An integrated human reliability based decision pool generating and decision making method for power supply system in LNG terminal

- Extending the original CREAM from a simply HRA method to a method which can generate a pool of plans for safety promotion.
- The target fuzzy membership degrees of human control modes are identified by GA optimization.
- Providing a mathematical and logical way to construct a standard and robust model for decision making to improve the safety.

In this paper, an integrated model is presented to support human reliability based decision producing and making process by evaluating safety promotion plan for power supply system in LNG (Liquid Natural Gas) terminal. This model is mainly mathematically treated through fuzzy Cognitive Reliability and Error Analysis Method (CREAM) in combination with Genetic Algorithms (GA) and Adaptive Neuro-Fuzzy Inference System (ANFIS). The fuzzy CREAM accounts the operators' individual factors, organization factors, environmental factors and technique factors together to identify the fuzzy membership degree of each control mode and to calculate Human Error Probability (HEP). However, when the calculated HEP fails to meet the requirement, the GA will identify the target membership degree of each CREAM control mode, and adopting such target membership degree and fuzzy logic rule to generate a decision pool for safety promotion. Finally, an experts' evaluation result based ANFIS provides a standard evaluating system for plan choice and update. The proposed model has been tested on a power supply system for an LNG terminal in Beihai China.