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control limits

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  • #48884

    dimi
    Participant

    I have encountered this Problem: A process with very narrow control limits and many points out of limits but when measuring the characteristics of product tolerances seem to be Ok. There is no issue with mistakes at mesuring procedure neither at control limits calculation. How can this be explained; 

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    #165934

    Six Sigma guy
    Member

    process out of control but with a very widen spec limits thats why though ur process is meeting customer expectations but not under control… check if there is any process change? check if the baselines needs to be revisted…probably u could also be clubbing two different processes in same control chart.

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    #165935

    Harish Goyal
    Participant

    i dont think its concerned with specification limits. Yhere may be some calc mistake there in process.
    why dont you put the data here so that someone can see and give suggestion.
    Regards
    Harish

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    #165936

    chhabra
    Participant

    data from two process can be represneted by bimodla distribution having 2 or more peaks in histogram .
     
    FYI
     
    Regards
    Amit

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    #165937

    Dhananjay Hegde
    Participant

    Hi.
    The process is able to meet the tolerance limits indicates that it is a capable process.But capability and stability are 2 different things.Stability talks about indication of special cause variation and in your case the problem is about stability.It would be great if you can share the raw data.
    Dhananjay

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    #166016

    Erik L
    Participant

    dimi,
     
    Overly narrow control limits, with a large # of OOC data points, is a potential indication of poor subgroup selection and/or autocorrelation in the data.  Another potential contributing factor could be the number of data points being used to create the points that are ultimately plotted this would magnify the impact of poorly selected rational subgroups.
     
    Are you using Xbar-R or Xbar-S?  Have you assessed the process data to understand where the independent variance component lies?  Tools that can help provide this insight include:  Multi-vari studies, COV/REML, and GLM analysis.
     
    Regards,Erik

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    #166017

    Ron
    Member

    Control limits are statistically inferred parameters commonly referred to as the “Voice of the Process” the situation you described is quite normal for a process where the drawing specifications are much looser than the capability of the process.
     
    Remember that control have no relationship to specification limits.
    Also be sure you are usingthe correct type of control chart.

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    #166021

    Dr. Scott
    Participant

    dimi,
    I suspect you are using binomial data with very large sample sizes.
    I suggest you follow the advice of Dhananjay at post your data here so we might help.
    Happy Holidays,
    Dr. Scott

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    #166188

    k.bhadrayya
    Participant

    Dear Dimi
    Since many of the points  on the control chart are out of specs, it shows that some assignable/ external  causes are influencing the process  . By reading your out put data and corelating with the changes of inputs taken from the log sheet of production must show some trends. Keenly observe the changes in the input data and relate to out put data. Unless the factors affecting this distrubance are detected and teken remidial action , control charts will not help.
    k.bhadrayya
     
     
     

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    #166205

    lemiii
    Participant

    Without specific data, I say you are suffering from one or two classical situations, overcontrol and / or measuring nearly identical parts.
    Overcontrol:  one reading, one adjustment (lots of points are out of control, 50% above the control limit and 50% below).  Operators are trying too hard to control the process based on one reading.  Try this, never make a process adjustment based on inidividual readings.  Only, adjust if the subgroup average is out of control.  If you are in an overcontrol situation, statistically, you do not know what your process looks like.  You need to instruct your folks to not make any adjustments for 2 days.  Let the process define itself. 
    Measuring nearly identical parts.  Once set up, in the short run, the process will produce nearly identical parts, R is nearly zero, hence the control limits will be very narrow.  If this happens, you will throw your process into an overcontrol condition.  If your process is producing nearly identical parts, then you do not need to monitor your process.  You need to monitor your set up, nominal is best.  
      

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    #166212

    jberilla
    Participant

    You can also consider gage resolution.  When you have a limited number of observational values (usually considered <6) displayed in your R or S chart, your subgroup averages will will uncharacteristically small, resulting in tight CL on your mean chart.
    Look to the R/S chart and determine if you have 6 or more different values represented.  If not, consider:

    Changing the gage (if not too expensive) if possible, if not
    Using larger sample sizes, if possible, if not
    Gather the R or S chart subgroup averages over a longer time frame

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