An improved FMEA analysis method based on QFD and TOPSIS theory

  • Ying-Kui Gu
  • Zi-xin Cheng
  • Guang-qi Qiu
Original Paper


In order to solve the fuzziness in calculating the risk priority number in traditional failure modes and effect analysis (FMEA), a ranking method of failure mode improvement priorities based on technique for order preference by similarity to ideal solution theory was proposed firstly. An integrated analysis model based on FMEA and quality function deployment (QFD) was proposed to fully consider the interaction between various failure modes and the customer satisfaction degree with product performance, economy, and service. The importance of customer requirements is obtained by using the analytic hierarchy process, and the importance of technical characteristics is obtained by using weighted geometric average algorithm. Then the importance of the technical characteristics is converted to the correction coefficient to the FMEA evaluation, so as to obtain the relative harmfulness of each failure model. The proposed integrated model makes up for the deficiencies in FMEA that the relevant information of customer requirements and technical characteristics can not be used as the basis for judging failure mode improvement priorities, and the expansion of each stage of QFD can provide information and basis for the analysis and evaluation of the failure modes in the FMEA. A case of failure modes and effect analysis of a certain diesel engine fuel system was taken as an example to illustrate the proposed method.


Failure modes and effect analysis (FMEA) Technique for order preference by similarity to ideal solution (TOPSIS) Risk priority numbers (RPN) Quality function deployment (QFD) Cross-entropy 



This research was partially supported by the National Natural Science Foundation of China under the Contract Number 61463021, the Young Scientists Object Program of Jiangxi Province, China under the Contract Number 20144BCB23037.


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Copyright information

© Springer-Verlag France SAS, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Mechanical and Electrical EngineeringJiangxi University of Science and TechnologyGanzhouPeople’s Republic of China

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