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A statistical estimate that describes the process’s ability to fulfill the characteristic’s requirements with a stable, in-control process. It is a measure of an item’s inherent variability as a product of the processes involved and provides a means to assess whether the output of a process is within the requirements or specifications.
Many companies use SPC to control their manufacturing and assembly processes. Other companies use 100% inspection and some companies do nothing. How can one choose between these three alternatives?
To make a rational choice, some questions need to be answered.
In the article Process Capability I – Overview and Indices, the main process performance indices were defined. In the article Process Capability Analysis II – Estimating Percent Defective, ways to calculate the percent defective were introduced.
In this article, the mathematical connection between the Cp index and percent defectives is made.
How is a manufacturing process determined to be capable of producing parts that meet engineering requirements? Some, like the finish of a gear tooth are critical, while the roughness of a non-contact surface isn’t critical. The critical characteristics need to be identified and checked to determine if the process is capable.
This article defines the analysis concepts and indices.
Process capability assessments (PCA) start during the product development process and continue into series production. Prototype parts are created by a variety of methods, ranging from hand-crafted parts to short term manufacturing in a production intent process under factory conditions. The methods that are closest to series production are the most realistic.
The connection between the specifications or drawings or design requirements and the manufacturing process is the capability of the process to consistently create items within spec.
A ratio of the specification over the spread of measured items provides a means to describe the process capability.
The ratios rely on the standard deviation or spread of the produced items. The index is meaningful only if the process is stable. Thus beyond making sure the measurements have minimal measurement error, check the stability using the appropriate control chart.
In this article we are assuming the measurements are normally distributed, yet knowing that is not always the case, you can calculate capability indices using the actual distribution.
The indices will have similar interpretations yet take care when applying these concepts using other than normal distribution data.
