An incremental fuzzy approach to risk-based evaluation of process equipment isolation schemes

Any time that process equipment needs to be out of service for inspection, maintenance, cleaning, or repair, sufficient isolation should be applied to isolate the equipment from the hazardous energies. Opting and implementing a proper scheme to isolate such equipment is critical to prevent accidents in process plants. Conventional risk-based methods to determine the isolation schemes are not so effective in dealing with subjective errors and uncertainties. Therefore, in this study we have developed an incremental fuzzy system to cope with the aforesaid limitations of conventional risk-based methods. In the proposed model, a numerical technique is applied for developing membership functions to reduce the uncertainty. In the incremental fuzzy model, three fuzzy inference systems in three levels are generated to calculate a release factor, outcome factor, and isolation level. Applying the proposed model to a three-phase separator, the results of the proposed model were compared with those of a conventional risk-based method, demonstrating that the proposed model can effectively handle the uncertainty while keeping the simplicity of the conventional approaches. The results are more transparent, detailed, and thus of greater value in identifying isolation schemes. Therefore, the proposed model can be an effective alternative to the conventional methods currently used in process plants for determination of isolation schemes.