How to measure Quality across multi-sites

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    Good day all,
    We are an aerospace company with manufacturing sites spread around the world.  I was asked to come up with a standardized way to measure Quality from those sites.  Since some of them does not have the same end product (some is the fully assembled aircraft, some is the fuselage, same are the cockpits…), how can I measure in an harmonized way the Quality of each site.
    I have thought off (# of non-conformity / 1000 hours of production).  I was challenged that if productivity is improving (less hour of prod), with the same level of non-conformity, the Quality ratio would prove that Quality is getting worse, which is not the case. On the other hand, if productivity is getting worse, Quality result will look better, assuming reject remains the same. 
    Is there a suggestion out there to measure Quality in a more robust way?



    Somewhere, some place there is an organization that assembles the sub-assemblies listed. That would be “the customer.”
    Go ask that customer how they define quality. Then ask the sub-assemblers what measures they would USE to provide evidence that they are meeting/exceeding the customer’s definition of quality. From there, use operational definitions, CTX, tree diagram, a C&E Matrix, or QFD.
    If “the customer” is you, then assemble a team of “internal stakeholders” and ask them to define dimensions of quality for both the products and services the sub-assemblies provide and use these to develop an overall definition of “value.” (NOTE: See Garvin for a starter list of nine dimensions of product quality and Zeithaml et al. for a starter list of five elements of service quality.)
    You may want to ask “The REAL Customers” — the ones that buy the fully assembled aircraft — how they define quality to avoid the potential that you have sub-optimized your assembly system.
    Then maybe you would want to help your assembly operations flow down “The Customer” definition of value to the production facilities that provide the parts they assemble.



    Hello Daniel,
    Assuming your specs are measures of customer expectation – a good measure of quality would be an over-all process capability index measure.  Or you could use a sigma performance measure – DPMO. 
    you can compare the occurances and variation of quality by comparing NP, P, C, and U charts between business units.  As mentioned by the other blogger, you can also include a customer satisfaction index or a frequency of warranty returns index.  There are a variety of things that are CTQ you can measure.  Just let it rip.
    Hope this helps get you started…



    I believe in your situation the right approach is to use balanced scorecards (BSC), so you can take care of many aspects of Quality KPIs and weighting them to understand the balance of improvements. Building right BSC, you can look at same time to all KPIs and summarize them in one higher indicator.
    Rgs, Peppe 



    I fully agree with Pepe. I come from the Automotive industry and we are also using BSC (Balanced Score Cards) to make a comparison between our different production plants all-over the world. We even have conversion factors defined that enable us to score seat assembly plants and trim cover assembly plants, or metal plants, or battery plants with one another although the processes and end-products themselves are rather different. So I thinks this is the way to go. Define your KPIs that are making your final quality, define how they should be scored so that everyone scores them the same (otherewise your MSA would fail). Before you start using the scoring system, do a Gage Study to proove you can use the system. If everything is acceptable, fire away !
    The conversion factors as we use them did come out only two years after we started using the BSC because that was the moment when there was enough numbers to start calculating these factors…


    Heebeegeebee BB

    Define, Measure and analyze your KPC’s/KQC’s/KPIV’s and compare DPMO’s/Sigma level.
    Remember, Sigma level is “the great equalizer”, allowing you to compare differing populations/processes.

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