Multiple failure mode and effects analysis - an approach to risk assessment of multiple failures with FMEA

Pickard, K.; Müller, Péter; Bertsche, Bernd

doi:10.1109/rams.2005.1408405

Cited by 28 publications

(17 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…For instance, Gargama et al [4] develop a fuzzy risk priority number (FRPN) method for single failure mode analysis, but the effects of the components on the system with multiples failure modes have not been taken into account. According to the problem, Brought to you by | Purdue University Libraries Authenticated Download Date | 6/1/15 11:30 PM Pickard et al [5] have taken the consideration of multiple failures within a system. However, multiple failure prob lems of a large and complex system have not yet been successfully handled.…”

Section: Introductionmentioning

confidence: 99%

Weighted Fuzzy Risk Priority Number Evaluation of Turbine and Compressor Blades Considering Failure Mode Correlations

Gan

Zhu

et al. 2014

International Journal of Turbo &Amp; Jet-Engines

View full text Add to dashboard Cite

Failure mode, effects and criticality analysis (FMECA) and Fault tree analysis (FTA) are powerful tools to evaluate reliability of systems. Although single failure mode issue can be efficiently addressed by traditional FMECA, multiple failure modes and component correla tions in complex systems cannot be effectively evaluated. In addition, correlated variables and parameters are often assumed to be precisely known in quantitative analysis. In fact, due to the lack of information, epistemic uncertainty commonly exists in engineering design. To solve these problems, the advantages of FMECA, FTA, fuzzy theory, and Copula theory are integrated into a unified hybrid method called fuzzy probability weighted geometric mean (FPWGM) risk priority number (RPN) method. The epis temic uncertainty of risk variables and parameters are characterized by fuzzy number to obtain fuzzy weighted geometric mean (FWGM) RPN for single failure mode. Multiple failure modes are connected using minimum cut sets (MCS), and Boolean logic is used to combine fuzzy risk priority number (FRPN) of each MCS. Moreover, Copula theory is applied to analyze the correlation of multiple failure modes in order to derive the failure pro babilities of each MCS. Compared to the case where de pendency among multiple failure modes is not consid ered, the Copula modeling approach eliminates the error of reliability analysis. Furthermore, for purpose of quan titative analysis, probabilities importance weight from failure probabilities are assigned to FWGM RPN to reas sess the risk priority, which generalize the definition of probability weight and FRPN, resulting in a more accurate estimation than that of the traditional models. Finally, a basic fatigue analysis case drawn from turbine and com pressor blades in aeroengine is used to demonstrate the effectiveness and robustness of the presented method. The result provides some important insights on fatigue reliability analysis and risk priority assessment of struc tural system under failure correlations.

show abstract

Section: Introductionmentioning

confidence: 99%

Weighted Fuzzy Risk Priority Number Evaluation of Turbine and Compressor Blades Considering Failure Mode Correlations

Gan

Zhu

et al. 2014

International Journal of Turbo &Amp; Jet-Engines

View full text Add to dashboard Cite

show abstract

“…The advantages, although there are some things that have to be considered, are that the information can be passed on over the complete design cycle and the lifetime prediction in earlier design stages than with tests. Future projects, in cooperation with industries, will try to consider multiple failures in FMEA, according to the approach in 7 , for the determination of the lifetime behaviour and the transferability of the results gained in the area of automotive transmissions on other industrial products and/or systems.…”

Section: Discussionmentioning

confidence: 99%

Integrative qualitative quality assurance and reliability prediction over the complete product design cycle

Pickard

Dieter

2008

Quality & Reliability Eng

Self Cite

View full text Add to dashboard Cite

In this paper the possibilities of a qualitative and systematic procedure for the selection of the most developable concept in early design stages and the transfer of the gained information into a failure mode and effects analysis are shown. Further, the possibility of deriving reasonable lifetime distributions from the FMEA assessment values for the description of the system behaviour is demonstrated. With this integrative qualitative approach new products can be accompanied with a procedure, which passes on all its information without any losses, over the complete product design cycle.

show abstract

“…Hsu et al [31] suggested a method that uses this technique to analyse the risks of components in compliance with the EU RoHS directive in the quality control stage. Pickard et al [32] proposed an integrated model that combined multiple failure modes into a single one, to investigate a system that simultaneously considers various failure modes. Recently, FMEA has often been coupled with other methods to improve its applicability in risk management.…”

Section: Failure Mode and Effect Analysis (Fmea)mentioning

confidence: 99%

Identification and Prioritisation of Risk Factors in R&D Projects Based on an R&D Process Model

2018

View full text Add to dashboard Cite

Abstract:Although the importance of risk management and failure management has been emphasized in many organizations for sustainable development, most of the related studies have dealt with manufacturing or service processes, rather than R&D processes. Since R&D projects have high uncertainty in schedule and the quality of output, more attention should be paid to manage the risks of R&D activities. Thus, this paper proposes a systemic approach to performing R&D failure and risk management in the R&D process. To these ends, failure mode and effect analysis (FMEA) is employed, and is modified to meet the specific features of R&D activities with a stage-gate model that can identify the failure modes in each stage of the R&D process model. In addition, a process to prioritize the risks of R&D failure is suggested to support a decision-making process in R&D management, by applying the decision-making trial and evaluation laboratory (DEMATEL). The proposed approach is applied to a case of R&D process of a software development company, in order to illustrate its validity. This paper can help R&D managers to identify and cope with the risks in the R&D process by employing a systematic method.

show abstract

Multiple failure mode and effects analysis - an approach to risk assessment of multiple failures with FMEA

Cited by 28 publications

References 2 publications

Weighted Fuzzy Risk Priority Number Evaluation of Turbine and Compressor Blades Considering Failure Mode Correlations

Weighted Fuzzy Risk Priority Number Evaluation of Turbine and Compressor Blades Considering Failure Mode Correlations

Integrative qualitative quality assurance and reliability prediction over the complete product design cycle

Identification and Prioritisation of Risk Factors in R&D Projects Based on an R&D Process Model

Contact Info

Product

Resources

About