Use-related risk analysis for medical devices based on improved FMEA

Ling, Liansheng; Ma, Shuai; Zhu, Wang; Li, Ping

doi:10.3233/wor-2012-0976-5860

Cited by 11 publications

(9 citation statements)

References 2 publications

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“…To overcome the above drawbacks, fuzzy logic has been widely applied in Failure Modes, Effects and Criticality Analysis [33]. Vast majority of fuzzy FMECA approaches employs fuzzy if-then rules for prioritization of failure modes [34]- [37]. This requires a vast amount of expert knowledge and expertise.…”

Section: Fuzzy and Multi-criteria Approachesmentioning

confidence: 99%

A Critical Comparison of Alternative Risk Priority Numbers in Failure Modes, Effects, and Criticality Analysis

2019

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Risk priority number (RPN) is a widely used approach, and it is a powerful means to assess the criticality of modes in a failure modes, effects, and criticality analysis (FMECA) worksheet. In the application of the traditional FMECA, the RPN is determined to rank the failure modes; however, the method has been criticized several times for having many drawbacks and weaknesses, such as the presence of gaps in the range of admissible values, the duplicates value provided by different combinations of the base factors, and the high sensitivity to small changes. This paper analyses and compares some alternative RPN formulation proposed in the literature to overcome these limits. This paper takes into account only the alternative RPN, which proposes a powerful solution without increasing the computational complexity and remaining coherent to the classical idea included in the international standard IEC 60812. In order to compare the advantages and disadvantages of these alternative RPNs, an FMECA was developed for a heating, ventilation, and air condition (HVAC) system in railway application. The critical analysis of the comparison can provide recommendations and suggestions regarding the choice of the alternative RPN based on the type of application. Finally, this paper takes into account the scales reduction of possible values related to the parameters (i.e., occurrence, severity, and detection), which influence the assessment of the RPN. This approach allows the designers to mitigate the drawbacks related to the full scale and provide an easier and faster assessment of the scores to evaluate the criticality analysis and prioritization. INDEX TERMS FMECA, railway engineering, reliability theory, risk priority number.

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Section: Fuzzy and Multi-criteria Approachesmentioning

confidence: 99%

A Critical Comparison of Alternative Risk Priority Numbers in Failure Modes, Effects, and Criticality Analysis

2019

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“…Except the above optimization of RPN, most of the work is mainly focused on fuzzy logic, for the classical FMECA ignores some real situations. Hence, fuzzy FMECA methods are employed to express the uncertainty [ 22 , 23 ]. The approach needs a large amount of proper expertise and experience.…”

Section: Literature Reviewmentioning

confidence: 99%

A Novel Approach to Support Failure Mode, Effects, and Criticality Analysis Based on Complex Networks

Wang

Dai

Luo³

et al. 2019

Entropy

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Failure Mode, Effects and Criticality Analysis (FMECA) is a method which involves quantitative failure analysis. It systematically examines potential failure modes in a system, as well as the components of the system, to determine the impact of a failure. In addition, it is one of the most powerful techniques used for risk assessment and maintenance management. However, various drawbacks are inherent to the classical FMECA method, especially in ranking failure modes. This paper proposes a novel approach that uses complex networks theory to support FMECA. Firstly, the failure modes and their causes and effects are defined as nodes, and according to the logical relationship between failure modes, and their causes and effects, a weighted graph is established. Secondly, we use complex network theory to analyze the weighted graph, and the entropy centrality approach is applied to identify influential nodes. Finally, a real-world case is presented to illustrate and verify the proposed method.

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“…The grey theory has been applied widely to deal with decisions characterized by incomplete information well, such as operation, mechanism, structure, healthcare, behavior, which are neither deterministic nor totally unknown, but are partially known. As it can explore system behavior using relation analysis and model construction well, many different approaches integrating grey theory with FMEA have been suggested to detect the failure modes.…”

Section: Preliminariesmentioning

confidence: 99%

An Evidential Failure Mode and Effects Analysis Using Linguistic Terms

Xiao

Fei

et al. 2016

Quality & Reliability Eng

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Failure mode and effects analysis (FMEA) has been extensively used in reliability engineering domain. Risk priority number (RPN), defined as the product of occurrence (O), severity (S), and detection (D) of a failure, is the most important measure used in FMEA for prioritizing risk. In this paper, a new evidential FMEA using linguistic term is presented. First, the linguistic terms have been applied in the form of assessment distribution, which enables the experts to express their assessments in a more realistic way and hence improving the applicability of the FMEA. Second, a novel method to transform the experts' linguistic judgments into basic probability assignments (BPAs) is proposed. Third, the flexibility of assigning a weight to each criterion in the FMEA provides a means of specifically identifying weak areas in the system/component studied. At the same time, the weights can be utilized as the discounting coefficients to address the problem existing in conflicting evidence combination. An example is illustrated to show the practical application of the proposed FMEA methodology in engineering. Copyright © 2016 John Wiley & Sons, Ltd.

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Use-related risk analysis for medical devices based on improved FMEA

Cited by 11 publications

References 2 publications

A Critical Comparison of Alternative Risk Priority Numbers in Failure Modes, Effects, and Criticality Analysis

A Critical Comparison of Alternative Risk Priority Numbers in Failure Modes, Effects, and Criticality Analysis

A Novel Approach to Support Failure Mode, Effects, and Criticality Analysis Based on Complex Networks

An Evidential Failure Mode and Effects Analysis Using Linguistic Terms

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