Changing LCL (Lower Control Limit) on a Minitab Control Chart

[George Davis]

Hello,

I am developng a control chart that tracks warranty returns. Obviously, the desired level is "0". I would like the control chart to reflect this. Is there any way to set the LCL to ) in Minitab?

Thanks in advance.

George

[Jim Wynne]

Originally Posted by George Davis

I am developng a control chart that tracks warranty returns. Obviously, the desired level is "0". I would like the control chart to reflect this. Is there any way to set the LCL to ) in Minitab?

Thanks in advance.

George

Welcome to the Cove.
That would be the lower specification limit, not control limit, and you should be able to set the spec limit wherever you want it. The control limits are calculated from the input data.

[Caster]

The poster may have a point, I think Minitab sometimes calculates and displays a negative LCL. Although mathematically correct, it makes no sense in the real world. I think IMR charts do this?

I'll have to check when I get in to work, oddly enough as much as I love SPC, I don't have a copy of MiniTab here at home!

So now I'll ask an expert, does anyone know how to set CL breaks in Mintab?

[Steve Prevette]

True, if you are getting a negative LCL when negative numbers are not possible, there is no reason to display the negative LCL, or perhaps overide it to zero. But - you would need to keep in mind where one standard deviation below average and two standard deviations below average are in case you are using them as part of detection rules.

I assume the original question asker had a LCL greater than zero, but wanted to show the LCL at zero since that was the desired specification. As properly pointed out, that would not be a good idea. One reason why not is - let us say this is a counting of bad things happening chart (injuries, defects, events, etc). The fact that the LCL is greater than zero means that we need to be realistic and say by the current process that we will most likely have a non-zero rate. That doesn't make it good or bad, but we need to acknowledge what the process is currently capable of.

And, by realizing the LCL is greater than zero, we know that if we do receive a time interval with zero items counted, then something special has indeed happened, and we may have a basis for celebration. Unless of course the method by which we got to zero was we said - "The next person to report a bad thing gets fired".

[George Davis]

Thanks to everone who replied. Yes, Minitab did produce a negative LCL, and zero is the lowest possible (we are measuring units returned for warranty credit).

This is receiving further discussion here. There is some concern that showing the process as being within control limits will cause some to believe the current level is acceptable (not true). We do not have an upper specification limit for returns. We are thinking of establishing a target, which would be less than the mean to explain the expectations.

G

[Allattar]

Just wondering if using a proportion chart would be a better application here?

I can also hazard a guess that the lower bound at zero makes the data non-normal. In that case to display correctly on an I-MR chart you may want to transform the data to a normal distribution.

It also sounds like it is just binomial data, and whilst a binomial distribution can be applied to an I-MR chart, it should probably only be used where the distribution approximates a normal one.

[Steve Prevette]

Originally Posted by Allattar

Just wondering if using a proportion chart would be a better application here?

I can also hazard a guess that the lower bound at zero makes the data non-normal. In that case to display correctly on an I-MR chart you may want to transform the data to a normal distribution.

It also sounds like it is just binomial data, and whilst a binomial distribution can be applied to an I-MR chart, it should probably only be used where the distribution approximates a normal one.

Control charting will work regardless of the distribution. Dr. Shewhart documented the Tchebychev Inequality (see other discussions on the Cove about that) and tested control charting with the normal distribution, and two non-normal distributions. I-MR (and my preference, I-sigma) can be used effectively even if the distribution is non-normal.

If what is being plotted is indeed binomial (I can't tell from what has been posted so far), I would recommend going to the p-chart control chart.

[Allattar]

I quite happily understand that Individuals charts work for non normal data. However the control limits are going to be in slightly odd places. At least for an individuals chart calculated this way.

This is then where you get a negative control limit.