Hi, control charts are to determine if the process is in statistical control (consistent and predictable). Stability should be done at first. After that will be checked the distribution. Lets consider that the actual process is not stable (minimum boundary in the process cannot be less than 0 - for instance delivery times etc..) Non-normal Data increase the chances for false signals. I have read that up to 4 times. If the process is out of control, the process needs to be improved and not bother with transformation, as they will be meaningless. When any process with natural non-normal distribution needs to be checked for stability at first (like others with normal distribution), such processes have a big disadvantage, because the probability that these will be unstable is up to 4 times bigger. How do you decide if OOC points are false signals or they are really there because the process is unstable? How do you handle with such cases?