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Towards a safety case for runtime risk and uncertainty management in safety-critical systems

机译:建立安全关键系统中运行时风险和不确定性管理的安全案例

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Many safety-critical systems have a human-in-the-loop for some part of their operation, and rely on the higher cognitive abilities of the human operator for fault diagnosis and risk-management decision-making. Although these operators are often experts on the processes being controlled, they still sometimes misjudge situations or make poor decisions. There is thus potential for Safety Decision Support Systems (SDSS) to help operators, building on past successes with Clinical Decision Support Systems in the health care industry. Such SDSS could help operators more accurately assess the system's state along with any associated risk and uncertainty. However, such a system supporting a safety critical operation inevitably attracts its own safety assurance obligations. This paper will outline those challenges and suggest an initial safety case architecture for SDSS.
机译:许多对安全至关重要的系统在其某些部分的运行中都处于“人为循环”状态,并且依赖于操作员的更高认知能力来进行故障诊断和风险管理决策。尽管这些操作员通常是受控过程的专家,但他们有时仍会误判情况或做出错误的决定。因此,安全决策支持系统(SDSS)可以在医疗行业的临床决策支持系统的成功基础上,帮助运营商。这种SDSS可以帮助运营商更准确地评估系统状态以及任何相关的风险和不确定性。但是,这种支持安全关键操作的系统不可避免地要承担其自身的安全保证义务。本文将概述这些挑战,并提出SDSS的初始安全案例架构。

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