@article{ref1,
title="Optimization of multi-level safety information cognition (SIC): a new approach to reducing the systematic safety risk",
journal="Reliability engineering and system safety",
year="2019",
author="Lei, Yu and Wu, Chao and Feng, Yanxi and Wang, Bing",
volume="190",
number="",
pages="e106497-e106497",
abstract="All systems can be associated with and expressed by information. For a normal system, the correct and smooth information exchange is the necessary condition of a safe system. Based on this, we can deduce that safety information which flows correctly and smoothly in a system is very important for safety. Therefore, the aims of this paper are to reduce the Safety Information Cognition (SIC) asymmetry and the safety risk in a system. Firstly, the process of multi-level SIC was innovatively analyzed from the perspective of the flow structure according to the Bayesian network. Secondly, some strategies and a model for the SIC optimization were creatively proposed based on the graph theory. Finally, the application of the optimization model was illustrated with an example. The optimization effect can be obtained by quantitatively comparing the safety information amount between before and after optimization, and the practical result proves that the optimization model works. In general, the optimization model can optimize the transmission routes of safety information and reduce safety information distortion. Our work can provide a new and effective method to improve the information transmission efficiency of multi-level SIC. It can be applied to safety management to reduce the systematic risk in a certain sense.<p /> <p>Language: en</p>",
language="en",
issn="0951-8320",
doi="10.1016/j.ress.2019.106497",
url="http://dx.doi.org/10.1016/j.ress.2019.106497"
}