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Statistical Process Control | Chart for Means (x-bar chart)
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- čas přidán 20. 07. 2015
- This video shows how to construct x-bar chart from process data and determine if the process is in control.
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Joshua Emmanuel hey can you please do a video on cusum control chart on R studio.
Where and how to find value A2?
Tq sirr ❤
A set of data has a mean of .634 unit and a standard deviation of .005 unit. Construct an X Bar chart if the number of samples is 5
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why did we use A2 and not A3? how to determine?
very helpful. thanks
thank you
Hello. It takes some time, sampling and processing to get to those UCL, LCL and mean value. So when you come to this situation like data point 5 is out of control then normally one cannot go on just like that but must consider what to do with this outlier and what to do with the limits...
When (condition) and how (procedure of recalculation) to reset the new upper&lower control limits. Is there a video or clear procedure for available ?
The existence of an outlier signals an out-of-control system. Given that history cannot be rewritten, the outlier cannot be erased, and subsequent recalculations are not possible. Rather, the outlier serves as a clear indication that the system was not operating correctly. It prompts the need to pinpoint the responsible factors and proactively address the root cause for a more reliable and stable system.
Great job!!!
clear one
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You should take value of A2 from N=10 not from N=5
Thank you so much sir...
Sorry pls I'm not still clear with how you get the Control constant
Best vid, thanks!
Maybe can someone with a stats background answer this on here? If Joshua Emmanuel could himself that would be amazing. I've heard it said that setting up a control chart is essentially like doing a continuous test of hypothesis. In our case here, we are testing if the process is in control.
H0: The process is in control (perhaps an equivalent test(s) could be that the LCL or UCL is equal to the value that you have shown
H_alternative: The process is not in control.
This is essentially a two tailed test because the out of control point could be either beyond the UCL or the LCL.
My question is this... Assuming point P1 plots out of control. If we find an assignable cause to this point, is this not proof that our trial limits actually are good and the process was in control prior to this point?
If our limits are truly bad, it would seem to me that we would not be able to find an assignable cause for our "out of control" point. If we don't find this cause, that is probably because our "out of control" point really is in control for whatever larger bounds we are supposed to have.
I'm very confused.
Ho is a starting assumption that the process is in control.
If you find an assignable cause to P1, then the process is truly out of control (rejecting a false null hypothesis).
If you can’t find an assignable cause to the out of control P1, then you could be committing a Type I error if your limits are fine. It could be an error in measurement.
If your limits are truly bad (too wide margin), you may not be able to identify the out-of-control points (Type II error). If the margin is wrongly too small, you may incorrectly declare some of the in-control points as out-of-control.
thank you so much!!
Thanks
if the points you plotted were the same in the video, but the one out of control we within the UCL and LCL, would that mean it is in or out of control even if the majority of points is skewed upwards
Thank you!!!
why did we took the value under 5 for A2?
Samples of size 5 were collected daily. See 1:10
Best
Thankyou So muchh :D
If I am taking the daily 5 samples reading means, my LSL and USL will fluctuate. Then how to plot the values in daily basis(if am plotting daily avg values manually)
You are to construct an x-bar chart such that the control limits would include 97% of the sample means, where the random samples would be of size 5; this it say that type I error would occur with 3% probability. The process standard deviation is known to be 3.2. The following data is used to construct the control chart.
You are to calculate the UCL only. Round your answer to TWO places of decimal.
Sample # obs 1 obs 2 obs 3 obs 4 obs 5
1 17 16 17 10 17
2 16 17 15 10 20
3 13 20 11 12 20
4 18 18 12 20 18
5 17 15 15 10 15
can you please solve this?