Offered By: edX
Duration: 8 weeks long, 3-4 hours a week
Understand the background and meaning of Six Sigma and the five steps of the DMAIC process improvement flow: Define, Measure, Analyze, Improve and Control. Discuss what “Quality” means and how to identify the Voice of the Customer.
You will learn how to set an improvement project goal, calculate process yield, and identify Critical-to-Quality parameters.
You will learn how to map a process and to use the necessary statistical techniques to establish the baseline performance of a process and to calculate the process capability.
To complement the lectures, we provide interactive exercises, which allow learners to see the statistics “in action.” Learners then master the statistical concepts by completing practice problems. These are then reinforced using interactive case studies, which illustrate the application of the statistics in quality improvement situations.
Upon successful completion of this program, learners will earn the TUM Lean and Six Sigma Yellow Belt certification, confirming mastery of Lean Six Sigma fundamentals to a Green Belt level. The material is based on the American Society for Quality (www.asq.org) Body of Knowledge up to a Green Belt Level. The Professional Certificate is designed as preparation for a Lean Six Sigma Green Belt exam.
Week 1: Six Sigma Introduction Introduction to the Six Sigma Methodology and the DMAIC process improvement cycle. Understand the contributors to the cost of quality. Discuss the difference between defects and defectives in a process and how to calculate process yield, including a comparison of processes of different complexity using the metric DPMO.
Week 2: DEFINE – Defining the Problem Discuss how to understand customer expectations, using the Kano Model to categorize quality characteristics. Start the first and difficult task of a Six Sigma project, Defining the Problem, and review the key content in a Project Charter.
Week 3: MEASURE – Statistics Review Review of random variables and probability distributions used commonly in quality engineering, such as Binomial, Poisson, and Exponential. Cover descriptive statistics, emphasizing the importance of clearly communicating the results of your project.
Week 4: MEASURE – Normal Distribution Learn the characteristics of the Normal Distribution and how to use the Standard Normal to calculate probabilities related to normally distributed variables. Cover the Central Limit Theorem, and how it relates to sampling theory.
Week 5: MEASURE – Process Mapping Introduce Process Mapping, including SIPOC and Value Stream Mapping. We identify the Critical-to-Quality characteristic for a Six Sigma project
Week 6: MEASURE – Measurement System Analysis
Learn the basics of Measurement Theory and Sampling Plans, including Precision, Accuracy, Linearity, Bias, Stability, Gage Repeatability & Reproducibility
Week 7: MEASURE – Process Capability Introduction to Process Capability and the metrics CP/CPK for establishing our baseline process performance.
Week 8: Quality Topics and Course Summary Cover the basics of Tolerance Design and the risk assessment tool failure Mode and Effects Analysis (FMEA).
Review the complete Six Sigma Roadmap before summarizing and closing the course.
Martin Grunow and Holly Ott