Making sense of data, understanding variation, and improving processes is not a spectator sport. It is method and technique that is best learned by doing. It is for this reason that the workbooks and quick guides found here were created and are offered free of charge. These materials will help you build the knowledge and skills that are a necessary part of reducing costs and improving quality possible. Without them, you are just guessing.
Companies that make analytical software are not in the business of teaching you how to make sense of data by understanding variation. They are in the business of selling you software. Have software build process behavior charts for you if you like, but only do so after verifying that the software-calculated process limits are correct using the instructions in this guide.
If you do not want to use the dataset provided here, a dataset with known process limits can be used. This alternate dataset should have at least one value that falls outside the process limits on the X chart and one value that is greater than the URL on the mR chart.
To characterize a process is to determine if future process behavior can be predicted within limits using a process behavior chart.
This flowchart outlines the logic of characterization. It serves as a reminder that when all of the values on a process behavior chart fall inside the process limits, the underlying causal system is characterized as predictable. Here, only common causes of routine variation influence process behavior and future process behavior CAN be predicted within the process limits.
Conversely, when one or more values fall outside the process limits, the underlying causal system is characterized as unpredictable. Here, both common causes of routine variation and assignable causes of exceptional variation influence process behavior and future process behavior CANNOT be predicted within the process limits.
The XmR Chart Workbook & Quick Guide teaches readers how to build the most useful type of process behavior chart—the XmR chart. By following a six-step process, you’ll learn how to organize a spreadsheet and calculate process statistics in a way that makes constructing an XmR chart an easy and intuitive process.
Gather the data
Calculate the moving ranges
Calculate the average moving range
Calculate the mean
Calculate the process limits
Put it all together (construct the chart)
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