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Automated Generation of Fault Scenarios to Assess Potential Human Errors and Functional Failures in Early Design Stages

机译:自动生成故障方案,以评估早期设计阶段的潜在人的错误和功能故障

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摘要

Human errors are attributed to a majority of accidents and malfunctions in complex engineered systems. The human error and functional failure reasoning (HEFFR) framework was developed to assess potential functional failures, human errors, and their propagation paths during early design stages so that more reliable systems with improved performance and safety can be designed. In order to perform a comprehensive analysis using this framework, a wide array of potential failure scenarios need to be tested. Coming up with such use cases that can cover a majority of faults can be challenging for engineers. This research aims overcome this limitation by creating a use case generation technique that covers both component- and human-related fault scenarios. The proposed technique is a time-based simulation that employs a modified depth first search (DFS) to simulate events as the event propagation is analyzed using HEFFR at each time-step. The results show that the proposed approach is capable of generating a wide variety of fault scenarios involving humans and components. Out of the 15.4 million scenarios that were found to violate the critical function, two had purely human-induced faults, 163,204 had purely non-human-induced faults, and the rest had a combination of both. The results also show that the framework was able to uncover hard-to-detect scenarios such as scenarios with human errors that do not propagate to affect the system. In fact, 86% of all human action combinations with nominal human-induced component behaviors had underlying human errors.
机译:人类错误归因于复杂的工程系统中的大多数事故和故障。开发了人为错误和功能故障推理(HEFFFR)框架以评估早期设计阶段的潜在功能故障,人类错误及其传播路径,以便设计具有更高性能和安全性的更可靠的系统。为了使用此框架进行全面的分析,需要测试各种潜在的故障情景。随着可以覆盖大部分故障的这种用例,可以对工程师挑战。该研究目的是通过创建涵盖组件和人类相关的故障场景的用例生成技术来克服这种限制。所提出的技术是一种基于时间的模拟,该模拟采用修改的深度第一搜索(DFS)来模拟事件,因为在每个时间步骤使用Heffr分析事件传播。结果表明,该方法能够产生各种涉及人类和组件的故障情景。在被发现违反临界功能的1540万场景中,两种纯粹是人类诱导的错,163,204件纯粹是非人诱导的故障,其余部分都有两者。结果还表明,该框架能够揭示难以检测的场景,例如具有不传播影响系统的人为错误的情况。事实上,86%的所有人类行动组合具有标称人类诱导的组分行为的潜在人类错误。

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