首页> 外文期刊>Open Journal of Safety Science and Technology >Developing a Risk-Based Approach for Optimizing Human Reliability Assessment in an Offshore Operation
【24h】

Developing a Risk-Based Approach for Optimizing Human Reliability Assessment in an Offshore Operation

机译:开发一种基于风险的方法来优化海上作业中的人员可靠性评估

获取原文
           

摘要

Human error plays a pivotal rule in all aspects of engineering activities such as operation, maintenance, design, inspection and installation. Industries are faced up to various significant human errors and consequently irrecoverable loss each year, but still there is a lack of heeds to qualify as well as quantify such errors. This paper tries to estimate the probability of failure in lifting of light structures in sea by considering human errors. To do this, a strong qualifying tool such as Functional Resonance Analysis Method (FRAM) is applied to develop high risk accident scenario by considering non-linear socio-technical interaction in system. Afterwards, human error probability is calculated for each activity using the Success Likelihood Index Method (SLIM) based on resonance that is carried out in FRAM network. Then Event Tree (ET) is conducted to assess consequences. The present study is aimed to interpret the importance of attentions to qualitative methods in implementing quantitative risk analyses to consider human error in calculation. The final outcome depicts that considering human error in the process of risk assessment will result in more accuracy and reliability in final Risk Probability Number (RPN). The developed methodology has been applied to a case study of an offshore installation.
机译:人为错误在工程活动的各个方面(例如操作,维护,设计,检查和安装)起着至关重要的作用。行业每年都面临着各种重大的人为错误,因此每年都将蒙受不可挽回的损失,但是仍然缺乏注意来量化和量化此类错误。本文试图通过考虑人为错误来估计海上轻型结构举升失败的可能性。为此,通过考虑系统中的非线性社会技术互动,应用了功能强大的鉴定工具(例如功能共振分析方法(FRAM))来开发高风险事故场景。然后,根据在FRAM网络中执行的共振,使用成功可能性指数方法(SLIM)为每个活动计算人为错误概率。然后进行事件树(ET)评估后果。本研究旨在解释在执行定量风险分析时要考虑定性方法的重要性,以在计算中考虑人为错误。最终结果表明,在风险评估过程中考虑人为错误将导致最终风险概率编号(RPN)的准确性和可靠性更高。所开发的方法已应用于海上设施的案例研究。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号