Lean Six Sigma Black Belt Project Requirements

The requirements relate to the tools that a Black Belt should have proficiency using. This blog will tell you what we at Six Sigma Development Solutions, Inc. suggest as attributes of a good Sigma Black Belt Project.

A Black Belt Project has been rumored to have a requirement of a $300,000+ 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 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/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 Black 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) with 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 Black Belt project, once discovering the Key Process Input Variables (KPIV’s), we might find that we don’t know what specifications to 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.

A Black Belt should be taught to understand the Design of Experiment (D.O.E.) toolset.

This toolset will help you to statistically get a better understanding of what those specifications should be for the KPIV’s in question in order to get a more optimum output.

There will be some difference in a Good Six Sigma Black Belt project between Service and Industrial disciplines.

In a Service discipline, in general, you will have more Attribute/Discrete “X’s” (Because most in 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 Black Belt project in your organization with the attributes explained in this blog?

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