INTEGRATING KNOWLEDGE-BASED AND MATHEMATICAL-PROGRAMMING APPROACHES FOR PROCESS SAFETY VERIFICATION

Hazard and Operability analysis (HAZOP) is a popular method for perfor ming hazards analysis of chemical plants. It is labour- and knowledge- intensive and could benefit from automation. Recently, a knowledge bas ed framework for automating HAZOP analysis, called HAZOPExpert, was pr oposed. Dimitriadis et al. (1995) proposed a quantitative model based approach for hazard evaluation. This approach used a dynamic model of the plant and bounds on the process disturbances (including failure mo des) and parameters to identify possible unsafe situations. The qualit ative analysis performed by HAZOPExpert is thorough and computationall y efficient. However, in some situations it suffers from ambiguity. Th e quantitative analysis has the capability to perform an exact analysi s without ambiguities, but a complete quantitative analysis can be com putationally prohibitive. In this paper, we present an integrated qual itative-quantitative approach for hazard identification and evaluation which overcomes the shortcomings of qualitative and quantitative meth ods. In the integrated framework, the broad details of a particular ha zardous scenario are extracted by inexpensive qualitative analyses. A detailed quantitative analysis is then performed if needed and only on those parts of the plant identified by the qualitative analysis to co ntribute to the hazard. This framework is illustrated using an industr ial case study.