Predictive Quality Control Charts Startup Panel - Attributes Tab
Select the Attributes tab of the Predictive Quality Control Charts Startup Panel to access the options described here. For details regarding these chart types, refer to Quality Control Introductory Overview - Common Types of Charts.
Note: the analyses and computations for predictive modeling (via Neural Networks) will be performed on the "plot points," i.e., the sample proportions, rates, etc., for the variables selected for the attribute control charting.
- C chart for attributes
- Double-click C chart for attributes, or select C chart for attributes and click the OK button to start this analysis. The analysis produces C charts for attributes. In these charts, we plot the numbers of defectives and it is constructed based on the Poisson distribution, which is also referred to as the distribution of rare events.
- U chart for attributes
- Double-click U chart for attributes to start this analysis. The analysis produces U charts for attributes. In these charts, we plot the rates of defectives, that is, the numbers of defectives divided by the number of units inspected. Like the C chart, this type of chart is based on the Poisson distribution, but unlike the C chart, this chart does not require a constant number of units, and it can be used, for example, when the batches (samples) are of different sizes.
- Np chart for attributes
- Double-click Np chart for attributes to start this analysis. The analysis produces Np charts for attributes. In these charts, we plot the number of defectives (per batch, per day, per machine) as in the C chart, but it is based on the binomial distribution.
- P chart for attributes
- Double-click P chart for attributes to start this analysis. The analysis produces P charts for attributes. In these charts, we plot the percent of defectives (per batch, per day, per machine, etc.) as in the U chart. However, the control limits in this chart are based on the binomial distribution (of proportions).
See also, Quality Control Introductory Overview - Common Types of Charts, Control Charts for Variables vs. Charts for Attributes, and Quality Control Charts Index.
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