Capability is just one of the many performance metrics available in six sigma metrics. Others include throughput, Overall Equipment Effectiveness, cycle-time, and so on. It comes in two forms which depends on your type of data , variable and attribute. Both look at performance versus specification(s). Here we focus on the application of attribute type data. For a detail look at variable data then please visit this page
Attribute capability is expressed as Defects per Unit (DPU), calculated as:
It is necessary, therefore, to define the unit and the defect. A unit is the physical output from the process. It is something that is inspected, evaluated, or judged to determine suitability for use. It is something delivered to customers or users. Examples include..:
A defect is anything that does not meet a critical customer requirement or an established standard. Examples include
*Typographical error on an invoice
*Customer call dropped
*Missing order information
There can be multiple defect types for each unit and multiple defects of each type per unit. When evaluating DPU, you decide on the definition. DPU could mean the total of all the individual defects (or errors) on each unit. Or it can be applied to individual defect types, thus identifying which defect type is creates the largest loss.You can count defects per unit, or count units defective.
You generally use attributes to identify opportunities by prioritizing based on the commonest defect type (typically using a Pareto Chart).
DPU does not take process complexity into account To do this, you measure Defects per Million Opportunities (DPMO), defined as
The definition of unit and defect is the same as before. To understand oppportunities, you must know the difference between defects and defectives. A defective unit is any unit containing a defect. There can be multiple defects in one defective unit and the defectives units are a result of defects. It is impossible to reduce the number of defective units without reducing the number of defects. Opportunities therefore are the number of potential chances within a unit to be
It can often be difficult to identify all opportunities and it generally depends on the Customer. Examples include...
*Purchase Orders. Opportunities = Number of critical fields x 2 because the fields can either be empty or incorrect.
*Customer Call. Opportunities = Number of defect reason codes (for example, a missed call, a dropped call, an unresolved call, a call sent to a manager, a call that requires a call back, and a call that lasts longer than 15 minutes).
Opportunities are notoriously open to abuse. A process could be artificially improved if there are more opportunities considered at the end of the project than at the beginning. So be consistent when defining the opportunities.
The roadmap to calculate the capability for attribute type data follows:
For the metrics wanted, define the goals and specifications. Ensure the validity of the metric .
Define the Unit, Defect, and Opportunity as per the descriptions above.
Collect process data. Collect at least 100 data points if the proportion of defects is greater than 5%. If the defect rate is less than 5%, then the sample size needs to be increased accordingly or it might be better to switch to a variable type metric.
Calculate DPU and DPMO as per the equations above. From the DPMO calculate the sigma rating from a lookup table .
Interpreting The Output
DPMO is the capability measurement primarily used to calculate process sigma rating. The infamous 3.4 Defects per Million representing "Six Sigma performance" is actually 3.4 DPMO. Some novice belts worry about meeting the required Sigma Rating. They assume the project is only successful if the process has a six sigma defect rating when the project is complete. This is untrue; sx sigma as an initiative, is about breakthrough performance improvement. If a change generates
significant savings, additional capacity, or revenue then the sigma rating is really a secondary concern.