Abstract:
The main challenge for any insurer/reinsurer has proved to be underwriting major refinery/Petrochemical risk. Insurers have already considered process risk management measures while accepting and evaluating the risks all over the world. Erstwhile petrochemical tariff was adopting experiencing methodology as basis for premium calculation in Iran. In the present de-tariff scenario decisions will be crucial for underwriters on accepting the risk and deciding the terms and conditions. On the other hand the insured will be looking for merit based rating instead of general market driven premium calculations. Generalizing the risks based on the type of occupancy or the past experience also won’t do well either to the insured or to the insurer. Chemical process quantitative risk analysis (CPQRA) is a methodology designed to provide management with a tool to help evaluate overall process safety in the chemical process industry (CPI). Management systems such as engineering codes, checklists and process safety management (PSM) provide layers of protection against accidents. However, the potential for serious incidents cannot be totally eliminated. CPQRA provides a quantitative method to evaluate risk and to identify areas of cost-effective risk reduction. This method can be used as an effective tool in the entire gamut of underwriting of petrochemical risks in case of property insurance. One of the most important issues in insurance companies, is the making the wise decision on insurance risk. Insurers to cover risks in the process of motivation and a desire to identify and eliminate condition s that risk. Premiums payable by the insurer that the insurance will be commensurate with risk. Insurers attempt to identify and reduce risk plays an important role in increasing safety in the community. One major concern to insurers or reinsurers is whether to accept the risk of petrochemical refineries, and the tariffs and conditions commensurate with the identified risks. Insurers always seek ways to reduce risk insured. The present paper introduces the effective process of risk analysis that can be applied by the Insurance companies in order to identify and predict this kind risks
Machine summary:
BLEVE and projectile models are primarily empirical (AIChE/ CCPS,1989,1994,1995) Pool fire modeling is well developed, Detailed reviews and suggested formulas are provided (AIChE/CCPS, 1988a, 1989, 1995) Moreover, extensive research has been done on risk management in Iran , that includes different issues such as Risk management for project man agers (Najafi, 2004), Risk analysis in selecting and developing suppliers (Rugh an yan , 2006), in tr oducin g r isk management systems ,including case study in the aviation industry (Office of Safety and Technology, Depar t men t of Tr an spor tat ion , Dep ar tm en t of Technology Education and Research, 2007) and thesis such as model based on risk analysis in dam projects an d hydro power plan ts(Soh rabi, 2006), etc.
S p e c i f i c re sea rch ob ject ives 9To provide a systematic risk assessment process to better insure 9To provide a new model for risk analysis and decision on acceptance or rejection of risk by insurers (the combination of fire detection and explosion and risk analysis methodologies Insurance) RESEARCH METHOD P e tro c h e mi ca l I n sta lla tio n s The use of Insurance Risk Surveys and PML/EML (Estimate maximum loss) calculation is now a generally accepted practice in the Onshore Energy Sector.
According to the arrangement of equipment at intervals and the percentage of damage, Effective distance shows with circles with different colors (figure7), amount of loss is measured and probability maximum of loss estimated (PML) (table5).