, including DMAIC and DFSS methodologies. A lab component emphasizes the use of teams to provide hands-on experiences, enhance learning, and develop skills in group dynamics.
Contact Hour Distribution: 3 hours lecture.
(RE) Prerequisite(s): Statistics 251.
Comment(s): Available to other majors who have completed an introductory course in probability and statistics.
Registration Permission: Consent of instructor.
Add to Portfolio (opens a new window)
|
|
