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Testing a theory about your data

If your theory is concerned with different results coming from different shifts, operators, or equipment, try separating the data. For example, you might suspect that one machine is the source of more scrap than another machine. If you are considering process improvements, one way to test a theory is to make a change in the process and track the effects. To do this, isolate data.

  1. If you are collecting data from multiple lines or shifts, you might make a change on one shift or line, and stratify data for analysis. If you are using SQCpack, the filter function can help create a subset of data from the process you have changed.

  2. Create a control chart , histogram , or run chart , or perform capability analysis with data collected after the change. Compare charts or capability indices created before and after the change.

  3. Create a control chart showing data collected before and after the change. You can create a separate set of control limits for each group of data. Has the process improved? Stayed the same? Worsened?

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