Accident Analysis Using Fault Tree Analysis: A Case Study of AB Specialty Silicones

Document Type : SEMIT 2024

Authors

1 Health and safety department, Shahid beheshti university of medical sciences, Tehran, Iran

2 Univesity of science and culture,Tehran, Iran

Abstract

Since the Industrial Revolution, industrial production processes have become increasingly complex, involving far more than just simple raw materials. The interaction of two or more incompatible substances can lead to severe consequences, including significant financial losses, environmental damage, and human injuries. Notably, while nearly all industries rely on a wide range of materials, many potential reactions within these processes remain poorly understood. A striking example is the 2019 incident at AB Specialty Silicones, which resulted in considerable human and financial losses. Fortunately, tools and techniques, such as fault tree analysis (FTA), can predict such events effectively.
In this research, we utilized the FTA method to identify the root causes of this accident, focusing on factors that would not have occurred if they had not been combined. By examining the key elements that directly contributed to the incident, we emphasize that proper control of these factors could have prevented it. Industrial accidents not only cause damage to organizations but also significantly impact safety culture and worker morale. To prevent such incidents, risk assessments must be complemented by learning from the experiences of other organizations. This dual approach acts as a shield, enabling companies to manage and control accidents more effectively.
Many studies primarily focus on the statistical analysis of accidents, often overlooking their root causes. This paper aims to address that gap by identifying and analyzing the dimensions of the incident to uncover its underlying factors.
It is worth noting that, to date, no specific research has been conducted on the analysis and investigation of incidents in the silicone industry. The results of our research could serve as a foundation for further studies in this field.

Keywords

References

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Journal of Optimization and Supply Chain Management
Volume 1, Issue 2
December 2024
Pages 120-132

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