Constructing Bayesian Network by Integrating FMEA with FTA

Ma, Ding; Zhou, Zhen; Jiang, Yongqing; Ding, Wenfei

doi:10.1109/imccc.2014.148

Cited by 6 publications

(4 citation statements)

References 6 publications

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“…Thus, combining the principles of failure tree analysis with Markov models provides the best results in relation to engineering systems. [19]. In the studies [18][19][20], the method of analyzing the failure tree for various engineering systems was used; the use of this method allowed reducing the time for diagnosing the cause of failures and increasing the efficiency of the systems.…”

Section: Resultsmentioning

confidence: 99%

“…[19]. In the studies [18][19][20], the method of analyzing the failure tree for various engineering systems was used; the use of this method allowed reducing the time for diagnosing the cause of failures and increasing the efficiency of the systems. The presented method is included in national standards, for example, as the standard of the United States of America MIL-HDBK-217 "Reliability prediction of electronic equipment" [21] or the Russian RD 03-418-01 "Guidelines for risk analysis of hazardous showed a significant number of failures in wheels and axles during technological operation.…”

Section: Resultsmentioning

confidence: 99%

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Technical Maintenance of Vehicles: Improvement of Reliability of the Major Components and Units

Tortbayeva,

Pernebekov,

Ussipbayev

et al. 2023

Communications

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The purpose is to determine the impact of operating conditions on the reliability of vehicles, to identify the main causes of failure of truck units and assemblies and to find ways to improve their reliability. The main methods are a systematic approach to analysis of complex technological systems, the fault tree analysis to identify the most common causes of failure of trucks in the climatic conditions of Central Asia. It has been revealed that one of the frequent causes of failure of units and assemblies is fatigue failure, the finite element modelling of which allowed the study to obtain a diagram of limit deviations for various cycle asymmetries and as a result, the ability to predict the process of fatigue failure under the influence of external factors. The study results are aimed at the possibility of predicting the failure of components and assemblies of trucks conditioned by fatigue failure.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Technical Maintenance of Vehicles: Improvement of Reliability of the Major Components and Units

Tortbayeva,

Pernebekov,

Ussipbayev

et al. 2023

Communications

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“…To ensure the scientificity, objectivity, and rationality of the selected risk factors, this paper consults with experienced experts in the industry field and consults relevant materials to obtain the main potential risk factors of China's imported bauxite maritime logistics (see Table 8). Improper operation by the crew FM 4 Piracy or terrorist attack FM 5 Terrible sea conditions FM 6 Bauxite-free surface effect FM 7 Ship facilities and equipment failure Among these failure modes, the first one is related to bauxite transit reliability. Guinea has been China's largest source of imported bauxite in recent years.…”

Section: Identification Of Failure Mode Of Bauxite Ocean Maritime Log...mentioning

confidence: 99%

Risk Assessment of Bauxite Maritime Logistics Based on Improved FMECA and Fuzzy Bayesian Network

Sun

Wang

2023

JMSE

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Because of the many limitations of the traditional failure mode effect and criticality analysis (FMECA), an integrated risk assessment model with improved FMECA, fuzzy Bayesian networks (FBN), and improved evidence reasoning (ER) is proposed. A new risk characterization parameter system is constructed in the model. A fuzzy rule base system based on the confidence structure is constructed by combining fuzzy set theory with expert knowledge, and BN reasoning technology is used to realize the importance ranking of the hazard degree of maritime logistics risk events. The improved ER based on weight distribution and matrix analysis can effectively integrate the results of risk event assessment and realize the hazard evaluation of the maritime logistics system from the overall perspective. The effectiveness and feasibility of the model are verified by carrying out a risk assessment on the maritime logistics of importing bauxite to China. The research results show that the priority of risk events in the maritime logistics of bauxite are “pirates or terrorist attacks” and “workers’ riots or strikes” in sequence. In addition, the bauxite maritime logistics system is at a medium- to high-risk level as a whole. The proposed model is expected to provide a systematic risk assessment model and framework for the engineering field.

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“…The use of Bayesian networks (BNs) has been integrated into improved FMEA versions integrating stochastic uncertainty and conditional probabilities into models. A BN has an advantage in dealing with uncertainty [22]. Therefore, a good FMEA has the necessary features to build a good BN: a bottom-up (or top-down) analysis of all the components, subcomponents and cause-failure-effect chains [23].…”

Section: Introductionmentioning

confidence: 99%

Bayesian Linguistic Conditional System as an Attention Mechanism in a Failure Mode and Effect Analysis

Baeza-Serrato

2024

Applied Sciences

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Fuzzy Inference System behavior can be described qualitatively using a natural language, which is known as the expert-driven approach to handling non-statistical uncertainty. Generally, practical applications involve conceptualizing the problem by integrating linguistic uncertainty and using data by integrating stochastic uncertainty. The proposed probabilistic fuzzy system uses the Gaussian Density Function (GDF) to assign a probability to input variables integrating stochastic uncertainty. In addition, a linguistic interpretation is used to project various categories of the GDF integrating linguistic uncertainty. Likewise, one of the relevant aspects of the proposal is to weigh each input variable according to the heuristic interpretation that determines the probability assigned to each of them a priori. Therefore, the main contribution of the research focuses on using the Bayesian Linguistic Conditional System (BLCS) as a mechanism of attention to relate the categories of the different input variables and find their posterior-weighted probability at a normalization stage. Finally, the knowledge base is established through linguistic rules, and the system’s output is a Bayesian classifier multiplying its normalized posterior conditional probabilities. The highest probability value of the knowledge base is identified, and the Risk Priority Number Weighted (RPNW) is determined using their respective posterior-normalized probabilities for each input variable. The results are expressed on a simple and precise scale from 1 to 10. They are compared with the Risk Priority Number (RPN), which results in a Failure Mode and Effect Analysis (FMEA). They show similar behaviors for multiple combinations in the evaluations while highlighting different scales.

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Constructing Bayesian Network by Integrating FMEA with FTA

Cited by 6 publications

References 6 publications

Technical Maintenance of Vehicles: Improvement of Reliability of the Major Components and Units

Technical Maintenance of Vehicles: Improvement of Reliability of the Major Components and Units

Risk Assessment of Bauxite Maritime Logistics Based on Improved FMECA and Fuzzy Bayesian Network

Bayesian Linguistic Conditional System as an Attention Mechanism in a Failure Mode and Effect Analysis

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