It is very challenging to monitor production processes using a beta control chart known as BCC, so we use this chart (BRCC) which has a strong correlation with fractions and ratios to monitor more detailed and complex cases. Moreover, BRCC works better with continuous data and a sufficiently large sample size of n. It goes without saying that BRCC is consistent with a beta distribution with a different shape. Determining properties of n and np charts is the most common use of fractional and proportional data in control charts [13, 14]. We consider the control charts with distribution for the fraction of defectives between upper and lower limits follows that Def ~ b (n, p). The upper and lower bounds can be specified for this control chart using the equation below: CLD=x ̂±w√((x ̃(1-x ̃ ))/n) where: x ̃ is the mean inside the upper and lower limit w or k Z□(δ/(2 ))=3 is permissible error boundary area limit (or, the number of standard deviations from the mean process). If the sample size (n) is equal to or larger than 25, the binomial distribution will be reasonably symmetric at the mean point, in which case the control limits can be roughly calculated using the normal distribution [20, 16]. The upper and lower bounds of np can be found using the p-rule because the graph of np and the graph of p are actually the same. Therefore, it can be said that one is a more primitive version than the other.
