# Control Limits on XR-Chart

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This topic contains 1 reply, has 2 voices, and was last updated by Robert Butler 8 months, 3 weeks ago.

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- February 23, 2019 at 8:03 am #236629
Hello

I’m having some issues when applying SPC in some of my processes with high tolerances.

I know that control limits and specification limits represent different things however when using standard XR-CHARTS sometimes i end up with situations like this:

The control limits are defined within a tolerance of 0,2 on the XRCHART and i have a specification tolerance of 2

I understand the fact that control limits tell me the behavior of the process but for me those control limits don’t make sense.

I do not need to have control limits so narrow as the process is expected to have a high variation that was acknowledge by customer when choosing the specification tolerance.

It does not make financial sense to investigate such small variations in processes like this.

I want my XRCHARTS to be able to really identify tendencies and points out of control in my processes, i have tried to define a historical standard deviation with a higher value in order to have a bigger tolerance for the control limits but it seems like I am cheating the values.

Does it make sense to define smaller specification limits as control limits in this cases since process under control limits is a requirement by the customer?0February 23, 2019 at 11:29 am #236630

Robert ButlerParticipant@rbutler**Include @rbutler in your post and this person will**

be notified via email.If your process is expected to exhibit large variation then you should ask yourself why it is that you are seeing variation that is much lower than you thought it would be. Some things you might want to check:

1. Where did you get the idea that the process variation is large? Does someone actually have prior data that exhibits large variation or is this just someone’s impression based on who knows what? Also, if prior data does exist – how do you know it is representative of the process?

2. For the XbarR chart – are the samples actually independent? If you are taking repeated samples from the same lot of production material then there is a very good chance that the samples are repeated measures and not independent. Estimates of variation based on repeated measures will be much less than estimates based on independent samples.

If your process really is as tight as your initial calculations would indicate then you are in the very fortunate situation of being able to meet customer requirements 100% of the time.

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