How to Collect Data for Control Charts for Six Sigma - dummies

How to Collect Data for Control Charts for Six Sigma

By Craig Gygi, Bruce Williams, Neil DeCarlo, Stephen R. Covey

You must collect data for control charts for Six Sigma projects in a way that avoids a distorted or inaccurate view of the process performance — whether overly optimistic or too bleak. Using rational subgroups is a common way to assure that this distortion doesn’t happen.

A rational subgroup is a small set of measurements in which all the items in the subgroup are produced under as similar conditions as possible, typically within a relatively short time period — short enough that special causes are unlikely to occur within the subgroup. In this way, rational subgroups enable you to accurately distinguish special cause variation from common cause variation.

Make sure that your subgroup measurements are randomly selected and don’t unfairly favor any specific operating condition. For example, don’t take subgroups from only the first shift’s production if you’re analyzing performance across multiple shifts. Or don’t look at only one vendor’s material if you want to know how the overall process, across all vendors, is really running.

Finally, don’t concentrate on a single time of the day, such as just before the lunch break, to collect your subgroup measurements.

Rational subgroups are usually small, typically consisting of three to five measurements. Make sure that rational subgroups consist of measurements that were produced as closely as possible to each other, especially if you want to detect patterns, shifts, and drifts. If a machine drills 30 holes a minute and you want to create a control chart of hole size, a good rational subgroup may consist of four consecutively drilled holes.

If your process consists of multiple machines, operators, or other process activities that produce streams of the same process characteristic you want to control, use separate control charts for each of the process streams.