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Bayesian analysis improves functional safety

机译:贝叶斯分析提高了功能性安全性

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Functional safety engineers follow the ISA/IEC 61511 standard and perform calculations based on random hardware failures. These result in very low failure probabilities, which are then combined with similarly low failure probabilities for other safety layers, to show that the overall probability of an accident is extremely low (e.g., 1E-5/yr). Unfortunately, such numbers are based on frequentist assumptions and cannot be proven. However, looking at actual accidents caused by control and safety system failures shows that accidents are not caused by random hardware failures. Accidents are typically the result of steady and slow normalization of deviation (a.k.a. drift). Although it is up to management to control these factors, Bayes' theorem can be used to update our prior belief (the initial calculated failure probability) based on observing other evidence--such as the effectiveness of the facility's process safety management process. The results can be dramatic.
机译:功能性安全工程师遵循ISA / IEC 61511标准,并根据随机硬件故障执行计算。 这些导致的失效概率非常低,然后将其与其他安全层的类似低故障概率组合,表明事故的总体概率极低(例如,1E-5 / YR)。 不幸的是,这些数字基于频繁的假设,并且无法被证明。 然而,看着由控制和安全系统故障引起的实际事故表明,事故不是由随机硬件故障引起的。 事故通常是偏离和偏差率稳定(A.K.A.漂移)的结果。 虽然管理层来控制这些因素,但是,贝叶斯定理可用于基于观察其他证据 - 例如设施过程安全管理进程的有效性来更新我们的先前信仰(初始计算的失败概率)。 结果可能是戏剧性的。

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    《InTech 》 |2020年第2期| 共6页
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