Analysis on Causative Factors and Evolution Paths of Blast Furnace Gas Leak Accident

Abstract

Although the interest in metallurgical accident investigation of blast furnace gas (BFG) leakage has increased to explore the engineering failures, more effort is needed to address the individual and organizational causative factors to clear and determine the weak links for improving safety management and accident prevention to achieve green metallurgical manufacturing. This study aims to examine the causative factors and evolution paths of BFG leakage by introducing a combined method, the 24 model and Bayesian network (BN), based on 50 cases of fire, explosion and suffocation accidents caused by BFG leakage. A BN model of BFG leakage was established based on the identification of 25 causative factors by the 24 model. Results showed that eight nodes, including A1 (unsafe operation), A2 (unsafe behavior), A4 (unsafe condition), B1 (valve failure), B2 (improper gas safety operation), X4 (use of BFG violates regulations), X5 (water gas is not cut off before shutdown reduction) and X6 (incomplete steam purging), were more sensitive than others, and the posterior probability of nodes A1, A2, A3 (unsafe command), A4, B1, B2, B4 (improper emergency behavior), B5 (unsafe behaviors on BFG site) increased compared to prior probability. Three main accident causal chains were obtained which indicate that control the unsafe operations (A1) related to gas (B2) and valve (B1) are suggested to be improved. Another important factor is A4 (unsafe condition), which is related to intrinsic safety conditions. Considering the results, the key points of 3E strategy about BFG leakage prevention are suggested. This study provides useful insights to understand the organizational and individual factors and their relative influence in BFG leakage accidents, which will support BFG leakage prevention and safety management.