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Abstract

A methodology has been developed to conduct probabilistic fault tree analysis during risk assessment in chemical process industries. The methodology is based on a system involving (a) development of fault tree, (b) determination of minimum cutsets or shortest pathways leading from initiating events (malfunctioning) to the top event (the major accident), (c) probability analysis, and (d) working out improvement index values. To this end techniques of Boolean algebra, structure moduling, analytical method of cutsets finding (top-to-bottom algorithm), Monte-Carlo simulation, optimization technique and fuzzy probability set have been used.

We named the methodology Analytical -Simulation Methodology (ASM) and we developed a software package PROFAT (PRObabilistic fault tree analysis) to facilitate the use of the methodology in a rapid and eflective, yet user-friendly manner. PROFAT enables the user to find out, in an industry, (i) initiating events which may eventually lead to a major accideizt, (ii) shortest routes (minimum cutsets) a series of initiating events may take place while aiding each other in causing the accideizt. (iii) the probabilities of occurrence of such initintirig events, (iv) relative contributiom of each of the initiating events and, finally, (v) identfiing initiating events with the greatest potential to cause the top event (major accident) so that accident prevention strategies aud emergency preparedness plans can be focused on them.

The noteworthy attributes of the system are: resilience towards lack of precision in the basic data, swift processing with moderate requirements of computation cupacity (sophistication of computers needed), ease of use, and direct1y utiliz-able output. The applicability of PROFAT has been denionstrated with a case study of a sulfolane manufacturing unit.