How do you choose a Green Belt Project for Certification?
What are the requirements for an initial Six Sigma Green Belt Project for Certification?
The requirements relate to the tools that a Green Belt should be proficient in. This blog will tell you what we at Six Sigma Development Solutions, Inc. suggest are attributes of a good Sigma Green Belt Project.
A Green Belt Project has been rumored to have a requirement of a $150,000+ savings. At SSDSI, we do not have a ROI requirement for dollars saved. We do have a requirement of having a measurable effect on value. That effect has to be initially determined in a well-developed Six Sigma Charter.
What are the attributes of a good Green Belt Project?
We should not “already know the solution” to the problem. A good Six Sigma project has a solution that must be discovered through the process of analysis.
We should understand the Output (the “Y”) in measurable terms. For example, if something is good or bad, do we know exactly what separates the good from the bad? Is this a subjective measurement that could be interpreted differently by different operators?
We should have measurable and controllable inputs (X’s).
For a Green Belt Project, these measurable and controllable inputs (X’s) should be both Attribute/Discrete data and Variable/Continuous data.
For example, a process to fill a bottle full of a liquid could have the following “X’s”: Fill Date (Discrete), Fill Time (Discrete), Fill Operator (Discrete), Fill Height (Variable), Fill Weight (oz.) (Variable), Fill Liquid Pressure (Variable), etc.
These measurable inputs (X’s) combine to produce an Output (Y): Some Measure of Good or Bad. The “Y” could also be a measure of Capability using CpK/PpK.
This past data should be collected to populate a Multi-Vari sheet.
For example, a Multi Vari Sheet could be an Excel spreadsheet where each row has a measurement for each of the “X’s” and each “Y” (if more than one “Y”).
In our “Bottle Filling” scenario, each time a bottle is filled, there should be a measurement for each “X” that creates the “Y.”
If we take a sample of 100 bottles, we should have 100 rows of data. This data helps us to do hypothesis testing as well as other statistical analysis to understand the true nature of the process.
In a Green Belt Project, once discovering the Key Process Input Variables (KPIV’s), we might find that we do not know what specifications would optimize the KPIV’s.
For example, if we find that Fill Liquid Pressure is a KPOV but we do not know the Optimum Pressure Tolerance (Upper Spec Limit, Target and Lower Spec Limit) to get an Optimum Product (Output “Y”) then we can use a Design of Experiments (D.O.E.) to find the Optimum Pressure Tolerance.
There will be some difference in a good Six Sigma Green Belt Project between Service and Industrial disciplines.
Generally in a Service discipline, you will have more Attribute/Discrete “X’s” (because most Service disciplines will tell you that “we don’t make widgets with measurable tolerances”). Because of this, D.O.E. is less prevalent in a Service discipline.
Can you give us an idea of a good Green Belt Project in your organization with the attributes explained in this blog?