Predictive Quality Control Charts Startup Panel - Quick Tab

Select the Quick tab of the Predictive Quality Control Startup Panel to access the options described here. For details regarding these chart types, refer to Quality Control Introductory Overview - Common Types of Charts.

The options available from this dialog allow you to construct standard quality control charts (for attributes, variables), and to apply various modeling tools to explore the patterns in the charts. Using the neural networks options, forward (in time) predictions can also be made (and plotted) for the chart points (e.g., X-bar, Ranges), to help engineers anticipate likely changes or trends predicted from the multitude of parameters (variables) monitored via charts.

Note: the analyses and computations for predictive modeling (via neural networks) will be performed on the "plot points," i.e., the sample means and ranges or standard deviations for the variables selected for the variable control charting.
SixGraph with X-bar & R chart
Double-click SixGraph with X-bar & R chart, or select SixGraph with X-bar & R chart and click the OK button to start this analysis. The analysis produces a list of SixGraph compound graphs for each selected variable; X-bar charts (for means) and an R (range) chart for the variability of the process can also be requested. Other types of charts for continuous variables are available on the Variables tab.
X-bar & R chart for variables
Double-click X-bar & R chart for variables, or select X-bar & R chart for variables and click the OK button to start this analysis. The analysis produces a list of X-bar charts (for means) and an R (range) chart for the variability of the process. Other types of charts for continuous variables are available on the Variables tab.
Individuals & moving range
Double-click Individuals & moving range to start this analysis, which produces Individuals and moving range charts for each variable selected for the analyses. In this plot, individual observations (sample size of 1) are plotted and you use so-called moving ranges (of adjacent observations) in order to estimate a process sigma and establish control limits. Other types of charts for continuous variables are available on the Variables tab.
C chart for attributes
Double-click C chart for attributes to start this analysis. The analysis produces C charts for attributes for all selected variables. In this chart, we plot the number of defectives, and it is constructed based on the Poisson distribution, which is also referred to as the distribution of rare events. Other types of attribute charts are available on the Attributes tab.
P chart for attributes
Double-click P chart for attributes to start this analysis. The analysis produces P charts for attributes for all selected variables. In this chart, 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). Other types of attribute charts are available on the Attributes tab.

See also, Quality Control Introductory Overview - Common Types of Charts, Control Charts for Variables vs. Charts for Attributes, and Quality Control Charts Index.