Knowledge-based expert system framework to conduct offshore process HAZOP study

被引:0
|
作者
Khan, FI [1 ]
机构
[1] Mem Univ Newfoundland, Fac Engn & Appl Sci, St John, NF A1B 3X5, Canada
关键词
HAZOP; expert system; safety; qualitative risk assessment; offshore process operation;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
HAZOP has stood the test of time as an essential step in risk assessment, yet HAZOP suffers from serious drawbacks, which include: i) requirement of large expert team, ii) team must be multi-disciplinary and must have extensive knowledge of the design, operation, and maintenance aspects of the process plant, iii) the requirement of highly paid manpower for fairly large number of man-days makes HAZOP very expensive, and iv) a large number of likely deviations from normal are of routine nature yet the HAZOP team has to consider and study each one of them. This makes the team's task rather tedious. At the same time the team can't overlook or bypass any of the large number of routine causes as each has the potential to cause an accident. A knowledge-based expert system framework is proposed for automating HAZOP studies for offshore process facilities. The framework is aimed to enable HAZOP studies at significantly lesser costs and with better accuracy than conventional HAZOP studies. By facilitating automation of HAZOP, it is expected to contribute towards improvement in the study efficacy and more significantly, risk minimization of the process facilities.
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页码:2274 / 2280
页数:7
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