Article
Engineering, Industrial
Jian-Lan Zhou, Ze-Tai Yu, Ren-Bin Xiao
Summary: The Success Likelihood Index Method (SLIM) is widely used to estimate human error probability. To overcome its reliance on a small number of experts, researchers proposed a large-scale group SLIM (LG-SLIM) problem to establish a consensus model and conducted related experiments in railway driving.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Engineering, Industrial
Hu -Chen Liu, Jing-Hui Wang, Ling Zhang, Qi-Zhen Zhang
Summary: Human reliability analysis is a method used to enhance the safety and reliability of complex socio-technical systems. Current studies often involve small groups of experts, which is insufficient for addressing increasingly complex problems. This article proposes a large group SLIM model that considers experts' noncooperative behaviors and social relations, and effectively calculates the human error probabilities of tasks.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Engineering, Industrial
Danilo T. M. P. Abreu, Marcos C. Maturana, Enrique Lopez Droguett, Marcelo R. Martins
Summary: This paper proposes a methodology for human reliability analysis in maritime pilotage operations. The results suggest that the presence or absence of a pilot significantly affects accident probabilities, and identifies key performance shaping factors.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Engineering, Industrial
Gizem Kayisoglu, Bunyamin Gunes, Elif Bal Besikci
Summary: System reliability assessment is important for the operation and maintenance of industrial and service sectors, including maritime transportation. Safety is a top priority for the maritime transportation sector due to its direct impact on the environment, human life, and goods transported. Human factors play a critical role in improving safety and reliability assessment is vital for researchers and decision makers.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Nuclear Science & Technology
Wooseok Jo, Seung Jun Lee
Summary: This study proposes a human reliability analysis methodology for start-up and shutdown operations in nuclear reactors, and uses a Bayesian belief network model for quantitative evaluation. The research validates the process and effectiveness of the proposed methodology through the study of general operating procedures, simulation-based screening analysis, and task analysis.
ANNALS OF NUCLEAR ENERGY
(2022)
Article
Engineering, Industrial
Pablo-Ramses Alonso-Martin, Ignacio Montes, Enrique Miranda
Summary: Human Reliability Analysis aims to address the hazardous consequences caused by human factors. We propose an alternative based on distortion models to quantify the influence of human factors and provide robust estimations.
Article
Engineering, Chemical
Hua Li, Xicheng Xue, Yanbin Wang, Lizhou Wu, Xinhong Li
Summary: This paper presents a convolutional neural network (CNN) methodology based on the PyTorch framework to identify unsafe behavior among lifting operation drivers in chemical plants. By collecting 22,352 images of equipment lifting operations, the behavior of lifting drivers was divided into eight categories and a ResNet50 network model was used for identification. The results show that the proposed model achieves high accuracy, recall, and F1 value. This knowledge provides a new perspective for preventing safety accidents caused by the dangerous behaviors of lifting operation drivers in the chemical industry.
Article
Engineering, Industrial
Xin Li, Yong Guo, Fan-liang Ge, Fu-qiang Yang
Summary: The hybrid approach of CREAM, fuzzy theory, and Bayesian network was used to analyze the reliability of scaffolding operators. By analyzing the characteristics of scaffolding operations, operational and cognitive subtasks were identified. A relational network of common performance conditions was determined using a Bayesian network, and fuzzy languages were transformed into conditional probabilities. The human error probabilities of the operational and cognitive subtasks were calculated, and the total human error probability of the scaffolding operation was determined using a series-parallel hybrid structure. The results showed that the total human error probability at the construction site was 4.30E-03. Scaffold dismantling and supervisory inspection had a significant impact on human error, highlighting the importance of training and education on work methods. This method provides a new approach to human reliability analysis and the safety of work at height.
Article
Engineering, Industrial
Zengkai Wang, Shengkui Zeng, Jianbin Guo, Haiyang Che
Summary: This study proposes a novel method for assessing the reliability of man-machine phased-mission systems, focusing on addressing the phase dependencies of human cognitive errors. By analyzing and categorizing the types of cognitive error dependencies and constructing system reliability models using Bayesian networks, a comprehensive assessment approach is successfully developed.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Environmental Sciences
Hui Zou, Lucy Marshall, Ashish Sharma
Summary: Understanding the origins of errors between model predictions and catchment observations is essential in hydrologic model calibration and uncertainty estimation. A new model calibration strategy called Bayesian ecohydrological error model (BEEM) is implemented, utilizing satellite metadata information to decompose data error from total residual error. The results show that BEEM is valid in a synthetic setting and improves model calibration by estimating the model error appropriately and estimating uncertainty more precisely.
WATER RESOURCES RESEARCH
(2023)
Article
Engineering, Marine
Rafi Ullah Khan, Jingbo Yin, Faluk Shair Mustafa, Siqi Wang
Summary: This study investigates the multifaceted role of human factors in hazardous cargo port accidents, revealing safety issues, bad supervision, intellectual problems, and violations as prominent factors affecting the occurrence of accidents. A sensitivity analysis was conducted to determine the most critical accident causation factors.
Article
Engineering, Industrial
Cagatay Kandemir, Metin Celik
Summary: The study proposes marine engineering maintenance and operations specific error producing conditions (mmo-EPCs) based on ship accident data, extending the current shipboard operations human reliability analysis (SOHRA). The findings introduce a new method called marine maintenance and operations human reliability analysis (MMOHRA), which significantly alters the values of various error producing conditions compared to similar approaches, demonstrating its potential for improved safety practices in the marine engineering field.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Construction & Building Technology
Zhe Sun, Zhufu Zhu, Ruoxin Xiong, Pingbo Tang, Zhansheng Liu
Summary: Prefabricated building construction involves complex lifting operations that require multiple cranes to work simultaneously. These operations create challenges for risk prognosis and control due to frequent interactions among human, cyber, and physical environments. Human errors pose challenges for resilient lifting operation control, necessitating a dynamic human systems risk prognosis and control approach. This study critically examines the opportunities and challenges in establishing this approach and provides a research roadmap for future activities in automated lifting operations.
DEVELOPMENTS IN THE BUILT ENVIRONMENT
(2023)
Article
Management
Akram Khaleghei, Michael Jong Kim
Summary: This paper presents a maintenance control model for semi-Markov processes and develops a new analysis approach to solve the partially observable semi-Markov decision problem, improving efficiency and accuracy in maintenance optimization.
OPERATIONS RESEARCH
(2021)
Article
Engineering, Industrial
Yunfei Zhao
Summary: This research proposes a Bayesian approach for comparing human reliability analysis methods, utilizing ensemble modeling to output predictions of human error probability and updating weights using Bayes' rule. The results show that posterior beliefs vary depending on the dataset used.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)