Control Charts
Statistical process control was developed as a feedback system that aids in preventing defects rather than allowing defects to occur. One element of a process control system is control charts. Dr. Walter Shewhart defined the concept of common and special cause variation during the 1920s at Bell Laboratories. He developed a tool that he called the control chart, which could graphically depict variation. This control chart, could also distinguish the two types of variation from each other, thus allowing for the elimination of special causes and the reduction of common cause variation.
There are several types of variables data and attributes data control charts. This section will discuss the different types of control charts, the applications of each control chart, and the interpretation of the data.
Types of Control Charts
Variables data are quantitative data that can be measured. Some examples are the diameter of a bearing or the thickness of a newly minted coin. Variables data are usually represented as X-bar and R-charts and X-bar and s-charts.
Attributes data are qualitative data that can be counted. Some examples are a count of scratches per item or a count of acceptability for a go/no-go gauge. Attributes data are usually represented as nonconforming units and are analyzed by using p, np, c, or u control charts.
First, determine what variable you will measure. Then gather data and chart the data accordingly (Figure 2.2).
Figure 2.2
Sample Control Chart