An imprecise Fault Tree Analysis for the estimation of the Rate of OCcurrence Of Failure (ROCOF)

被引:16
作者
Curcuru, Giuseppe [1 ]
Galante, Giacomo Maria [1 ]
La Fata, Concetta Manuela [1 ]
机构
[1] Univ Palermo, Dipartimento Ingn Chim Gest Informat Meccan, I-90128 Palermo, Italy
关键词
Rate of Occurrence of Failure; Fault Tree Analysis; Initiator Events; Enabler events; Dempster-Shafer Theory; UNCERTAINTY QUANTIFICATION; COMBINATION; JUSTIFICATION; VARIABILITY; RULE;
D O I
10.1016/j.jlp.2013.07.006
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
The paper proposes an imprecise Fault Tree Analysis in order to characterize systems affected by the lack of reliability data. Differently from other research works, the paper introduces a classification of basic events into two categories, namely Initiators and Enablers. Actually, in real industrial systems some events refer to component failures or process parameter deviations from normal operating conditions (Initiators), whereas others refer to the functioning of safety barriers to be activated on demand (Enablers). As a consequence, the output parameter of interest is not the classical probability of occurrence of the top event, but its Rate of OCcurrence (ROCOF) over a stated period of time. In order to characterize the basic events, interval-valued information supplied by experts are properly aggregated and propagated to the top. To this purpose, the Dempster-Shafer Theory of evidence is proposed as a more appropriate mathematical framework than the classical probabilistic one. The proposed methodology, applied to a real industrial scenario, can be considered a helpful tool to support risk managers working in industrial plants. (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1285 / 1292
页数:8
相关论文
共 29 条
[1]  
[Anonymous], 2000, GUID CHEM PROC QUANT
[2]  
[Anonymous], 1999, 6030039 IEC
[3]  
[Anonymous], 1999, 61508 IEC
[4]   An approximation approach for uncertainty quantification using evidence theory [J].
Bae, HR ;
Grandhi, RV ;
Canfield, RA .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2004, 86 (03) :215-225
[5]   Uncertainty quantification of structural response using evidence theory [J].
Bae, HR ;
Grandhi, RV ;
Canfield, RA .
AIAA JOURNAL, 2003, 41 (10) :2062-2068
[6]  
Curcuru G., 2012, P PSAM11 ESREL 2012
[7]   Epistemic uncertainty in fault tree analysis approached by the evidence theory [J].
Curcuru, Giuseppe ;
Galante, Giacomo Maria ;
La Fata, Concetta Manuela .
JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES, 2012, 25 (04) :667-676
[8]  
Dubois D., 1986, INT J INTELL SYST, V1, P133
[9]   Handling and updating uncertain information in bow-tie analysis [J].
Ferdous, Refaul ;
Khan, Faisal ;
Sadiq, Rehan ;
Amyotte, Paul ;
Veitch, Brian .
JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES, 2012, 25 (01) :8-19
[10]   Methodology for computer aided fuzzy fault tree analysis [J].
Ferdous, Refaul ;
Khan, Faisal ;
Veitch, Brian ;
Amyotte, Paul R. .
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION, 2009, 87 (04) :217-226