An introduction to the Six Sigma methodology and DMAIC cycle for process improvement with a focus on the Define and Measure phases. In this course, you will start by gaining an understanding of the background and meaning of Six Sigma and the five steps of the DMAIC process improvement flow: Define, Measure, Analyse, Improve, and Control.
In this course, we will start with the Define phase, where you will 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.
We continue with the Measure phase, where you will learn how to map a process and use the necessary statistical techniques to establish the baseline performance of a process. You will also learn the basics of a Measurement System Analysis and calculate the process capability. We will cover topics such as Tolerance design and Failure Mode and Effects Analysis (FMEA) as well as review the entire Six Sigma Roadmap as preparation for the second course in this series.
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 Technical University of Munich Lean Six Sigma Yellow Belt Certification, confirming mastery of the fundamentals of Lean Six Sigma to a Yellow Belt level, based on the American Society of Quality’s Body of Knowledge for the Certified Six Sigma Yellow Belt.
What you’ll learn
- To understand the background and meaning of the Six Sigma methodology and the role of the DMAIC process improvement cycle.
- To identify the Voice of the Customer and translate it into Critical-to-Quality parameters.
- To calculate process yield and process capability.
- How to apply the Define and Measure phases of the DMAIC cycle in your work or research, to identify problems and quantitatively assess the impact of process changes using statistical analysis. share then reinforced using interactive case studies, which illustrate the application of the statistics in quality improvement situations.
Week 1: Six Sigma Introduction
Introduction to the Six Sigma Methodology and the DMAIC process improvement cycle. We learn about the cost of quality and how to calculate process yield.
Week 2: DEFINE – Defining the Problem
We discuss how to understand customer expectations, using the Kano Model to categorize quality characteristics. We 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. We cover descriptive statistics, emphasizing the importance of clearly communicating the results of our 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
We 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: Course Summary and Review.
- Martin Grunow
- Holly Ott