Reliability design based on dynamic factorial experimental model
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Cited by 2 publications
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Research has shown that nearly 80% of the costs and problems associated with product design are created during product development, and cost and quality are essentially designed into products during the conceptual design stage. Failure identification procedures (such as failure modes and effects analysis (FMEA), failure modes, effects and criticality analysis (FMECA) and fault tree analysis (FTA)) and design of experiments are currently being used for both quality control and for the detection of potential failure modes during the design stage or postproduct launch. Although all of these methods have their own advantages, they do not provide the designer with an indication of the predominant failures that should receive considerable attention while the product is being designed. The work presented here proposes a statistical clustering procedure to identify potential failures in the conceptual design stage. A functional approach, which hypothesizes that similarities exist between different failure modes based on the functionality of the product/component, is employed to identify failure modes. The various steps of the methodology are illustrated using a hypothetical design example. Copyright c 2004 John Wiley & Sons, Ltd.KEY WORDS: clustering algorithm; conceptual design; failure-free design; failure mode; failure modes and effects analysis; function based design; product design; statistical based design BACKGROUND I dentification of potential failure modes during the product design process is critical for creating failure-free designs. Industry currently uses procedures such as failure modes and effects analysis (FMEA), fault tree analysis (FTA) and failure modes, effects and criticality analysis (FMECA), as well as prior knowledge and experience, to determine potential failure modes. These procedures require designers to have both a broad knowledge of commonly occurring failure modes and an understanding of any connections or causality between failures in order for the design to be successful. If sufficient knowledge is not available to predict all of the realistically possible failure modes, then the current failure prevention procedures may be insufficient. Heft4, Teil 2 (1996) of the Verband der Automobileindustrie, Germany.The traditional FMEA, when performed rigorously, contains valuable information about the failures of various components, but has two fundamental weaknesses: (1) the lack of a methodological guideline to conduct the FMEA; and (2) the lack of a natural, repeatable language to record the information 2 . Current industrial FMEA practice is severely restricted in its usefulness and analytical power due to the limitations of spreadsheet-based approaches to acquiring, representing and reasoning with system failure knowledge. Thus, the standardization of the failure mode vocabulary would make the procedure more useful and repeatable.In this work, we use a matrix-based method to help sort through the failure modes associated with products. A matrix approach for recording failure data was introdu...
Research has shown that nearly 80% of the costs and problems associated with product design are created during product development, and cost and quality are essentially designed into products during the conceptual design stage. Failure identification procedures (such as failure modes and effects analysis (FMEA), failure modes, effects and criticality analysis (FMECA) and fault tree analysis (FTA)) and design of experiments are currently being used for both quality control and for the detection of potential failure modes during the design stage or postproduct launch. Although all of these methods have their own advantages, they do not provide the designer with an indication of the predominant failures that should receive considerable attention while the product is being designed. The work presented here proposes a statistical clustering procedure to identify potential failures in the conceptual design stage. A functional approach, which hypothesizes that similarities exist between different failure modes based on the functionality of the product/component, is employed to identify failure modes. The various steps of the methodology are illustrated using a hypothetical design example. Copyright c 2004 John Wiley & Sons, Ltd.KEY WORDS: clustering algorithm; conceptual design; failure-free design; failure mode; failure modes and effects analysis; function based design; product design; statistical based design BACKGROUND I dentification of potential failure modes during the product design process is critical for creating failure-free designs. Industry currently uses procedures such as failure modes and effects analysis (FMEA), fault tree analysis (FTA) and failure modes, effects and criticality analysis (FMECA), as well as prior knowledge and experience, to determine potential failure modes. These procedures require designers to have both a broad knowledge of commonly occurring failure modes and an understanding of any connections or causality between failures in order for the design to be successful. If sufficient knowledge is not available to predict all of the realistically possible failure modes, then the current failure prevention procedures may be insufficient. Heft4, Teil 2 (1996) of the Verband der Automobileindustrie, Germany.The traditional FMEA, when performed rigorously, contains valuable information about the failures of various components, but has two fundamental weaknesses: (1) the lack of a methodological guideline to conduct the FMEA; and (2) the lack of a natural, repeatable language to record the information 2 . Current industrial FMEA practice is severely restricted in its usefulness and analytical power due to the limitations of spreadsheet-based approaches to acquiring, representing and reasoning with system failure knowledge. Thus, the standardization of the failure mode vocabulary would make the procedure more useful and repeatable.In this work, we use a matrix-based method to help sort through the failure modes associated with products. A matrix approach for recording failure data was introdu...
Research has shown that nearly 80% of the costs and problems are created in product development and that cost and quality are essentially designed into products in the conceptual stage. Currently failure identification procedures (such as FMEA, FMECA and FTA) and design of experiments are being used for quality control and for the detection of potential failure modes during the detail design stage or post-product launch. Though all of these methods have their own advantages, they do not give information as to what are the predominant failures that a designer should focus on while designing a product. This work uses a functional approach to identify failure modes, which hypothesizes that similarities exist between different failure modes based on the functionality of the product/component. In this paper, a statistical clustering procedure is proposed to retrieve information on the set of predominant failures that a function experiences. The various stages of the methodology are illustrated using a hypothetical design example.
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