Modeling Non-Normal Data Using Statistical Software
Process control and process capability can now be modeled using non-normal distributions.
Consider the following examples of key quality characteristics for different products:
• Trace contaminant concentration in a semiconductor raw material.
• Noise level from a portable generator.
• Concentricity of an engine drive shaft.
• Distance to bogie of an airplane wing profile.
• Breaking strength of an LCD screen.
Customers expect the suppliers of these products to provide proof of process stability and process capability. When suppliers create control charts and run capability analyses, they assume that their data follow a normal distribution. However, the natural distribution of these quality characteristics— and hundreds more like them— is not the normal distribution.
In the past, this situation posed major challenges. Today, however, this problem can be easily solved using the calculation capabilities of statistical software and our understanding of distributions that provide good models for most non-normal quality characteristics, such as the exponential, lognormal, and Weibull distributions. Minitab Statistical Software, from Minitab, State College, Pa., can perform control chart and capability calculations for quality characteristics that do not follow the normal distribution.
Due to the equations in this article a PDF has been made available for you to download.
