Control charts take data about your process and plot it so you can distinguish between common-cause and special-cause variation. Knowing the difference is important because it permits you to address potential problems without over-controlling your process.
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Control charts are fantastic for assessing the stability of a process. Is the process mean unstable, too low, or too high? Is observed variability a natural part of the process, or could it be caused by specific sources? By answering these questions, control charts let you dedicate your actions to where you can make the most impact.
Assessing whether your process is stable is valuable in itself, but it is also a necessary first step in capability analysis. Your process has to be stable before you can measure its capability. You can predict the performance of a stable process and therefore improve its capability. If your process is unstable, by definition it is unpredictable.
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XmR/ImR Chart Will Handle Most Service Industry Data
Wheeler and Pyzdek have both offered articles about how the XmR is the Swiss Army Knife of control charts. Master the XmR and you are well on your way to mastering ccontrol charts.
You don't have to know the decision tree for choosing the right control chart. QI Macros Control Chart Wizardl will automatically chose the right control chart based on your data.
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