Statistical Process Control: X-bar and R-Chart Control Limits

This video demonstrates how to determine the upper and lower control limits for X-bar and R-Charts.

[@shubhamvernekar4023]

what if a standard deviation of a temperature setting is already given, e.g 25 deg with 2 %+- tolerance . so now on hourly basis i take certain reading and the mean of that calculates to 23 deg but as per the already given setting it say the average/middle line should be 25 what should i do in this case?

[@The_Business_Doctor]

Hi Shubham, If you're provided with that information, you can construct initial control chart limits based on that and when you take your samples and plot the means against those parameters you can see where your process might be out of control. Normally you take samples and determine the control chart limits. In this problem, you would have conducted 35 samples, to determine the mean and standard deviation, construct the control chart limits as demonstrated, then plot the means from the samples. Hope this helps. Mark

[@domenicoscarpino3715]

Hi, thanks a lot for the videos. I have a question. I have studied that design of experiments help to reduce variability. I'm trying to understand which variability though when I compare this concept to control charts. I wonder if some of the common cause variability (noise) that we see in the charts can be actually reduced by controlling some factors with design of experiments. In other words, is controllable factor variability part of the noise when it's not controlled?

[@The_Business_Doctor]

I would think so. Many controllable factors in a process might go uncontrolled.

[@domenicoscarpino3715]

@@The_Business_Doctor thank you