Cask Principle of Multi-Attribute Risk Assessment: Non-Weighted Maximal Approach for Production Accidents

This paper proposes a non-weighted maximal approach of multi-attribute risk assessment for production accidents, which comes from the Chinese practice of risk management rather than the theoretical weighted multi-attribute approach. The existing literature for risk assessment of pipeline accidents,...

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Bibliographic Details
Main Authors: Lei Wang, Xin Wang, Zhaowei Ding
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9454507/
Description
Summary:This paper proposes a non-weighted maximal approach of multi-attribute risk assessment for production accidents, which comes from the Chinese practice of risk management rather than the theoretical weighted multi-attribute approach. The existing literature for risk assessment of pipeline accidents, there is an absence of or lack of explicit consideration of some special dimensions, i.e., environmental pollution as the important derivative disaster. The non-weighted maximal approach is described the maximum function among multiple criteria, which include fatalities, serious injuries, direct economic loss, and environment pollutions. The approach comes from the Chinese government official achievement assessment system with the characteristics of “one ticket veto system for production safety”, and has applied to ex ante assessing likelihood of the accident, and ex post holding the responsible for accidents. At last, applying the case of the Chinese Qingdao oil pipeline accident, the maximal approach is compared with the FN curve criterion, the ALARP principle and the ELECTRE TRI method. The results show that the maximal approach of production safety accident criterion pays more attention to the risk density or risk consequences, which follows the “cask principle” and is much more useful controlling the risk when targeting the vulnerable links of engineering systems.
ISSN:2169-3536