ARTICLES (WHITE PAPER)

Attribute, pass/fail proportion data, can be monitored over time for stability and then, when a process is stable, provide a prediction statement. When a process has a recent region of stability, it can also be said to be predictable. When this occurs, we can use historical data to make a statement about what we might expect in the future, assuming things stay the same; e.g., the center line of the chart if no transformations are needed to create the 30,000-foot-level chart, and the subgroup sizes are approximately the same.

Time-series data that have multiple subgroup samples can be monitored over time for stability and then, when a process is stable, provide a prediction statement.

With a high-level process-output tracking at the 30,000-foot-level, there will be an infrequent subgrouping/sampling plan such that the typical variability from input variables that could affect the response will occur between these subgroupings. An infrequent subgrouping/sampling interval could be day, week, or month, where responses from differing people, departments, machines, and so forth would be captured within each subgroup. 30,000-foot-level charting does not offer timely identification of process changes but instead provides a high-level view of how the process is performing from a customer-of-the-process point of view.