Process capability is the analysis of a process to determine its quality. A single or several quality characteristics are selected, some of which might be variable or attribute. For variable characteristics, the distribution of the data collected is for normality, and the distribution average p, and standard deviationσ are calculated. It has been shown in this and previous chapters that it takes a sample size of 30 measurements to directly obtain these two parameters and determine whether the distribution of data is normal. For low-volume production, the previous section discussed methods of determining a confidence interval for the two parameters. The confidence limits from these intervals could be used for worst-case determination of six sigma quality. For attribute processes, the defect rate is determined for parts that are manufactured in small quantities as prototypes, or from similar parts in current production. The reject rate can be translated into DPU (PPM), DPMO, FTY, Cpk, or sigma quality, as was shown in Chapters 2 and 4.
The amount of sampling required for determining process capability is also dependent on whether the process has been in production (existing) for some time or is a new process is being created. It is also desirable that once the process is operating on a regular basis, and a reasonable level of quality is achieved, the quality characteristic(s) being measured be charted for statistical control in control charts. For quality level approaching six sigma and beyond, control charting might not be required; a total quality management program to monitor individual defects per period as opposed to use the sampling methods of control charts could be substituted.