Fault Creator Cases Analysis Based on Bayesian Method in Current Permit to Work System to Optimize the Protection Layers and Risk Management, During Commissioning and Startup Phases of Gas Refinery Plant

Accident statistics indicate that the majority of accidents at four categories of human, environment, equipment, and reputation of a community have mainly occurred in the process industries. Amongst them, the Oil and Gas industries have a significant portion, as these industries handle large quantities of flammable, toxic chemicals, and exposure to the high potential of serious accidents. Having considered these issues, it is essential to execute an in place safe system of work in such industries. Permit to work system (PTWS) is one of the most important and effective key of HSEMS subsystems, which has a significant role in identifying, predicting, controlling, and eliminating hazards of activities and probable accidents at workplaces. As a question for this research, it is being used in the oil and gas industry. Currently used PTWS method at gas refineries in Pars Special Economic Energy Zone (PSEEZ) is a paperbased management system document, based on the statistical results obtained using the experiences of trustees and experts, which intrinsically contains some defects and deficiencies; consequently it could not provide sufficient and effective barriers. These inherent PTWS errors and faults as the databased permit to work system (D.B.P.T.W) are leading the operating system to different types of accidents, and finally system failures and catastrophic disasters. Therefore, in this study Bayesian theory was applied for the conditional probability of fault creator cases (FCCs) of PTWS assessment. Fault creator cases analysis in permit to work system with changes in the current PTWS were used (Current Permit to Work, C.P.T.W) in gas refineries by logical management. So that the use of this new method based on historical and interconnected and multifaceted fault factors communication and also disconformity/capability for immediate and simultaneous informing and discovering on the relevant system components and also according to a Bayesian analysis on seven important and critical variables for both CPTWS and DPTW.S for pessimist and optimist statuses may improve the protection safety layers and it is possible to decease and finally eliminate accidents as low as reasonably practicable (ALARP) level at gas refinery plants.