Critical review on data-driven approaches for learning from accidents: comparative analysis and future research

Y Niu, Y Fan, X Ju - Safety science, 2024 - Elsevier
Data-driven intelligent technologies are promoting a disruptive digital transformation of
human society. Industrial accident prevention is also amid this change. Although many …

[HTML][HTML] Learning from major accidents: A machine learning approach

N Tamascelli, R Solini, N Paltrinieri… - Computers & Chemical …, 2022 - Elsevier
Learning from past mistakes is crucial to prevent the reoccurrence of accidents involving
dangerous substances. Nevertheless, historical accident data are rarely used by the …

Identification of risk features using text mining and BERT-based models: Application to an oil refinery

JB Macêdo, M das Chagas Moura, D Aichele… - Process safety and …, 2022 - Elsevier
The uncontrollable release of hazardous substances may lead to catastrophic accidents. In
this context, risk studies are aimed at recommending either preventive measures or …

Application of Bayesian network and artificial intelligence to reduce accident/incident rates in oil & gas companies

F Sattari, R Macciotta, D Kurian, L Lefsrud - Safety Science, 2021 - Elsevier
Process safety management (PSM) is a framework that demonstrates a company's
commitment to process safety, a better understanding of hazards and risks, a …

Using text mining and multilevel association rules to process and analyze incident reports in China

Y Zhu, H Liao, D Huang - Accident Analysis & Prevention, 2023 - Elsevier
Incident investigation reports provide information on defects related to the system safety and
indications for improvements. Currently, the analysis of these reports relies heavily on …

[HTML][HTML] Learning from major accidents: a meta-learning perspective

N Tamascelli, N Paltrinieri, V Cozzani - Safety science, 2023 - Elsevier
Learning from the past is essential to improve safety and reliability in the chemical industry.
In the context of Industry 4.0 and Industry 5.0, where Artificial Intelligence and IoT are …

A theoretical framework for data-driven artificial intelligence decision making for enhancing the asset integrity management system in the oil & gas sector

F Sattari, L Lefsrud, D Kurian, R Macciotta - Journal of Loss Prevention in …, 2022 - Elsevier
Asset integrity and reliability is one of the 20 elements of Process Safety Management (PSM)
as defined by the Center for Chemical Process Safety (CCPS). We combine expert …

[HTML][HTML] Extraction and classification of risk-related sentences from securities reports

M Fujii, H Sakaji, S Masuyama, H Sasaki - International Journal of …, 2022 - Elsevier
With the drastically changing business environment, it is difficult even for experts to properly
extract and classify risk statements from securities reports, which contain large volumes and …

Classification and causes identification of Chinese civil aviation incident reports

Y Jiao, J Dong, J Han, H Sun - Applied Sciences, 2022 - mdpi.com
Safety is a primary concern for the civil aviation industry. Airlines record high-frequency but
potentially low-severity unsafe events, ie, incidents, in their reports. Over the past few …

Identifying low-quality patterns in accident reports from textual data

JB Macedo, PMS Ramos, CBS Maior… - … of occupational safety …, 2023 - Taylor & Francis
Accident investigation reports provide useful knowledge to support companies to propose
preventive and mitigative measures. However, the information presented in accident report …