A Supportive Framework for Collaborative Implementation of Quantitative Risk Analysis in the Hazardous Process Industry and Application to Natural Gas Plant

摘要

Quantitative Risk Analysis (QRA) in the hazardous process industry has been utilized by national safety organizations and business operators as a very valuable tool for obtaining numerical estimates of risk effectively. However, QRA has a complex and difficult analysis process, and this sets a limitation on the implementation of the risk management principles, that is, participation and communication of various stakeholders on the overall risk analysis stages repetitively. In addition, QRA requires a long period of analysis time, and this makes it even more difficult to be used as a prompt decision-making tool in changes of safety policies and external environment. Therefore, this paper suggests an analysis framework that supports a collaborative QRA to overcome such limitations and a quantitative risk management process model based thereon. This is based on the analysis pivot named ARHSP (Accidental Release Hazard Scenario Point), and ARHSP is characterized by the sharing of information and execution of co-operative work for quantifying the risk. In other words, ARHSP is a well-organized risk analysis unit that is set by experts in a way that analytical information can be reviewed and entered by internal stakeholders such as safety managers in the case of necessity, which makes division of work (cooperation) possible. Furthermore, the framework proposed in this paper is applied to the QRA system development of KOGAS, which is one of the largest LNG importers. Further, the effectiveness is validated by showing that relevant parties apply it to perform QRA collaboratively for three large LNG import terminals in a short-period compared to the time expected in a conventional way. Ultimately, this study demonstrates a practical framework to which organizations or enterprises can refer when they want to establish a relevant method or develop a system for activating efficient QRA application.