(0a) Dynamic Process Safety Management System in the Prevention of Tank Overfill: A Case Study

Process safety is a critical concern for all industries, as they are consistently engaged in efforts to reduce and manage operational risks. Traditional risk analysis methods are widely used in process safety management but often produce static outputs, mainly printed documents, that may become scattered and outdated. This study addresses this limitation by implementing a dynamic process safety management system that integrates classical methods with a dynamic risk level assessment to manage the risk of overfill in a naphtha storage tank at a midstream facility. Developed using the Python-based Django framework, the system features an interactive front-end platform where the tank’s bowtie (BT) diagram was built. The platform also guides through layer of protection/mitigation analysis (LOPA/LOMA) based on a predefined set of threats, consequences, and barriers. The system back-end, on the other hand, periodically runs an algorithm that collects real-time corporate and automation data related to controls, such as critical alarms, performance indicators, and operational checklists of the tank. In line with the hierarchy of risk control, each barrier reduces the risk in some level, which may be changed every new collected data brought by the algorithm execution, ensuring up-to-date assessments. Thus, the user can visualize the current overfill risk level and evaluate the effectiveness of the existing safety controls. Therefore, the proposed system helps process safety professionals and managers identify weaknesses in the safety barriers control of a storage tank, providing accurate and updated data to support effective risk management and decision-making strategies.