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Control Charts; Confused

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  • #51527

    Kevin DuCasse
    Participant

    I have the responsibility of setting up a metric for final electrical test and I was trying to use an attribute chart to track the defects per unit.  The parts that we are testing can fail for one or more tests througout the  test process and we would like to capture each event.
    Which would be best to use, the C, U, P, or Np?  Would DPMO be a better choice?
     

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    #178814

    Ken Feldman
    Participant

    U chart is chart of choice if the number of parts being tested varies from time period to time period. Otherwise a C chart is fine.

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    #178815

    Gary Cone
    Participant

    For anyone to give you a definitive answer to this, we would need to know a lot more about your process and product.
    A couple of things to think about –
    1) Are you high volume, low mix or the opposite?
    2) Is your defect distribution predictible? For example, if you have a DPU of 1, you should expect 37% of your units to have no defects, 37% to have one defect, 18% to have two defects, and so on.
    If 1 and 2 are true, go with an np chart. Better yet use Lean concepts to limit space in the repair area where if your limited space is ever full, shut down the line because you are having an unexpected number of defects.

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    #178818

    Ken Feldman
    Participant

    Hey, stop making it complicated. You are starting to sound like that idiot Stan. A C or U chart is fine.

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    #178819

    Gary Cone
    Participant

    what would you be trying to detect with a u or c chart?

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    #178820

    Ken Feldman
    Participant

    According to the poster: “track the defects per unit”That’s sort of the definition of the C or U chart. Of course this assumes that the defect occurrence is not frequent and that he is seeking to monitor change over time. Also assumes that he is testing some number of units per time period and wishes to see if the process is getting better or worse or staying the same.

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    #178822

    Kevin DuCasse
    Participant

    The process is low volume, low mix.  We have four different products that we produce from the same type of process. 
    The defect distribution is not predictable.  I was leaning heavily on the use of the c chart, but I believe it is to be used if the defects are rare.  So I turned my attention to the u chart. 
     
     

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    #178824

    Gary Cone
    Participant

    You need to ask why you want a control chart. Conrol charts don’t track data, data collection systems do that.
    If you know your defect distribution is not predictable, whay aren’t you working on that instead? When defect distribution is not predictable, solutions are usually pretty easy and straight forward.

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    #178825

    Kevin DuCasse
    Participant

    Thank you for your input.  I had concluded the same.  I do not need a control chart at all.  Please explain your last statement that “when defect distribution is not predictable, solutions are usually pretty easy and straight forward.”
     
     

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    #178826

    Gary Cone
    Participant

    As explained in ever SPC book in existance, c and u charts have extremely limited usefulness. In electronics, the number of defects found in any given unit is going to very small as compared to say, defects per 100′ of a seemless tube, or defects per 1000 sq ft of float glass (good applications of c and u).
    Why would you need a chart when you can tell the folks that the odds of having x or more defects in any given unit is very small and when you have one, set it aside for detailed analysis. You don’t need a chart, you need a simple rule.
    The other side of this is he already knows his defect distribution is unpredictable, and any reasonable data collection system will have enough information in it to go solve that problem. In electronics, this unpredictability is often caused by the repair techs skill or a flawed fault tree or a MSA problem.
    c ad u assumes that the defects follow a poisson distribution, he already knows that is not true, so he should make it true before worring about a chart.

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    #178827

    Gary Cone
    Participant

    Go get data on DPU and let me know what it is for any or all of the 4 products and I’ll walk you through it,
    This should have been in your Six Sigma training. I am sure it is in Darth’s.

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    #178832

    Fontanilla
    Participant

    DPMO is rubbish.  Forget it.

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    #178833

    GB
    Participant

    hahahaha, you make funny!

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    #178858

    Trudy
    Member

    I’m surprised no one has suggested that you simply gather the failure information over a defined period of time and prepare a pareto analysis of the data.  Using a pareto chart has worked best for me when several different failure modes are present in one system test.

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    #178860

    Ron
    Member

    Making some big assumptions here Gary.

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    #178861

    Ron
    Member

    Trudy,
    While a pareto chart can point you in a direction there is no statistical value behind the chart.
    Many false trails can be obtained by using an incorrect chart.
    Very obvious trends can be observed and in some cases that may be enough but usually you want to know more than what a pareto chart will offer.

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    #178862

    Gary Cone
    Participant

    This is kind of like telling someone to make a pareto. No big
    assumption.

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    #178864

    Trudy
    Member

    Ron,
    I agree.  Pareto analysis may help take the confusion out of what type of chart to use by allowing the focus to be on a single failure mode.  I’ve never applied a control chart for systems using multiple failure modes. 
    Trudy

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    #178866

    Vallee
    Participant

    Kevin,I would like to take a step back and ask do you know what is causing the defects in the first place? The defects you are tracking appear to be lagging indicators and I wonder if you are tracking the leading indicators as well? Are you wanting to graph the defects at this point to establish a baseline and/or to see if it is getting worse or better? or to see where to go find out what is causing the defects? I know this sounds basic but if you look at the discussions above the argument started because people have different opinions for chart uses based on what you are going to do with the information. Develop your metrics on what your process is doing and on what you intend to do with the numbers you collect. Then have the above discussion.

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