A methodology for modeling operator errors of commission in probabilistic risk assessment
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Cited by (46)
Effects of digitalization of nuclear power plant control rooms on human reliability analysis – A review
2020, Reliability Engineering and System SafetySystematic review of human and organizational risks for probabilistic risk analysis in high-rise buildings
2019, Reliability Engineering and System SafetyCitation Excerpt :This framework classifies unsafe acts into two types of activities: errors, which he defines as unintended actions; and violations, which are intended actions. Macwan and Mosleh [95] introduced another cognitive error framework that provides reference models to categorize human error. The human reliability analyses suggest error identification through task analyses and influence diagrams in the context of specific accident or risk scenarios, utilizing performance shaping factors that influence risk outcomes.
Investigating a homogeneous culture for operating personnel working in domestic nuclear power plants
2016, Reliability Engineering and System SafetyCitation Excerpt :However, it is still careful for HRA practitioners to directly employ information from existing HRA databases because of the absence of two underlying PSFs: organization and social aspect. For example, detailed PSFs belonging to the organization category (such as team cohesion and communication characteristics) are significant for understanding the performance of operating personnel working in NPPs [25,29,33,36,43]. At the same time, these PSFs affect others as shown in existing studies where significant interrelations among team cohesion, communication characteristics, and workload have been demonstrated [10,44,52,53].
Phoenix - A model-based Human Reliability Analysis methodology: Qualitative Analysis Procedure
2016, Reliability Engineering and System SafetyCitation Excerpt :The development of the second generation HRA methods has taken place mostly along two parallel tracks. One track attempts to enhance the quality of HRA analysis within the “classical” framework of PRA [7,8]. The other track reflects the belief that substantive improvement in HRA for PRA applications requires structural changes to the PRA methodology, moving from the static, hardware-driven view of the world to a more flexible dynamic model of accident scenarios.
Investigating the appropriateness of a decision chart to characterize the level of task descriptions in nuclear power plants
2013, Progress in Nuclear EnergyCitation Excerpt :From the point of view of managing large process control systems, these benefits are essential because one of the dominant factors affecting their operational safety has been known as human performance related problems (e.g., human error) (Frostenson, 1995; HSE, 2005; Pyy et al., 2001; Taylor, 2000). In other words, if procedures are effective for enhancing the performance of human operators, then the provision of good procedures will be a practical way to reduce the risk of large process control systems (Brito, 2002; Dien et al., 1992; Hattermer-Apostel, 2001; Macwan and Mosleh, 1994; Salminen and Tallberg, 1996; Wieringa and Farkas, 1991). Actually, Degani et al. (1999) articulated this expectation by advocating such that: “In complex human-machine systems, successful operations depend on an elaborate set of procedures provided to the human operators.
Human and organizational error data challenges in complex, large-scale systems
2009, Safety ScienceCitation Excerpt :Examples of perceptual errors include failures to recognize dangerous situations, or approaches to dangerous situations; failures to recognize patterns of events that could lead to failures; or a lack of awareness of surroundings, situations or behavior that could led to adverse events. Cognitive error frameworks provide reference models to categorize human error; in addition, human reliability analyses suggest error identification through task analyses and influence diagrams in the context of specific accident or risk scenarios, utilizing performance shaping factors that influence risk outcomes (Macwan and Mosleh, 1994; Swain, 1987; Swain and Guttmann, 1983). Similarly, systemic models of accident causation and human performance adopt the view that since both failures and successes in large-scale systems are the outcome of normal performance variability, it is necessary to study both successes and failures in systems, and to find ways to reinforce the variability that leads to successes, as well as to dampen the variability that leads to adverse outcomes.
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Current Address: Lab. for Measurement and Control, Department of Mechanical Engineering, University of Delft, Mekelweg 2, 2628 CD Delft, The Netherlands.