Login / Signup

A chemical accident cause text mining method based on improved accident triangle.

Zheng LiMin YaoZhenmin LuoXinping WangTongshuang LiuQianrui HuangChang Su
Published in: BMC public health (2024)
The results show that reducing unit-level accidents can prevent group-level accidents. The accidents of the sample enterprises are mainly personal injury accidents, production accidents, environmental pollution accidents, and quality accidents. The leading causes of personal injury accidents are employees' unsafe behaviors, such as poor safety awareness, non-standard operation, illegal operation, untimely communication, etc. The leading causes of production accidents, environmental pollution accidents, and quality accidents include the unsafe state of materials, such as equipment damage, pipeline leakage, short-circuiting, excessive fluctuation of process parameters, etc. CONCLUSION: Compared with the traditional accident classification method, the accident triangle proposed in this paper based on the organizational level dramatically reduces the differences between accidents, helps enterprises quickly identify risk factors, and prevents accidents. This method can effectively prevent accidents and provide helpful guidance for the safety management of chemical enterprises.
Keyphrases
  • risk factors
  • risk assessment
  • machine learning
  • oxidative stress
  • human health
  • particulate matter
  • air pollution
  • mouse model
  • quality improvement
  • data analysis