EMGT E446 - Statistical Methods in Six Sigma
- Credit Hours: 4R-0L-4C
- Term Available: -
- Graduate Studies Eligible: Yes
- Prerequisites: MA 223 or MA 382 or consent of instructor.
- Corequisites: None
A course on statistical methods used in the Six Sigma to include the following topics: the history of Six Sigma, certification and belts, the Define-Measure-Analyze-Improve-Control (DMAIC) methodology, review of statistical tools associated Six Sigma (e.g., the “Magnificent Seven,” inference, graphics), project election tools (e.g., Voice of Customer, Affinity Diagram, Critical to Quality Diagram), Define phase tools (e.g., Spaghetti Diagram, Kano Model, Root Cause Analysis, Cause and Effect Diagram), computation of Sigma Levels and Defects per Million, Measure phase tools (e.g., Gage Repeatability and Reproducibility, Attribute Agreement Analysis, descriptive and inferential statistics), Analyze phase tools (e.g., Cause and Effect Matrix, Failure Modes and Effects Analysis, Design of Experiments), Improve phase tools (e.g., practical applications to improve a real-world process), Control phase tools (e.g., control charts, capability analysis), cost of poor quality, and the use of statistical software for data analysis. The use of real-world data in exercises will be emphasized. Other topics to be included as time allows: lean methodologies, team formations, Taguchi’s loss function, regression, process tampering.