Architecture of Hybrid Decision Support Sytem for Risk Management of Offshore Platforms

海上平台的风险管理要求实时调整程序以适应现有条件。这些情况可能是由环境因素(例如风暴或冰)、船上事故(例如火灾)、船只相撞或平台或其能力的退化(例如腐蚀)引起的。在有风险的情况下，操作员通常遵循预先设计的程序，但在程序的设计中可能没有预见到某些特定情况。有经验的操作员通常可以估计类似于他以前经历的情况的严重程度，并采取适当的措施。然而，在某些情况下，在采取适当行动之前，需要更多地了解当前的风险情况、这种情况的潜在恶化情况、适用的程序和替代选择。本研究的目的是将分析方法(基于系统分析的概率风险评估)和人工智能(基于经验丰富的操作员建议和操作/应急程序的专家系统)的力量结合在一个用于船上平台风险管理的混合实时决策支持系统中。一个关键的理论问题是这两类信息的聚合。将开发一个原型。这个原型的一个可能的选择是，当天气条件使延迟和立即维护都变得危险时，解决冗余平台的安全管理问题。

Risk management on offshore platforms requires real-time adaptation of procedures to existing conditions. These conditions can be caused either by environmental factors(e.g., storms or ice), on-board incidents(e.g., a fire), boat collisions, or degradation of the platform or its capacity(e.g., by corrosion.) In situations of risk, the operators generally follow procedures that have been predesigned, but some specific circumstances may not have been foreseen in the design of the procedures. An experienced operator can generally estimate the severity of a situation similar to one he has experienced previously and take appropriate measures. In some instances, however, more information is needed about the current risk situation, potential deterioration of this condition, applicable procedures, and alternative options before appropriate actions can be taken. The object of this research is to combine the powers of analytical methods (probabilistic risk assessment based on systems analysis) and artificial intelligence (expert systems based on recommendations of experienced operators and on operating/emergency procedures) in a hybrid real-time decision support system for risk management on board platforms. A key theoretical issue is the aggregation of these two types of information. A prototype will be developed. One possible option for this prototype is to address the problem of safety management for a redundant platform when the weather conditions make both delayed and immediate maintenance hazardous.