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Six Sigma: Analyze, Improve, Control
- Self-paced
- Free Access
- Fee-based Certificate
- 8 Sequences
- Introductive Level
Course details
Syllabus
Week 1: ANALYZE - Root Cause Analysis
Introduction to methods for root cause analysis, including Cause and Effect (Fishbone diagrams) and Pareto Charts. We learn how to perform statistical correlations and regression analyses.
Week 2: ANALYZE - Inferential Statistics
Learn the inferential statistics techniques of confidence intervals and hypothesis testing in order to use sample data and draw conclusions about or process centering.
Week 3: IMPROVE - Design of Experiments
Plan designed experiments and calculate the main and interaction effects.
Week 4: MEASURE - Analysis of Variance
Review how to perform a one-way Analysis of Variance (ANOVA) for comparing the between-factor variation to the within-factor variation for a single factor experiment.
Use a two-way ANOVA for testing the significance of the factor effects for a 2x2 DOE.
Week 5: CONTROL - SPC and Control Charts
Implement Statistical Process Control (SPC) & Control Chart Theory for monitoring process data and distinguishing between common cause variation and assignable cause variation. Construct X-bar and R Charts by calculating the upper and lower control limits and the centerline.
Week 6: CONTROL - Other Control Charts
Understand other control charts, including p-and c-charts and I/MR, and EWMA Charts and review of the Control and Response Plan for Six Sigma projects.
Week 7: Quality Tools: FMEA, 8D, 5 Whys
Use several important tools used in quality management, including the 8 Disciplines (8D) and 5 Whys, and learn the concept behind Design for Six Sigma (DFSS).
Week 8: Six Sigma Scenario and Course Summary
Step through a full Six Sigma scenario, covering all phases of the DMAIC process improvement cycle.
Prerequisite
This course reviews basic statistics used in Six Sigma and quality management, applying them to quality problems and methods. Therefore, basic math skills are necessary.
Instructors
Martin Grunow
Professor of Production and Supply Chain Management
Technical University of Munich
Holly Ott
Senior Lecturer in Operations Managementat Technical University of Munich and Professor Production Management at Rosenheim University
Technical University of Munich
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