The chart below shows the theoretical defect rates that can be expected from various process sigma levels, assuming that the underlying data is normally distributed.This chart can be used in a couple of different ways -For continuous data collected over the short term, calculate theprocess sigmaand find the value in the Short Term Sigma Level column. The theoretical defect level over the long run is noted in the Defects Per Million column.
If data has been collected over sufficient time to include long term variation sources, use the Long Term Sigma Level column.
In cases where attribute data exists (typically in the form of % defective), it is sometimes desirable to know the equivalentprocess sigmafor the process, even though the data may not follow a normal distribution. In these cases, convert the known defect rate into a defects-per-million value and find it on the chart.
Theprocess sigma can then be found in either of the two sigma level columns, depending on whether the defect rate represents short or long term data.Note that the long term sigma value is 1.5 less than the short term sigma value, to account for a1.5 sigma mean shiftover the long run.
The Pareto Principle (also known as the80/20 rule) states that in many situations, a small number factors will influence a given outcome the most, even when there are many more factors in the equation. For example, a student’s likelihood of getting into college will be (mostly) determined by two things: high school grades and standardized testing scores. Books have been written about all the factors that affect college acceptance decisions, but the reality is that excellent grades and competitive testing scores make up the majority of the equation for most schools.
The Pareto Principle is at work everywhere, and the real goal of any Six Sigma project is to find the top two or three factors that make up thetruePareto chart for a given problem, and then control those factors to achieve breakthrough performance. It’s that simple. But finding thetruePareto chart behind a given problem can be very challenging at times.
Here is a simple Pareto chart showing reasons for arriving late to work over the past year
5 - Why
When a basic problem is being addressed in the DMAIC process, the 5-Why approach is a good method for exploring and documenting root causes. The idea behind the 5-Why approach is to ask “Why?” five times when exploring the reason for a problem, hopefully arriving at the root cause, on or before the 5th
Why. Here is an example:Problem: We shipped the wrong item to our customer Why?Wrong item picked from inventory Why?Supplier put the incorrect part number on the box when it was shipped to our location Why?The operator at the supplier placed the wrong part number label on the box Why?The supplier is printing part number labels in batches of 20, and it is easy to pick up the wrong label Why?Supplier did not anticipate this problem when they designed their packaging processSo in the above case, both the 4thand 5thWhy’s can be addressed, and fixing the 5thWhy would result in a strongpreventiveaction for the future.
Below is a more familiar format for conducting a 5-Why analysis when multiple causes exist
Six Sigmaand its accompanyingDMAIC processare about identifying and controlling the true causes behind costly variation. Fishbone diagrams, also known as cause-and-effect diagrams, are about organizingpossiblecauses behind a given problem. Of course, all possibilities will need to be proved or disproved during the Analyze phaseof the project.
Fishbone diagrams are easy to construct, and the following example looks at possible causes of employee turnover, based on an excellent article fromSigma Assessment Systems, Inc
Click here for the Excel fileused to create this Fishbone Diagram.
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