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Slaying the dragons that sabotage protection measures to feed on the ash of your plant
Process Safety Progress ( IF 1 ) Pub Date : 2021-05-28 , DOI: 10.1002/prs.12274
Denise Chastain‐Knight 1
Affiliation  

Dragons are legendary winged monsters that breathe fire and feed on ash. Or so we think. This is a tale of three dragons that have evolved to hide in plain sight and quietly feed on the underpinnings of protection layers, eroding the effectiveness of process safety mitigation measures. These dragons are mischievous and feed off process upsets, near misses, and accidents. The Invisible Dragon roams around the plant breaking devices and causing people to make mistakes that set off alarms and causes safety instrumented systems (SIS) trips to initiate. Its special joy is creating initiating events that were not considered in the design. Tiny and Giant Dragons specialize in defeating the SIS protection layers, so that all three dragons can feed on the ash of an accident. The Tiny Dragon baits SIS designers with devices having extremely low failure rate data causing the humans to believe safety instrumented functions (SIF) are more reliable than they actually are. The Giant Dragon works alongside the Tiny Dragon to further undermine the SIS with its song of near perfect proof testing. This paper will illustrate the impacts of underestimating SIF demand rate, using overly optimistic failure rate data, and overestimating proof test coverage. We will discuss techniques to identify and correct these issues and suggest metrics to monitor SIS performance thus slaying the dragons.

中文翻译:

杀死破坏保护措施的龙,以植物的灰烬为食

龙是传说中的有翅膀的怪物,它们会喷火并以灰烬为食。或者我们认为。这是一个关于三条龙的故事,它们已经进化到隐藏在显眼的地方,并悄悄地以保护层的基础为食,削弱了过程安全缓解措施的有效性。这些龙很调皮,以过程混乱、未遂事件和事故为食。隐形龙在植物破坏装置周围漫游,导致人们犯错误,引发警报并导致安全仪表系统 (SIS) 跳闸启动。它特别的乐趣是创造设计中没有考虑的启动事件。小龙和巨龙擅长击败 SIS 保护层,以便所有三条龙都能以事故的灰烬为食。Tiny Dragon 以具有极低故障率数据的设备引诱 SIS 设计人员,使人们相信安全仪表功能 (SIF) 比实际情况更可靠。Giant Dragon 与 Tiny Dragon 合作,以其近乎完美的证明测试之歌进一步削弱 SIS。本文将说明低估 SIF 需求率、使用过于乐观的故障率数据和高估证明测试覆盖率的影响。我们将讨论识别和纠正这些问题的技术,并提出监测 SIS 性能的指标,从而扼杀恶龙。本文将说明低估 SIF 需求率、使用过于乐观的故障率数据和高估证明测试覆盖率的影响。我们将讨论识别和纠正这些问题的技术,并提出监测 SIS 性能的指标,从而扼杀恶龙。本文将说明低估 SIF 需求率、使用过于乐观的故障率数据和高估证明测试覆盖率的影响。我们将讨论识别和纠正这些问题的技术,并提出监测 SIS 性能的指标,从而扼杀恶龙。
更新日期:2021-05-28
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