In Control Chart Builder, you can create attribute charts, which are applicable for count data. Attribute charts are based on binomial and Poisson models. Because the counts are measured per subgroup, it is important when comparing multiple charts to determine whether you have a similar number of items in the subgroups between the charts. Attribute charts, like variables charts, are classified according to the subgroup sample statistic plotted on the chart.
|
Distribution Used to Calculate Sigma |
Statistic Type: Proportion |
Statistic Type: Count |
|---|---|---|
|
Binomial |
P chart, Laney P′ chart |
NP chart |
|
Poisson |
U chart, Laney U′ chart |
C chart |
Control Chart Builder makes some decisions for you based on the variable selected. Once the basic chart is created, you can use the menus and other options to change the type, the statistic, and the format of the chart.
• P charts display the proportion of nonconforming (defective) items in subgroup samples, which can vary in size. Because each subgroup for a P chart consists of Ni items, and an item is judged as either conforming or nonconforming, the maximum number of nonconforming items in a subgroup is Ni.
• Laney P′ charts display the same information as a standard P chart, but the control limits are calculated using a moving range adjusted sigma. In a standard P chart, the control limits are computed using the binomial distribution. However, this distribution often underestimates the variance in the actual data and causes false alarms to be reported in the chart. Laney P′ charts address these issues. The Laney P′ chart is particularly useful when the subgroup size is very large.
• NP charts display the number of nonconforming (defective) items in subgroup samples. Because each subgroup for an NP chart consists of Ni items, and an item is judged as either conforming or nonconforming, the maximum number of nonconforming items in subgroup i is Ni.
• C charts display the number of nonconformities (defects) in a subgroup sample that usually, but does not necessarily, consists of one inspection unit.
• U charts display the number of nonconformities (defects) per unit in subgroup samples that can have a varying number of inspection units.
• Laney U′ charts display the same information as a standard U chart, but the control limits are calculated using a moving range adjusted sigma. In a standard U chart, the control limits are computed using the Poisson distribution. However, this distribution often underestimates the variance in the actual data and causes false alarms to be reported in the chart. Laney U′ charts address these issues. The Laney U′ chart is particularly useful when the subgroup size is very large.
Note: Generally there is no harm in using a Laney chart over standard P and U charts. If there is no overdispersion, the moving range sigma adjustment is close to 1, resulting in a chart that is equivalent to a standard chart. However, if there is overdispersion then the Laney charts are better for process control. Overdispersion occurs when there is greater variability in the data than is assumed by the distribution.