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OVERVIEW
Why Do Six Sigma
Reading Assignment
Unit Quiz

How to Deploy Six Sigma
Reading Assignment
Unit Quiz
DEFINE
Project Definition
Reading Assignment
Unit Quiz

Project Scheduling
Reading Assignment
Unit Quiz

Change Mgmt & Teams
Reading Assignment
Unit Quiz
Tools
Reading Assignment
Unit Quiz

Est. Process Baseline
Reading Assignment
Unit Quiz

X Bar Charts
Reading Assignment
Unit Quiz

Individuals Data
Reading Assignment
Unit Quiz

Process Capability
Reading Assignment
Unit Quiz

Attribute Charts
Reading Assignment
Unit Quiz
Lean Methods
Reading Assignment
Unit Quiz

Intro to Regression
Reading Assignment
Unit Quiz
Tools
Reading Assignment
Unit Quiz
Tools
Reading Assignment
Unit Quiz

FINAL EXAM



Gatlin Education Six Sigma Green Belt - OVERVIEW Why Do Six Sigma - Page 3




Graphical View Of Six Sigma

The graphic shown here illustrates the concept of a Six Sigma level of performance. We measure from a process and see that its output over time is stable and represented by the burgundy distribution shown. The three Sigma level of the process is shown in the graph at the outer limits, or tails, of the process distribution. We use these three sigma levels of the process to look for process shifts on an SPC control chart.

Actually, the distribution goes beyond the three sigma level in both its positive and negative directions, but the tails are so small as we move beyond three sigma that we don�t often see any data beyond the plus or minus three sigma levels. This is why a control chart works so effectively: when we see data beyond the three sigma levels it is very likely the process has shifted.

We see from the graph that the customer requirements, the upper specification limit USL and the lower specification limit LSL, are quite a distance from the process target. In fact, in this case they are located at the plus and minus six sigma level of the measured process. The implication of this is that the process will only exceed the customer requirements a very small percent of the time. If the process is Normally distributed, we can calculate this probability as 2 times in a billion opportunities.