Application of risk management plan to technical risks in metro construction: Case study of the Grand Paris Express project

Zhang, Yi

doi:10.1016/j.tust.2024.105716

Cited by 4 publications

(2 citation statements)

References 22 publications

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“…Additionally, studies on risk management across different stages of prefabricated steel structure construction have become more comprehensive (Y. Zhang, 2024). Notably, Leu et al (2015) utilized fault trees and Bayesian networks to develop a model for assessing safety risks at construction sites.…”

Section: Literature Reviewmentioning

confidence: 99%

Quality Risk Assessment of Prefabricated Steel Structural Components during Production Using Fuzzy Bayesian Networks: A Case Study in China

Zhong,

Peng

2024

Preprint

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This study aims to address quality issues in the production of prefabricated steel structural components for buildings by investigating challenges in quality risk assessment. It identifies key factors contributing to quality problems and establishes an evaluation index system. Traditional methods encounter limitations in handling uncertainty and conducting quantitative analysis. Therefore, the fuzzy Bayesian network (FBN) theory is utilized to perform probabilistic analysis on quality risks during the production phase. This research achieves a more accurate and dynamic risk assessment by integrating the strengths of fuzzy logic and Bayesian networks (BNs) and by utilizing expert knowledge, the similarity aggregation method (SAM), and the noisy-OR gate model. The study reveals that factors such as the "low professional level of designers," "poor production refinement," and "poor storage conditions for finished products" have a significant impact on quality risks. This research offers a novel risk assessment tool for steel structural component production, effectively assisting enterprises in identifying potential risks, formulating risk reduction strategies, and enhancing production quality.

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Section: Literature Reviewmentioning

confidence: 99%

Quality Risk Assessment of Prefabricated Steel Structural Components during Production Using Fuzzy Bayesian Networks: A Case Study in China

Zhong,

Peng

2024

Preprint

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“…This research encompasses various dimensions, including evaluating safety performance risks in prefabricated buildings [13], controlling project investment risks [14], and conducting risk assessments during the construction phase [15,16]. Additionally, studies on risk management across different stages of prefabricated steel structure construction have become more comprehensive [17]. Notably, Leu & Chang et al [18] utilized fault trees and Bayesian networks to develop a model for assessing safety risks at construction sites.…”

Section: Literature Reviewmentioning

confidence: 99%

Quality Risk Assessment of Prefabricated Steel Structural Components during Production Using Fuzzy Bayesian Networks

Zhong,

Peng

2024

Buildings

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This study aims to address quality issues in the production of prefabricated steel structural components for buildings by investigating challenges in quality risk assessment. It identifies key factors contributing to quality problems and establishes an evaluation index system. Traditional methods encounter limitations in handling uncertainty and conducting quantitative analysis. Therefore, the fuzzy Bayesian network (FBN) theory is utilized to perform a probabilistic analysis of quality risks during the production phase. This research achieves a more accurate and dynamic risk assessment by integrating the strengths of fuzzy logic and Bayesian networks (BNs) and by utilizing expert knowledge, the similarity aggregation method (SAM), and the noisy-OR gate model. The study reveals that factors such as the “low professional level of designers”, “poor production refinement”, and “poor storage conditions for finished products” have a significant impact on quality risks. This study offers a scientific risk assessment tool designed to address the quality control challenges commonly experienced in the manufacturing of steel structural components. Identifying the critical risk factors that influence quality empowers actual production enterprises to develop risk management strategies and improvement measures in a more focused manner, thereby facilitating more effective resource allocation and risk prevention and control. Consequently, this approach has a significant impact on enhancing the overall production level and quality within the industry.

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Towards safety and efficiency by assessment of positioning approaches for Enhanced navigation in road tunnels

Broz,

Tichy,

Vlkovsky

et al. 2025

Tunnelling and Underground Space Technology

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Application of risk management plan to technical risks in metro construction: Case study of the Grand Paris Express project

Cited by 4 publications

References 22 publications

Quality Risk Assessment of Prefabricated Steel Structural Components during Production Using Fuzzy Bayesian Networks: A Case Study in China

Quality Risk Assessment of Prefabricated Steel Structural Components during Production Using Fuzzy Bayesian Networks: A Case Study in China

Quality Risk Assessment of Prefabricated Steel Structural Components during Production Using Fuzzy Bayesian Networks

Towards safety and efficiency by assessment of positioning approaches for Enhanced navigation in road tunnels

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