| Abstract: | Chains of accidents (the domino effect) have been occurring with ever increasing frequency in chemical process industries. This is reflected in several accidents ‘J Loss Prevent Process Ind 12 (1999a) 361’; the world's worst industrial accident of the 1990s — the Vishakhpatnam disaster — also involved the domino effect ‘J Loss Prevent Process Ind 12 (1999a) 361; and Process Safety Prog 18 (1999b) 135’. Such chains of accidents have a greater propensity to cause damage than stand-alone accidents ‘Process Safety Prog 17(2) (1998a) 107; and J Loss Prevent Process Ind 12 (1999a) 361’.In order to assess the likelihood of occurrence of the domino effect and its damage potential, use of deterministic models in conjunction with probabilistic analysis is required. Recently we have proposed a systematic methodology called ‘domino effect analysis’ (DEA). A computer-automated tool, DOMIFFECT, has also been developed by us based on DEA ‘Process Safety Prog 17(2) (1998a) 107; Environment Model Software 13 (1998b) 163; and Risk assessment in chemical process industries: advanced techniques. Discovery Publishing House (1998c)’.This paper illustrates the application of DEA and DOMIFFECT to an industrial complex comprising 16 different industries. Out of 12 credible accident scenarios envisaged in three different industries — namely Madras Refineries Limited (MRL), UB Petrochemicals (UBP) and Indian Organic Chemicals Limited (IOCL), eight scenarios are likely to cause the domino effect. A further detailed analysis reveals that accidents in the storage of liquified petroleum gas and propylene and in the reflux drum units of MRL may cause domino effects. Similarly, propylene storage of UBP and monoethylene glycol storage of IOCL are also likely to cause domino effects. The impact of various chains of accidents has been forecast which reveals that in several cases the accidents may be catastrophic, harming the entire industrial complex of 16 industries. The study leads to the identification of ‘hot spots’ — units that pose the greatest risk — in turn forewarning the industries concerned and enabling them to prioritize and augment accident-prevention steps. |
