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Control Charts in Minitab

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  • #54093

    chris reid
    Participant

    Hi I want to use a control chart to monitor performance during a project. The data I have prsented to me is for parcels delivered on time and is presented as a % each day e.g
    Mon 95%
    Tues 96%
    Wed 93%

    Can anyone tell me what control chart would be best to use bearing in mind my limited data.

    Many thanks.

    Chris.

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    #193554

    Joel Smith
    Participant

    Chris-

    Do you know the sample sizes that produced each percentage? If so, you can use Binomial Capability Analysis. Otherwise, when you say the data is non-normal, do you mean it does not follow the shape of the normal distribution or just that it is non-continuous data? Finally, is the data reported in whole percentages like you have illustrated or is that just an example?

    Joel

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    #193555

    Nik
    Guest

    I agree with Joel Smith. It depends on the source data. If the data is pass/fail, then use a binomial analysis. If it’s defects per unit, a Poisson analysis. And if the data is continuous data, then rule out special causes such as: look at the process for different levels of an X effecting it (humps in the data are a good sign), discrete data pretending it is continuous data, or evidence that the process is unstable (you can use graphical tools). If none of those are the case then try to identify the distribution using (on Minitab 15… don’t know where it is on 16) Stat>Quality Tools>Identify Individual Distribution. If it doesn’t fit any of those distributions, look at the process for different levels of an X effecting it (humps in the data are a good sign), discrete data pretending it is continuous data, or evidence that the process is unstable (you can use graphical tools).

    I also have a caution on your % data in your control chart. Find out what the root data is; how was that percentage calculated. There might be binomial or other continuous data behind the scenes that can give you a more effective control chart to use for identifying patterns and trends.

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    #193557

    chris reid
    Participant

    Hi thank you both very much.
    The problem is my proportion data is only available to me as described daily e.g

    Monday. 95% of parcels delivered.
    Tuesday 96% of parcels delivered.
    Wednesday 97% of parcels delivered.
    Etc.
    I don’t have the finer detail but it is auduted and Im told (I have to believe at this stage) it is reliable and independantly audited. Number of parcels each day is over 1000.

    The I chart look like it works, although I understand not strictly speaking the correct thing to do I cant think of a better option.

    Capability analysis wise I’m limited in what I can do in Minitab because I cant use sub groups so thought Id use a regular capability analysis, but this seems totally wrong to me (also this is why I say the data isn’t normal, capabilty analysis tells me this)

    Thanks again.

    Chris R.

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    #193576

    Joel Smith
    Participant

    Chris-

    Graph the data. If it is not highly skewed and the sample sizes are wildly variable (like 200 parts one day and 2000 the next) then just use the I-Chart. It is robust to many distributions of data and works well unless you have one of those criteria I just described.

    Capability Analysis is much more sensitive to distribution, but again graph the data or even better use a probability plot, and see if you have a good distribution fit. The Normal distribution approximates the binomial for good sample sizes, so if your data is in control you might be surprised how good that fit is. And if it is good, then go ahead and use Normal Capability Analysis.

    You’ll be in good shape if you can do those things with the data you have, and can then focus your efforts on solving problems instead of finding only slightly better statistical methods.

    Good luck!

    Joel

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    #193578

    chris reid
    Participant

    Joel, Thank you very much.

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