In every manufacturing operation there is variability. The variability becomes evident whenever a quality characteristic of the product is measured. There are two basically different reasons for variability, and it is very important to distinguish between them.

Normal Distribution

Variability Inherent in the Process occurs even when all adjustable factors known to affect the process have been set and held constant during its operations. There is a pattern to the inherent variation of specific stable processes, and their different basic characteristic forms of data from different processes. However the most frequent useful pattern is called a “Normal Distribution” as shown in the figure. This is frequently found in manufacturing processes and technical investigations.

Log-Normal Distribution
A bimodal distribution composed of two normal distributions

There are other basic patterns of variability; they are referred to as non-normal distributions. The “Lognormal Distribution” figure shows a distribution that is fairly common when making acoustical measurements and certain measurements of electronic products. If the logarithms of the measurements are plotted, the resulting pattern is a normal distribution (hence the name). For manufacturing processes the basic lognormal distribution does not exist very frequently. Many apparent basic lognormal distributions of data are not the consequence of a stable lognormal process but rather of two basically normal distributions with a large percentage produced at one level, as shown in the “Binomial Distribution” figure. The net result of these two distributions can produce a bimodal distribution with presents a false appearance of being inherently lognormal. On the other hand human knowledge work and intellectual property processes to produce true lognormal distributions. Examples are basic inventor activity and patent values.

Variability from Assignable Causes is the other important source of variability. This type of variation, named by Dr. Walter Shewhart, often contributes a large part to the overall variability of a process. Evidence of this type of variability offers important opportunities for improving the uniformity of product. The process average may change gradually as a result of gradual changes in temperature, tool wear, or operator fatigue. Or the process may be unnecessarily variable because two operators and machines are performing at different averages. Variability resulting from two or more processes operating at different levels, or a single source operating with an unstable average, are typical of production processes. They are the rule, not the exception to the role. This second type of variability must be studied by various techniques and data analysis which are discussed in this chapter. After the responsible factors are identified and corrected, continuing control of the process will be needed to ensure on going quality.