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We use run chart to see if there is any sign of special cause variation in our process data. It is graphical representation of the process performance plotted over time (hourly for Continuous Flow processing and most commonly in days or in months) Most importantly, What is Run? It is 1+ consecutive data points on the same side of Median (Either above median or below median) Variations can be common cause or special cause. Point to note: Common cause variation is outcome in an Stable process that is predictable & Special cause variations is outcome in an Unstable process that is not predictable By using run chart, we will be able to find the trend and pattern in the process data set Common patterns of non-randomness include: Mixture Patterns Cluster Patterns Oscillating Patterns & Trend Patterns When we run control chart on Minitab, it detects whether above mentioned patterns are existing in the data Sample data – Considered gold price/10 grams for the last 55 months Classification: Public In the above chart we can witness, clustering and trends. Cluster Pattern: In general, it is set of points in one area of the chart, above or below the median line. Thumb rule for cluster, 6+ continuous nearby points above/below the median line We can also check out the P value to see if there is potential cluster in the data Specifically, when P value is < 0.05, we could say possibly the data could indicate cluster. In reference to the above Run chart, Approximate p-value for clustering is 0.000 which is less than 0.05, so reject null hypothesis. Cluster can show sign of potential sampling or measurement issues. Trend Pattern: It is sustained drift in the data set; either upward trend or downward trend; Thumb rule to conclude trend is 6+ consecutive points either higher than previous data in one continuous period or the other way, that is 6+ consecutive points lower than previous data points. In the referred above chart we could observe an upward trend and P-value is also less than 0.05 to conclude potential trend. Now as we know about Cluster and Trend, lets note the below points: Opposite of Cluster is Mixture & Opposite of Trend is Oscillation Oscillation: When the process is not stable, we get data points spread above and below the median line, looks like oscillation. Thumb Rule: 14+ points in one continuous period increasing and then decreasing cyclically For P value < 0.05, possible oscillation can be observed. Classification: Public Mixture: When there are no points near the center line, with 14+ points upward and downward, increasing and decreasing over the median line and P value <0.05, we can have potential mixture in the data set. Run Chart & Control Chart In Control chart, along with the center line we have the upper and lower control limits. Another major difference is in Control chart - Center line is median and in Run chart - Center line is Mean; Run chart does not give any detail on the statistical control limits. We can see control chart as an Enhancement to Run Chart. In control chart, we will be able to check the stability - whether the process mean and variation are stable; check whether any out of control. We can check normality - data is normal or non normal; But it does not provide view on patterns. When we use control chart from assistant view in Minitab we get below output view: Stability Report Classification: Public It gives commonly used patterns for reference, however does not highlight the pattern in the output. Control charts will be useful over an Run chart, when the focus in on the variation and to identify potential deviation. However, downside of control charts is that it could have below limitations and can cause unnecessary wastage of time. False Alarms Incorrect Assumptions Incorrect Control Limits Both - Run chart and Control charts has its own advantages and used for different purpose [Run - Trend & Patterns; Control - Stability] and are useful based on the required objective, situation and analysis.