Reliability Analysis of Correlated Failure Modes by Transforming Fault Tree Model to Bayesian Network: A Case Study of the MDS of a CNC Machine Tool

Li, He; Yazdi, Mohammad

doi:10.1007/978-3-031-07430-1_2

Cited by 11 publications

(2 citation statements)

References 32 publications

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“…This section evaluates the viability and effectiveness of the proposed methodology by conducting a comparative analysis with two conventional MCDM methods initially, followed by a comparison with regular Bayesian networks (BNs). Specifically, the performance of the new method is benchmarked against the best-worst method (BWM) [122,123], Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) [124], and standard BN [125,126]. The comparative findings, as displayed in Table 6 and depicted in Fig.…”

Section: Comparison Analysismentioning

confidence: 99%

E-waste circular economy decision-making: a comprehensive approach for sustainable operation management in the UK

Yazdi,

Moradi,

Nedjati

et al. 2024

Neural Comput & Applic

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E-waste generation has broadly increased worldwide and is called intense pressure on sustainable practice implementation firms by recycling and redesigning the products. Thus, e-waste operation management in developed countries like the UK has become the top priority and is subjected to multiple sustainable circular economies (CE) contributing factors, including social, technical, environmental, and governmental policies. The authorized decision-makers can benefit from a well-established systematic decision-making tool to assess and evaluate the e-waste operation management considering the potential CE contributing factors. An extensive literature overview is expanded to identify the most relevant and influential contributing factors to e-waste CE. The city of London Metropolitan has been selected as the case location. In this regard, it is necessary to utilize an advanced multi-criteria decision-making tool to explore the interdependency and causality of CE-relevant factors. The present study proposed an innovative decision-making approach to address the multiple contributing factors of causality, interdependency, data, and model uncertainty in practice. It uses the step-wise weighted influence nonlinear gauge system method integrated with Fermatean fuzzy linguistic sets. This study conducted a sensitivity analysis to evaluate the effectiveness of the proposed decision-making approach in e-waste operation management. The results are promising, clearly demonstrating the framework’s competence. The CE index, crucial in designing e-waste operation management strategies, was calculated to be 2.8036. Among the various factors analyzed, “Environmental Management Systems” emerged as the most significant driving factor. This underscores the critical need to improve environmental management systems within e-waste operations.

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Section: Comparison Analysismentioning

confidence: 99%

E-waste circular economy decision-making: a comprehensive approach for sustainable operation management in the UK

Yazdi,

Moradi,

Nedjati

et al. 2024

Neural Comput & Applic

Self Cite

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“…Different techniques can be applied to determine the risk priorities associated with hazards in a particular system. Among the most notable are what-if analysis, checklists, hazard and operability study (HAZOP) [5,6], failure mode and effect analysis (FMEA) [7][8][9], fault tree analysis [10][11][12][13][14], and the risk matrix [15,16]. Each of these methods offers invaluable insights, especially when assessing hazards in specialized sectors like healthcare units.…”

Section: Introductionmentioning

confidence: 99%

Enhancing System Safety and Reliability through Integrated FMEA and Game Theory: A Multi-Factor Approach

Yazdi

2023

Safety

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This study aims to address the limitations of traditional Failure Mode and Effect Analysis (FMEA) in managing safety and reliability within complex systems characterized by interdependent critical factors. We propose an integrated framework that combines FMEA with the strategic decision-making principles of Game Theory, thereby enhancing the assessment and mitigation of risks in intricate environments. The novel inclusion of the Best Worst Method (BWM) and Pythagorean fuzzy uncertain linguistic variables refines the accuracy of risk evaluation by overcoming the inherent deficiencies of conventional FMEA approaches. Through sensitivity analysis, the framework’s efficacy in identifying and prioritizing failure modes is empirically validated, guiding the development of targeted interventions. The practical application of our methodology is demonstrated in a comprehensive healthcare system analysis, showcasing its versatility and significant potential to improve operational safety and reliability across various sectors. This research is particularly beneficial for systems engineers, risk managers, and decision-makers seeking to fortify complex systems against failures and their effects.

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Advances in Intelligent Reliability and Maintainability of Energy Infrastructure Assets

Peng

Adumene

et al. 2023

Studies in Systems, Decision and Control

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Reliability Analysis of Correlated Failure Modes by Transforming Fault Tree Model to Bayesian Network: A Case Study of the MDS of a CNC Machine Tool

Cited by 11 publications

References 32 publications

E-waste circular economy decision-making: a comprehensive approach for sustainable operation management in the UK

E-waste circular economy decision-making: a comprehensive approach for sustainable operation management in the UK

Enhancing System Safety and Reliability through Integrated FMEA and Game Theory: A Multi-Factor Approach

Advances in Intelligent Reliability and Maintainability of Energy Infrastructure Assets

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