Development of a computer-aided fault tree synthesis methodology for quantitative risk analysis in the chemical process industry

There has been growing public concern regarding the threat to people andenvironment from industrial activities, thus more rigorous regulations. The investigationof almost all the major accidents shows that we could have avoided those tragedies witheffective risk analysis and safety management programs. High-quality risk analysis isabsolutely necessary for sustainable development.As a powerful and systematic tool, fault tree analysis (FTA) has been adapted tothe particular need of chemical process quantitative risk analysis (CPQRA) and foundgreat applications. However, the application of FTA in the chemical process industry(CPI) is limited. One major barrier is the manual synthesis of fault trees. It requires athorough understanding of the process and is vulnerable to individual subjectivity. Thequality of FTA can be highly subjective and variable.The availability of a computer-based FTA methodology will greatly benefit theCPI. The primary objective of this research is to develop a computer-aided fault treesynthesis methodology for CPQRA. The central idea is to capture the cause-and-effectlogic around each item of equipment directly into mini fault trees. Special fault treemodels have been developed to manage special features. Fault trees created by thismethod are expected to be concise. A prototype computer program is provided toillustrate the methodology. Ideally, FTA can be standardized through a computerpackage that reads information contained in process block diagrams and providesautomatic aids to assist engineers in generating and analyzing fault trees.Another important issue with regard to QRA is the large uncertainty associatedwith available failure rate data. In the CPI, the ranges of failure rates observed could bequite wide. Traditional reliability studies using point values of failure rates may result inmisleading conclusions. This dissertation discusses the uncertainty with failure rate dataand proposes a procedure to deal with data uncertainty in determining safety integritylevel (SIL) for a safety instrumented system (SIS). Efforts must be carried out to obtainmore accurate values of those data that might actually impact the estimation of SIL. Thisprocedure guides process hazard analysts toward a more accurate SIL estimation andavoids misleading results due to data uncertainty.