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Failure mode and effect analysis with extended grey relational analysis method in cloud setting

Failure mode and effect analysis with extended grey relational analysis method in cloud setting Failure mode and effect analysis (FMEA) is a useful quality management technique applied in various industries for enhancing the reliability and safety of systems, products, processes and services. The traditional FMEA, however, has been criticised for many internal defects in the evaluation of failure modes, the determination of risk factor weights and the ranking of failure modes, which weaken its accuracy and effectiveness when applied. In this paper, we propose a new FMEA methodology integrating cloud model theory with extended grey relational analysis (GRA) for resolving the disadvantages of the classical risk priority number approach. First, cloud model theory is adopted to express the uncertain linguistic assessments given by FMEA team members. Then, an extended GRA method is presented to obtain the risk priority of the failure modes in FMEA. Moreover, based on the idea of GRA, a multiple objective optimisation model is established to calculate the risk factor weights with incomplete weight information. The feasibility and practicality of the proposed FMEA are elucidated by virtue of an empirical example from the paper industry. The results indicate that the new risk assessment model is able to produce more reliable risk ranking results of failure modes for risk-reducing actions. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Total Quality Management & Business Excellence Taylor & Francis

Failure mode and effect analysis with extended grey relational analysis method in cloud setting

Failure mode and effect analysis with extended grey relational analysis method in cloud setting

Total Quality Management & Business Excellence , Volume 30 (7-8): 23 – May 19, 2019

Abstract

Failure mode and effect analysis (FMEA) is a useful quality management technique applied in various industries for enhancing the reliability and safety of systems, products, processes and services. The traditional FMEA, however, has been criticised for many internal defects in the evaluation of failure modes, the determination of risk factor weights and the ranking of failure modes, which weaken its accuracy and effectiveness when applied. In this paper, we propose a new FMEA methodology integrating cloud model theory with extended grey relational analysis (GRA) for resolving the disadvantages of the classical risk priority number approach. First, cloud model theory is adopted to express the uncertain linguistic assessments given by FMEA team members. Then, an extended GRA method is presented to obtain the risk priority of the failure modes in FMEA. Moreover, based on the idea of GRA, a multiple objective optimisation model is established to calculate the risk factor weights with incomplete weight information. The feasibility and practicality of the proposed FMEA are elucidated by virtue of an empirical example from the paper industry. The results indicate that the new risk assessment model is able to produce more reliable risk ranking results of failure modes for risk-reducing actions.

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References (54)

Publisher
Taylor & Francis
Copyright
© 2017 Informa UK Limited, trading as Taylor & Francis Group
ISSN
1478-3371
eISSN
1478-3363
DOI
10.1080/14783363.2017.1337506
Publisher site
See Article on Publisher Site

Abstract

Failure mode and effect analysis (FMEA) is a useful quality management technique applied in various industries for enhancing the reliability and safety of systems, products, processes and services. The traditional FMEA, however, has been criticised for many internal defects in the evaluation of failure modes, the determination of risk factor weights and the ranking of failure modes, which weaken its accuracy and effectiveness when applied. In this paper, we propose a new FMEA methodology integrating cloud model theory with extended grey relational analysis (GRA) for resolving the disadvantages of the classical risk priority number approach. First, cloud model theory is adopted to express the uncertain linguistic assessments given by FMEA team members. Then, an extended GRA method is presented to obtain the risk priority of the failure modes in FMEA. Moreover, based on the idea of GRA, a multiple objective optimisation model is established to calculate the risk factor weights with incomplete weight information. The feasibility and practicality of the proposed FMEA are elucidated by virtue of an empirical example from the paper industry. The results indicate that the new risk assessment model is able to produce more reliable risk ranking results of failure modes for risk-reducing actions.

Journal

Total Quality Management & Business ExcellenceTaylor & Francis

Published: May 19, 2019

Keywords: FMEA; cloud model; grey relational analysis; incomplete weight; quality management

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