Soft Computing

, Volume 18, Issue 1, pp 169–183 | Cite as

A more general risk assessment methodology using a soft set-based ranking technique

  • Kuei-Hu Chang
Methodologies and Application


Process failure mode and effects analysis (PFMEA) is used in the high-tech industry to improve a product’s quality and robustness. It is not only an important risk assessment technique but also a valuable task for implementing production management. Its main purpose is to discover and prioritize potential failure modes. Most of the current PFMEA techniques use the risk priority number (RPN) value to evaluate the risk of failure. However, the traditional RPN methodology has a serious problem with regard to measurement scales, does not consider the direct and indirect relationship between potential failure modes and causes of failure, and loses potentially valuable expert-provided information. Moreover, there are unknown, partially known, missing, or nonexistent data identified during the process of collecting data for PFMEA; this increases the difficulty of risk assessment. Issues with incomplete information cannot be fully addressed using the traditional RPN methodology. In order to effectively address this problem, the current paper proposes a novel soft set-based ranking technique for the prioritization of failures in a product PFMEA. For verification of the proposed approach, a numerical example of the Xtal unit PFMEA was adopted. This study also compares the results of the traditional RPN and DEMATEL methods for dealing with incomplete data. The results demonstrate that the proposed approach is preferable for reflecting actual stages of incomplete data in PFMEA. As a result, product and process robustness can be assured.


Soft set Decision making trial and evaluation laboratory Risk priority number Process failure mode and effects analysis Risk assessment 



The author would like to express his sincerest gratitude to the Associate Editor and the anonymous referees for providing very helpful comments and suggestions which led to an improvement of the article. This work was supported in part by the National Science Council of the Republic of China under Contract No. NSC 99-2410-H-145-001 and NSC 101-2410-H-145-001.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Department of Management SciencesR.O.C. Military AcademyKaohsiungTaiwan

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