Week 1: Six Sigma Introduction
Introduction to the SIx Sigma Methodology and the DMAIC process improvement cycle. We learn about 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 our 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.
What you will 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 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.
- Professionals and executives of quality management from production and service companies
- Employees from all business areas and levels actively involved in quality systems and quality improvement
- Interested public