A simple graphic representation of process data over time. Use a run chart to look for evidence of special causes variation in your process. Special causes arise from outside the system and cause recognizable patterns, shifts, or trends in the data. A process is in control when special causes of variation has been eliminated.
A run chart plots the individual observations in the order that they were collected, and draws a horizontal reference line at the median. When the subgroup size is greater than one, the subgroup means or medians are plotted and connected with a line. Run charts also perform two tests for randomness that provide information on non-random variation due to trends, oscillation, mixtures, and clustering in your data. Such patterns suggest that the variation observed is due to special causes.
For example, a plastic manufacturer wants to assess its production process for one of its new products. They sample 5 products every hour for 20 hours and test the strength of the plastic. The following run chart resulted.
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The gray points represent the individual values. The blue points connected with a line represent the means of subgroups. With the exception of one observation, the points appear to vary randomly around the center line (median). The approximate P-values for clustering , mixtures, trends, and oscillation are all greater than the a level of 0.05. Therefore, there is no indication of special causes variation or non-randomness.
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