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MSA and picking errors

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  • #33447

    Fontanilla
    Participant

    I am a new Black Belt candidate in the measure phase of a six sigma project.  I am trying to develop an MSA for picking errors in a distribution business.  Picking errors ocurr when the component is not where it is suppose to be, mislabeled, wrong quantity …  23 pickers are picking parts.
    Any ideas?
     

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    #90537

    Mai Chi
    Participant

    It sounds like you would need to conduct an Attribute Gage R & R. You would need to select 3 operators and get them to measure how many defects (What is a defect would need to be spelt out in the Operational Definition) per component for a certain number of components (whatever is practical) 3 times each. This would test for repeatability and reproducibility.   You would then need to match their answers against the “true” answer. This would test for Accuracy.
    I hope this helps.

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    #90550

    Ron
    Member

    Sounds like you have a good candidate for a Discrete Gage R&R. If you have minitab it should be easy.
    The personnel either pick corrctly or they do not. Just mix up two or three of the same ordersin a blind test can keep track of the results.
     

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    #90557

    drew
    Participant

    Dan,
    Sounds like a real good BB certification project.  Your MBB and/or coach/mentor should advise you on this.  A straightforweard attribute MSA using discrete data should do it.
    Good luck

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    #90563

    vishwakarma
    Member

    Dan:
    If you are trying to reduce in-process variation (% disagreement) within this group of 23, I’d recommend you use an “Expert Gage R&R”, a slightly different form of “Attribute Gage R&R” suggested above.
    Since you’re dealing with attribute (discrete) data, bear in mind that a true Gage R&R is not possible (as that needs data to be variable or continuous). What you can do, is measure “percentage agreement” amongst the group of 23 operators, either amongst themselves (as suggested by first response on this string), or, with respect to an “expert” (the “should be”), which would be “expert gage R&R”.
    You might want to include two separate measures in your MSA – first, the operator selects whether there is a defect or not (i.e. sample pick list item is a “defective”), and second, what type of defect it is (amongst the list of possible defects you mention).
    Attribute MSA’s give you Alpha and Beta errors – the percentage chances that the operator incorrectly accepts a rejectable part, as well as the percentage chances the operator rejects an acceptable part.
    So while you won’t get true Gage R&R measures (%Tolerance etc.), you will get a first pass rolled throughput yield (RTY), using which you can compute sigma capability of your measurement system.
    An expert gage R&R would allow you the option (which you might NEED, based on your findings!) to benchmark the operator-to-operator variation as part of your study.
    Tabulating both – Defect/No Defect, AND What type of defect – will help you analyze MSA results using a P-chart and U-chart, on whether the MSA is STABLE or not.
    If the MSA results show, for instance, that the LOWEST operator-to-expert agreement is, say, 95%, then your measurement system is 3 sigma capable with a 1.5 sigma shift.
    Hope this helps…..

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    #90568

    Fontanilla
    Participant

    Thanks to all who replied to my MSA and picking error dilemma.  Here is what we have done so far.  We created a list of 20 potential picking error situations (the situations were identified by interviews with the pickers and management).  Then we created a standard, identifying each situation as yes this is a problem or no this is not a problem.  We asked the 23 pickers to do the same.  Then we compared their answers to the standard.  The best response was 85% agreement with the standard. I think this is similar to the Expert Gage R&R described by Sandeep

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    #90577

    AJ
    Participant

    There is an excellent article/case study regarding Attribute Gage R&R in ASQ’s Six Sigma Forum Magazine, Volume 2, Issue 4, August 2003.I just checked, and the full version is still available on line for ASQ members.Highly recommended reading…it has already prompted two projects at our company (automotive component manufacturing). 

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