Risk analysis of urea manufacturing plant using fuzzy logic approach

The potential hazard element of chemical process industries has become severe with technological developments over the past few years. Fertilizer industries like the urea industry deal with highly toxic components in nature, causing severe consequences. This paper implements the fuzzy lambda-tau (λ-τ) approach with the Petri net (PN) model on a urea manufacturing plant. The PN model helps to reduce the complexity of the problem, whereas fuzzy logic helps to deal with the uncertainty and vagueness of data. The urea plant has been divided into three major units, that is, the reacting unit (RU), purifying unit (PU), and concentrating unit (CU). The different reliability parameters, such as failure rate, repair time, reliability, and mean time between failures (MTBF), are determined for all these units with different spread rates (±15%, ±25%, and ±35%). A significant change of around 75% and 9% was observed for overall repair time and MTBF, respectively, for a ±35% spread rate. The reliability parameters are found as a function of the square of the spread rate. These studies suggest that the PU of the urea plant is the most vulnerable one and thus requires timely maintenance to avoid any accidents in the future. Furthermore, a detailed qualitative study is done utilizing failure mode and effect analysis (FMEA) to outline the numerous failure causes in order to enhance the system's availability and maintainability. The limitations of conventional FMEA are addressed in this study by obtaining fuzzy RPN values after application of the fuzzy FMEA technique. On comparison of the RPN and FRPN values, the FRPN values are found to be more reliable while prioritizing the failure causes in process industries.