The research on extracting the information of human errors in the main control room of nuclear power plants by using Performance Evaluation Matrix

Jou, Yung‐Tsan; Yenn, Tzu-Chung; Lin, Chiuhsiang Joe; Tsai, Wan-Shan; Hsieh, Tsung-Ling

doi:10.1016/j.ssci.2010.08.004

Cited by 19 publications

(17 citation statements)

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“…Risks in nuclear power plants have attracted the attention of many researchers because of large scale devastating disasters such as the Three Mile Island accident in 1979, the Chernobyl nuclear accident in 1986 and the Fukushima Dai-ichi nuclear accident in 2011. Scholars have examined risk in nuclear power plants from multiple angles, including construction risks (Wang et al 2011), risks of refueling leakage (Rohrer and Nierode 1996), and risks in systems operation (Smith 1998;Le Bot 2004;Carvalho et al 2008;Jou et al 2011;Lee et al 2012;Anuar and Kim 2014;Teperi et al 2017). Risks in systems operation are further divided into components outage, initiating events (Smith 1998), human error-especially individual psychological error (Le Bot 2004), as well as human factors in human-system interfaces (Carvalho et al 2008;Anuar and Kim 2014), in reporting and analyzing operational events (Teperi et al 2017), and in the main control room (Jou et al 2011;Lee et al 2012).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Production risk, in detail, lies in all variables, such as humans, materials, and machines, contributing to production processes (Govindaraju et al 2001). Based on our search of existing studies, the identified causes of production risk include procedure usage, fatigue, knowledge, experience, time pressure (Sheikhalishahi et al 2017), turnover (Vaurio 2009), efficiency of implementing orders (Bevilacqua and Ciarapica 2018), mental pressure (Jou et al 2011), maintenance planning (Krishnasamy et al 2005), ergonomic work conditions, discomfort, pain, stress, reduced visual, hearing, smell and tactile abilities (Govindaraju et al 2001), equipment failures (Lavasani et al 2015), monitoring systems (Chang et al 2010), land, labor (Tiedemann and Latacz-Lohmann 2013), weather (Karki et al 2012), environmental communication, risk communication (Ofori-Parku 2016), and risk attitude (Vollmer et al 2017). Among these causes, equipment failures, maintenance planning (Krishnasamy et al 2005) and monitoring systems (Chang et al 2010) are particularly examined as causes of production risk in thermal power plants in the literature.…”

Section: Production Risksmentioning

confidence: 99%

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Production risk caused by human factors: a multiple case study of thermal power plants

Diao

Ghorbani

2018

Front. Bus. Res. China

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Introduction: Thermal power plants are very popular in China. However, there has not been proportional research attention paid to production risk in these plants and human impact on production due to their importance in electricity generation. This study investigates production risks caused by human factors in thermal power plants and management methods to address identified human factors. Case description: Eighteen semi-structured interviews with front-line, middle and senior managers from four thermal power plants in China were carried out in this cross-sectional inductive study. Fault tree analysis and causal network analysis are used. Discussion and evaluation: We identify a range of production risks and human factors potentially influencing production in both negative and positive ways. We also recognize the most effective and practical relevant management methods to deal with identified human factors. Conclusion: By investigating production risk caused by human factors through the whole production process, this study emphasizes working attitude, safety consciousness, creativity and awareness of environmental protection as essential human factors potentially influencing production risks in thermal power plants. Through our analysis, by linking human factors to different types of production risk and supplying corresponding management methods to address these human factors, we offer practical human resource management approaches in the production management of thermal power plants.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Production Risksmentioning

confidence: 99%

Production risk caused by human factors: a multiple case study of thermal power plants

Diao

Ghorbani

2018

Front. Bus. Res. China

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“…The results of this study reinforce the ideas that the HSI is an important mediator between humans and automation and that it is important that the HSI communicate the right information to the operator at the right time. Jou et al (2011) applied content category analysis and performance evaluation matrix methods to explore the potential operator errors that can be caused by advanced digital HSI in light water reactor NPP control rooms. They identified that multiple accidents, pressure level, number of available operators, and other environmental factors are key issues that impact the likelihood of operator errors.…”

Section: Endsley's Sa Model (Shown Inmentioning

confidence: 99%

Development of an Initial Model of Human-Automatio

Oxstrand¹,

O'Hara²,

Joe³

et al. 2013

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viii ix EXECUTIVE SUMMARYThe U.S. Department of Energy (DOE) and the commercial nuclear power industry are exploring alternatives to meet energy demands in the United States. As part of this mission, they are looking at small modular reactors (SMRs) and advanced small modular reactors (aSMRs). The DOE, and in particular, the Office of Nuclear Energy (NE) is sponsoring research and development (R&D) on small reactors, as evidenced by NE's 2010 Report to Congress, Nuclear Energy Research and Development Roadmap. In short, DOE-NE's mission is to assist in revitalization of the U.S. nuclear industry, including development of advanced designs, through R&D. By doing so, NE can help accelerate deployment of new plants in the short term, support development of advanced concepts for the medium term, and promote design of revolutionary systems for the long term.All aSMR designs will employ advanced digital instrumentation, controls, and human-machine interfaces (ICHMI), technology that is significantly more advanced that existing analog systems in the light water reactor fleet. The U.S. DOE recognizes that ICHMI research, development, and demonstration is needed to address the specific technical challenges and technological gaps of ICHMI for aSMR designs. The new aSMRs will be designed to utilize new automation and instrumentation and control technologies, and there are a number of concerns about how those technologies will affect human performance and the overall safety of the plant. It is expected that aSMRs will rely on automation to a greater extent than the current nuclear power plant fleet. However, there are many issues and concerns that still need to be addressed related to how automation should be designed and implemented. For example, further researcher is needed to address how humans and automation will collaborate under various operational conditions.The Human-Automation Collaboration (HAC) research project is one of three research efforts related to investigating how the advanced technologies planned for aSMR designs will affect human factors and human performance. Given the increased use of automation in aSMR designs, the HAC research project is investigating the consequences of allocating functions between the operators and automated systems. The research effort addresses the questions of what the collaboration level should be and how it should be implemented to have the greatest positive impact on overall plant performance and safety. The research project is also developing a model of HAC, which will support aSMR designers when evaluating their proposed approach for conduct of operations in terms of how humans and automation collaborate. The research results will inform the integration and cooperation between plant staff and automation, with the purpose of maximizing productivity and safe operations of aSMRs. One key research goal is providing a technical basis to support the reduction in aSMR operations and maintenance costs through reduced staffing per unit, which is made possible by greater integration ...

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“…If several abnormal situations occur at once, decisions have to be made in even less time. Operators are usually unable to judge what situation should be given priority when confronted with complex abnormal situations such as these [6,7].…”

Section: Introductionmentioning

confidence: 99%

An abnormal situation modeling method to assist operators in safety-critical systems

Naderpour

Zhang

2015

Reliability Engineering & System Safety

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One of the main causes of accidents in safety-critical systems is human error. In order to reduce human errors in the process of handling abnormal situations that are highly complex and mentally taxing activities, operators need to be supported, from a cognitive perspective, in order to reduce their workload, stress, and the consequent error rate. Of the various cognitive activities, a correct understanding of the situation, i.e. situation awareness (SA), is a crucial factor in improving performance and reducing errors. Despite the importance of SA in decision-making in time-and safety-critical situations, the difficulty of SA modeling and assessment means that very few methods have as yet been developed. This study confronts this challenge, and develops an innovative abnormal situation modeling (ASM) method that exploits the capabilities of risk indicators, Bayesian networks and fuzzy logic systems. The risk indicators are used to identify abnormal situations, Bayesian networks are utilized to model them and a fuzzy logic system is developed to assess them. The ASM method can be used in the development of situation assessment decision support systems that underlie the achievement of SA. The performance of the ASM method is tested through a real case study at a chemical plant.

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The research on extracting the information of human errors in the main control room of nuclear power plants by using Performance Evaluation Matrix

Cited by 19 publications

References 6 publications

Production risk caused by human factors: a multiple case study of thermal power plants

Production risk caused by human factors: a multiple case study of thermal power plants

Development of an Initial Model of Human-Automatio

An abnormal situation modeling method to assist operators in safety-critical systems

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