Control Chart using R Integration

[intapiuser]

Problem

You want to create a Control Chart in Sisense to study how a process changes over time. A control chart always has a central line for the average, an upper line for upper control limit and a lower control limit. By comparing current data to these lines, you can draw conclusions about whether the process variation is consistent (in control) or is unpredictable.

Solution

• Install “qicharts” package in R console.

install.packages(qicharts);

• R script (Copy paste to Sisense Formula)

Center Line:

library(qicharts);

y<-c(do.call('cbind',args));

sisense_result<-qic(y,chart='i');

sisense_result$cl

Upper Control Limit:

library(qicharts);

y<-c(do.call('cbind',args));

sisense_result<-qic(y,chart='i');

sisense_result$ucl

Lower Control Limit:

library(qicharts);

y<-c(do.call('cbind',args));

sisense_result<-qic(y,chart='i');

sisense_result$lcl

 

Discussion

Control charts, also known as Shewhart charts or process-behavior charts, in statistical process control, are tools used to determine if a manufacturing or business process is in a state of statistical control.

References

https://www.isixsigma.com/tools-templates/control-charts/a-guide-to-control-charts

https://en.wikipedia.org/wiki/Control_chart

https://cran.r-project.org/web/packages/qicharts/vignettes/controlcharts.html#types-of-control-chart...

http://blog.minitab.com/blog/understanding-statistics/control-charts-show-you-variation-that-matters