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How can we use the information provided by process safety performance indicators? Possibilities and limitations

机译:我们如何使用流程安全性能指标提供的信息?可能性和限制

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To make further progress towards a safer industry, process safety performance indicators are indispensable. There are, however, some challenges involved with interpretation of indicator outcomes. By going too far in detail one loses overview, but in not noticing the important detail a false impression of safety may be obtained. Aggregation from a detailed level upward may give relief at this point, but what to do if indicator values do not improve any further? Is there a means to relate indicators to the plant's risk level? The paper will show that when making use of the new technique of Bayesian networks for risk management, progress may be made. It seems possible to relate technical failure rates with risk factors acting over time duration and to take action before something breaks down. While originating in bad design, operation, maintenance, or neglect, these risk factors are influenced in the background by organizational, management, and human factors, which are subject to indicator monitoring. An example will be given of results one can expect when the dependencies are modeled in Bayesian network fashion. Current developments in other areas such as in aviation and offshore platform maintenance appear to be advancing in the same direction.
机译:为了进一步进步走向更安全的行业,流程安全性能指标是必不可少的。然而,有些挑战涉及指标结果的解释。通过详细走得太远,一个丢失概述,但在没有注意到的重要细节可以获得安全的虚假印象。从详细的水平向上的聚合可能会在这一点上释放,但如果指标值没有进一步改善,该怎么办?是否有一种方法可以将指标与工厂的风险水平联系起来?本文将显示,在利用贝叶斯网络的新技术时,可以进行进度。似乎有可能将技术失败利率与危险因素相提并论,在休息时采取行动。虽然源于不良的设计,操作,维护或忽视,但这些风险因素受到组织,管理和人为因素的影响,这些因素受到指标监测的影响。将给出一个例子,结果可以在依赖关系以贝叶斯网络方式建模时。其他领域的当前发展如航空和海上平台维护似乎在同一方向上推进。

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