iSixSigma

PhD Dissertation

This topic contains 4 replies, has 5 voices, and was last updated by  Groll 9 years, 5 months ago.

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  • #53434

    Olga
    Participant

    Hi there,
    I am currently doing my post graduate dissertation. Right now, I am in the process to develop a proposal for my dissertation. My scientific adviser has a preference to see my dissertation research about using complex of tools- FMEA+Ontology in electro technology.
    I would be very interested and thankful to get in contact with people who would like to share their lessons learned about scope, theme, approach tip&tricks and whatever is value added for such a task.
    Thanks a lot in advance!
    Olga

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    #190115

    Strayer
    Participant

    The definitive source for FMEA is the AIAG (Automotive Industry Action Group), Look there first rather the many other sources you’ll find. I assume that your adviser’s reference to ontology is that an FMEA is properly used to identify how something might fail and how to reduce that possibility rather than to analyze how it actually failed. And, yes, an FMEA is properly done by a cross-functional team.

    First you need to identify a specific process or product. If you are doing a proces FMEA you need to decompose the process into specific steps, For a product FMEA, identify the components of the product. Then identify the various ways (failure modes) that each step or component might fail. Agree on a numerical value for the probability. Descirbe the effect of each failure and assign a numerical value. Describe the current controls that can detect/intercept the failure and assign a numercal value. The RPN (Risk Priority Number) is the product of these three values. Starting with the highest RPN, find ways to reduce the risk of failure then recompute the RPN. You will need to demonstrate that the changes actually reduced the risk.

    My primary tip is to use 1,3,5,7,9 for the numerical values. This makes it easier for the team to agree on a value and it helps to separate the RPN’s. Note that the order is reversed for detectability. 9 means highly probable, severe effect, but almost certain to be detected. 1 means highly unlikely, minimal effect, and unlikely to be detected.

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    #190140

    PhD
    Participant

    A subject such as FMEA seems rather “light” for a PhD. You might as well do a PhD on brainstorming.
    Why not something like a study of the degree of non-normality of industrial processes across a range of industries and the validity of Shewhart Charts ?

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    #190161

    Cone
    Participant

    Sorry but Wheeler has answered this question some time ago.

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    #190179

    Groll
    Participant

    Hi Olga,

    I posted a question a few weeks ago looking for a correlation between how mature a company is… and the waste that’s associated with that level of maturity.

    Maturity can be defined in many ways, one of the more popular ways is the CMM Index that essentially says: Level 1 is chaos, Level 2 some pockets of goodness, Level 3 each area is following a process but the process is not the same as the next area, Level 4 all areas are following the same process and Level 5 Contiuous Improvement.

    The reason it’s important is in order to invest in the maturing of a company (of which a Lean/Six Sigma program would be a large component of it), you need to provide data that allows the C Suite to decide how far do they want to go and how fast do they need to get there. Providing the data would be useful because they would feel they’ve decided to invest based on solid evidence.

    I’d be happy to talk further with you,

    Randy

    My email is Randy at My Insight Unlimited

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