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| Title: | Failure mode identification through clustering analysis |
| Author (s): | Arunajadai, S. Uder, S. Stone, Robert B. Tumer, I. |
| Department/Lab Affiliations: | Design Engineering Center Interdisciplinary Engineering Student Design Center |
| Keywords: | Clustering algorithm Conceptual design Failure mode Failure modes and effects analysis Failure-free design Function based design Product design Statistical based design |
| Issue Date: | 2004 |
| Publisher: | John Wiley & Sons, Inc. |
| Citation: | Arunajadai, S., Uder, S., Stone, R., and Tumer, I., 2004, “Failure Mode Identification through Clustering Analysis,” Quality and Reliability Engineering International, 20:1-16. |
| Abstract: | 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 post-product 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. |
| Type: | Article - Journal text |
| In Title: | Quality and Reliability Engineering International |
| Copyright Notice: | This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. FULL COPYRIGHT INFORMATION: |
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| title | Failure mode identification through clustering analysis |
| contributor.author | Arunajadai, S. |
| contributor.author | Uder, S. |
| contributor.author | Stone, Robert B. |
| contributor.author | Tumer, I. |
| contributor.deptlab | Design Engineering Center |
| contributor.deptlab | Interdisciplinary Engineering |
| contributor.deptlab | Student Design Center |
| contributor.sponsor | National Science Foundation |
| subject | Clustering algorithm |
| subject | Conceptual design |
| subject | Failure mode |
| subject | Failure modes and effects analysis |
| subject | Failure-free design |
| subject | Function based design |
| subject | Product design |
| subject | Statistical based design |
| date.issued | 2004 |
| publisher | John Wiley & Sons, Inc. |
| identifier.citation | Arunajadai, S., Uder, S., Stone, R., and Tumer, I., 2004, “Failure Mode Identification through Clustering Analysis,” Quality and Reliability Engineering International, 20:1-16. |
| identifier.pub.URI | |
| description.abstract | 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 post-product 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. |
| type | Article - Journal |
| type.DCMIType | text |
| type.status | Postprint |
| rights | This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. |
| rights.URI | |
| relation.isPartOf | Quality and Reliability Engineering International |
| date.accessioned | 2008-05-06T13:29:42Z |
| date.available | 2008-05-06T13:29:40Z |
| identifier.persist.URI |