Fuzzy-based failure mode and effect analysis (FMEA) of a hybrid molten carbonate fuel cell (MCFC) and gas turbine system for marine propulsion

Ahn, Junkeon; Noh, Yeelyong; Park, Sung Ho; Choi, Byung Il; Chang, Daejun

doi:10.1016/j.jpowsour.2017.08.028

Cited by 67 publications

(34 citation statements)

References 20 publications

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“…Moreover, the third category is dependent on the severity of a failure. For a bigger failure, the value of the severity is higher [11,43]. It should be noted that the classification of the occurrence, detectability, and severity is completely case dependent.…”

Section: Failure Mode and Effect Analysis (Fmea)mentioning

confidence: 99%

“…In other words, the descriptions in Tables 2-4 vary for different case studies. This paper uses the same standard as [11] for the application of a PEMFC in a marine power system. The result of the FMEA is the risk priority number (RPN), which is mainly computed by the multiplication of the mentioned three factors.…”

Section: Failure Mode and Effect Analysis (Fmea)mentioning

confidence: 99%

“…However, because of the practical imprecision and uncertainty, conventional FMEA techniques lead to low reliability and inaccurate results [48]. Recently, fuzzy type-1 logic techniques are considered for the FMEA [11] to improve the conventional results. However, these techniques still may lead to inaccurate results due to their inherent sensitivity with respect to the uncertainty.…”

Section: General Type-ii Fuzzy Based Failure Mode and Effect Analysismentioning

confidence: 99%

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A Novel Type-2 Fuzzy Logic for Improved Risk Analysis of Proton Exchange Membrane Fuel Cells in Marine Power Systems Application

et al. 2018

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A marine energy system, which is fundamentally not paired with electric grids, should work for an extended period with high reliability. To put it in another way, by employing electrical utilities on a ship, the electrical power demand has been increasing in recent years. Besides, fuel cells in marine power generation may reduce the loss of energy and weight in long cables and provide a platform such that each piece of marine equipment is supplied with its own isolated wire connection. Hence, fuel cells can be promising power generation equipment in the marine industry. Besides, failure modes and effects analysis (FMEA) is widely accepted throughout the industry as a valuable tool for identifying, ranking, and mitigating risks. The FMEA process can help to design safe hydrogen fueling stations. In this paper, a robust FMEA has been developed to identify the potentially hazardous conditions of the marine propulsion system by considering a general type-2 fuzzy logic set. The general type-2 fuzzy system is decomposed of several interval type-2 fuzzy logic systems to reduce the inherent highly computational burden of the general type-2 fuzzy systems. Linguistic rules are directly incorporated into the fuzzy system. Finally, the results demonstrate the success and effectiveness of the proposed approach in computing the risk priority number as compared to state-of-the-art methods.

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Section: Failure Mode and Effect Analysis (Fmea)mentioning

confidence: 99%

Section: Failure Mode and Effect Analysis (Fmea)mentioning

confidence: 99%

Section: General Type-ii Fuzzy Based Failure Mode and Effect Analysismentioning

confidence: 99%

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A Novel Type-2 Fuzzy Logic for Improved Risk Analysis of Proton Exchange Membrane Fuel Cells in Marine Power Systems Application

et al. 2018

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“…Based on the FMEA, the RPNs indicate the importance of different failure modes, and the failure modes with higher RPNs should be corrected and given a higher priority than those with lower RPNs. The detailed procedures for performing an FMEA in different industries have been introduced by Spreafico, Ahn, and Chen …”

Section: Preliminariesmentioning

confidence: 99%

A novel framework for the reliability modelling of repairable multistate complex mechanical systems considering propagation relationships

Gao

Wang

Gao

et al. 2018

Quality & Reliability Eng

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Due to the propagation, amplification, and concatenation in a failure process, the reliabilities of repairable multistate complex mechanical systems (RMCMSs) may be affected by a significant fluctuation due to a small exception associated with a reliability indicator. Focused on the problems arising from the lack of propagation relationships among fault modes, functional components, and failure causes in conventional reliability models, a novel framework for reliability modelling is proposed to comprehensively analyse the reliabilities of RMCMSs. First, the reliability models are abstracted as weighted and directed networks with five layers. Second, an improved failure mode and effects analysis (IFMEA) method combined with the D‐number method and VIKOR approach is presented to determine the importance of reliability nodes. Third, a cut set of the reliability model is generated by any exception of a reliability indicator by considering the propagation relationships, and the reliability sensibility index is defined to characterize the fluctuations in system reliability. The effectiveness of the proposed framework is demonstrated in an actual reliability modelling application. As an intuitive method, the proposed framework inherits the advantages of conventional models but overcomes the drawbacks of these existing methods. Therefore, this method can be flexibly and efficiently used in the reliability modelling of RMCMSs. Moreover, the approach provides a foundation for comprehensive and dynamic reliability analysis and the failure mechanism mining of RMCMSs, and it can be used in other engineering applications.

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“…Research has been conducted on an approach combining FMEA and the Boolean representation method (BRM) [7], a method that describes the elements required for FMEA and then develops and applies an appropriate FMEA form for an effective evaluation. Studies have also used a computer system method that supports FMEA evaluations on the Internet [8], the risk priority ranks (RPR) approach to prioritize failure modes [9], a method based on fuzzy logic that considers the interdependence between various failure modes [10][11][12][13][14], a fuzzy-based FMEA performance improvement method using GRAY relationship theory [15], and a method that provides a framework for automatically generating FMEA from past FMEA data using functional inference techniques [16]. Research has additionally been conducted on how to most effectively apply the FEMA system due to difficulties related to its numerous subsystems and the lack of consideration for the indirect relationship between the components in the RPN technique.In particular, in recent years, in order to apply environmentally friendly ships, ships using hybrid fuel cells, batteries, etc.…”

mentioning

confidence: 99%

Comparison and Verification of Reliability Assessment Techniques for Fuel Cell-Based Hybrid Power System for Ships

Jeon

Park

Kim

2020

JMSE

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In order to secure the safe operation of the ship, it is crucial to closely examine the suitability from the design stage of the ship, and to set up a preliminary review and countermeasures for failures and defects that may occur during the construction process. In shipyards, the failure mode and effects analysis (FMEA) evaluation method using risk priority number (RPN) is used in the shipbuilding process. In the case of the conventional RPN method, evaluation items and criteria are ambiguous, and subjective factors such as evaluator’s experience and understanding of the system operate a lot on the same contents, resulting in differences in evaluation results. Therefore, this study aims to evaluate the safety and reliability for ship application of the reliability-enhanced fuel cell-based hybrid power system by applying the re-established FMEA technique. Experts formed an FMEA team to redefine reliable assessment criteria for the RPN assessment factors severity (S), occurrence (O), and detection (D). Analyze potential failures of each function of the molten-carbonate fuel cell (MCFC) system, battery system, and diesel engine components of the fuel cell-based hybrid power system set as evaluation targets to redefine the evaluation criteria, and the evaluation criteria were derived by identifying the effects of potential failures. In order to confirm the reliability of the derived criteria, the reliability of individual evaluation items was verified by using the significance probability used in statistics and the coincidence coefficient of Kendall. The evaluation was conducted to the external evaluators using the reestablished evaluation criteria. As a result of analyzing the correspondence according to the results of the evaluation items, the severity was 0.906, the incidence 0.844, and the detection degree 0.861. Improved agreement was obtained, which is a significant result to confirm the reliability of the reestablished evaluation results.

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Fuzzy-based failure mode and effect analysis (FMEA) of a hybrid molten carbonate fuel cell (MCFC) and gas turbine system for marine propulsion

Cited by 67 publications

References 20 publications

A Novel Type-2 Fuzzy Logic for Improved Risk Analysis of Proton Exchange Membrane Fuel Cells in Marine Power Systems Application

A Novel Type-2 Fuzzy Logic for Improved Risk Analysis of Proton Exchange Membrane Fuel Cells in Marine Power Systems Application

A novel framework for the reliability modelling of repairable multistate complex mechanical systems considering propagation relationships

Comparison and Verification of Reliability Assessment Techniques for Fuel Cell-Based Hybrid Power System for Ships

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