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## About this lesson

Six Sigma projects strive to achieve a process capability that represents Six Sigma quality. The calculation of process capability is quite different depending upon whether the data is variable or attribute. This lesson will present the technique used for determining process capability with attribute data.

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## Quick reference

### Process Capability with Attribute Data

The determination of process capability is quite different depending upon whether the data is variable or attribute. Attribute data relies on a count of defects in the data set rather than spec limits and descriptive statistics.

### When to use

Process capability and process sigma are useful techniques for determining if a process is able to deliver consistently good results. When using these approaches, if the data is in the form of attribute data, then these techniques must be used rather than those for variable data.

### Instructions

Attribute data process capability differs from variable data process capability in several important respects. There is no measurement scale and numerical value to the data. Rather the basic unit of measure is a count of defects with respect to a standard. There is no upper and lower spec limit, instead there are opportunities to either meet the standard or fail the standard. There is no descriptive statistics of the measure, there is just the count. Attribute data can be converted to variable data using the central limit theorem or possibly using a transformation such as the binomial distribution. However, it is much easier to just use counts and the attribute data lookup table.

The attribute data lookup table relies on determining a DPMO (defects per million opportunities) value for the process. That value is used as the starting point to enter the lookup table and determine a process sigma and process yield.

It is important to understand DPMO, defects and defectives. These terms are used often in a discussion of Lean Six Sigma and control charting. The table below shows the definition of these terms and several others that are also relevant to SPC control charting. Thoroughly learn the definitions of these acronyms and how to calculate them.

The attribute data process capability lookup tables are found in numerous references and online. If taking the IASSC exam, you will have access to the tables if needed for any of your questions. To use the table, first calculate the DPMO for the process characteristic. Using that value, find an entry that is close to that number. If your DPMO value is between two entries, feel free to interpolate the data in the other two columns. The other columns are a process sigma, which directly correlates to the process capability value. Also, the table has a column for expected yield.

### Hints & tips

- It is easy to confuse defects and defectives. Defects apply to each unique opportunity that is checked against a standard. Defective always applies to products, processes or systems that normally have many opportunities.
- DPMO is determined for a particular type of opportunity, so it does correlate to a Cpk for that characteristic. However, defective units uses measures like PPM (parts per million) and each defective unit could have many different types of defects on it.
- Generally, when discussing attribute data processes, the process sigma is used instead of converting that sigma to a process capability.
- While I have talked about the conversion of process sigma to Cpk based upon a simple understanding of the Cpk metric, there is a view that conducts a 1.5 sigma shift when doing the conversion. The rationale for this is somewhat murky, so I don’t endorse it. However, you should be aware that your local Lean Six Sigma methodology may include this shift when converting from sigma to process capability.

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