• 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 into Critical-to-Quality parameters.
• To understand the concept of random variables, probability mass functions, and probability density functions.
• To calculate probabilities using the Normal distribution.
• To understand how the Central Limit Theorem applies to sampling and how to set up sampling plans.
• To understand the importance of a Measurement System Analysis in a Six Sigma project.
• To calculate Process Yield and Process Capability.
• To perform a risk assessment using a Failure Modes and Effects Analysis.
• How to apply the Define and Measure phases of the DMAIC cycle in your work or research, in order to identify problems and quantitatively assess the impact of process changes using statistical analysis.

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.

"My name is Arantxa and I am from Mexico, I'm a Manufacturing Engineer. This course has been great to take. The topics are very well explained in each of the videos and it also helps a lot with the practical examples and lectures about how to apply the different concepts and how are they used in the industry. This course has helped me to get a good command of the knowledge on Six Sigma methodology and to learn new concepts and topics which were unfamiliar to me. Holly has been an excellent teacher, making the lectures really interesting and easy to take. I highly recommend this course and I'm looking forward to taking the next course in this plan." - Aranta Almazan

"This course has helped me understand better what process improvement entails. I have also got know more about satisfying the needs of the customer, how to collect accurate data, how to execute improvement projects, etc. it has also helped me to gain insight into how to organize my workplace to improve my efficiency and effectiveness. Applying the visual management concept at my workplace has helped boost employee morale and performance." - Emmanuel Nyarko

"I absolutely loved this course! I had seen some of the concepts in my bachelor´s but they taught everything as a rule that one should memorize without teaching the why it works that way or how it works. The course provides the deeper knowledge needed to understand the statistics and concepts that may be familiar to us, it also provides a great number of examples that help with the retention of the knowledge and the understanding of how the theory is relevant and applicable in the real world. Although online is not my favorite learning method, and I would rather be in TUM learning everything I felt I did get the value I paid for. Even in an online format, I leave feeling like I learned many new things that will help me in my career. Looking forward to doing the other courses to get the Green Belt Certification." - Isabella betanco

"First of all, I'd like to thank the core team and all those involved in the development of this course, and thereby for providing this opportunity. My name is Thales Felipe, I am from Brazil, and, at the moment, I am B.Eng in industrial engineering. I have gathered experience in the transportation sector, particularly in the truck industry. Within this context, the 3 specific things this course has helped me out with are:

1. Extended the understanding of customer's expectations with defining methods, e.g. the Kano Analysis;
2. Strengthened the capacity of process analysis
3. Solidified acquired knowledge that had been provided in the bachelor's degree, specifically in quality engineering, which is my major." - Thales Felipe

"I have been very satisfied by the depth and breadth of this course, including the statistics presented. I very much appreciate access to statistical software to use for the final project. Reading the student forums has been very informative, and teaching assistants seem to respond to any query within hours. This is very impressive considering the course is being taken by people from all over the globe. I have some background in 6 sigma but have learned a lot about more aspects like CPK. I look forward to completing the other courses in this series so that I can bring this knowledge to bear on quality improvement projects in the hospital." - Matthew Hollan