• International Journal of Naval Architecture and Ocean Engineering
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• v.11 no.2
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• pp.782-795
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• 2019

Safety is always acritical focus of exploration of ocean resources, and it is well recognized that human factor is one of the major causes of accidents and breakdowns. Our research developed a dynamic human reliability assessment approach, Predicted Mean Vote-Cognitive Reliability and Error Analysis Method (PMV-CREAM), that is applicable to monitoring the cognitive reliability of oceanauts during deep-sea missions. Taking into account the difficult and variable operating environment of manned submersibles, this paper analyzed the cognitive actions of oceanauts during the various procedures required by deep-sea missions, and calculated the PMV index using human factors and dynamic environmental data. The Cognitive Failure Probabilities (CFP) were calculated using the extended CREAM approach. Finally, the CFP were corrected using the PMV index. This PMV-CREAM hybrid model can be utilized to avoid human error in deep-sea research, thereby preventing injury and loss of life during undersea work. This paper verified the method with "Jiaolong" manned submersible 7,000 m dive test. The"Jiaolong" oceanauts CR(Corrected CFP) is dynamic from 3.0615E-3 to 4.2948E-3, the CR caused by the environment is 1.2333E-3. The result shown the PMV-CREAM method could describe the dynamic human reliability of manned submersible caused by thermal environment.

• Nuclear Engineering and Technology
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• v.27 no.3
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• pp.292-300
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• 1995

This paper present a new dynamic HRA (Human Reliability Analysis) method and its application for Quantifying the human error probabilities in implementing an accident management action. For comparisons of current HRA methods with the new method, the characteristics of THERP, HCR, and SLIM-MAUD, which are most frequently used methods in PSAs, are discussed. The action associated with the implementation of the cavity flooding during a station blackout sequence is considered for its application. This method is based on the concepts of the quantified correlation between the performance requirement and performance achievement. The MAAP 3.0B code and Latin Hypercube sampling technique are used to determine the uncertainty of the performance achievement parameter. Meanwhile, the value of the performance requirement parameter is obtained from interviews. Based on these stochastic distributions obtained, human error probabilities are calculated with respect to the various means and variances of the timings. It is shown that this method is very flexible in that it can be applied to any kind of the operator actions, including the actions associated with the implementation of accident management strategies.

• Nuclear Engineering and Technology
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• v.40 no.5
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• pp.349-364
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• 2008

Over the years, probabilistic risk assessment (PRA) research activities conducted at the U.S. Nuclear Regulatory Commission (NRC) have played an essential role in support of the agency's move towards risk-informed regulation. These research activities have provided the technical basis for NRC's regulatory activities in key areas; provided PRA methods, tools, and data enabling the agency to meet future challenges; supported the implementation of NRC's 1995 PRA Policy Statement by assessing key sources of risk; and supported the development of necessary technical and human resources supporting NRC's risk-informed activities. PRA research aimed at improving the NRC's understanding of risk can positively affect the agency's regulatory activities, as evidenced by three case studies involving research on fire PRA, human reliability analysis (HRA), and pressurized thermal shock (PTS) PRA. These case studies also show that such research can take a considerable amount of time, and that the incorporation of research results into regulatory practice can take even longer. The need for sustained effort and appropriate lead time is an important consideration in the development of a PRA research program aimed at helping the agency address key sources of risk for current and potential future facilities.

• Journal of the Korean Institute of Gas
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• v.11 no.2 s.35
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• pp.60-64
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• 2007

Chemical Process industry in Korea has over 30 year's of history and is likely to face potential incidents. The traditional risk analysis and control system in Chemical Process industry focuses on mechanical defects, overlooking the human performance control. Although development of automation technology and controlling technology was necessary, human decision factor is essential to preventing accidents in the Chemical Process. Almost all serious accidents take place when inappropriate humanperformance and mechanical defects of safety equipments simultaneously occurs. The AHRA(Advanced Human Reliability Analyzer) software has been developed to collect failure data and analyze human error probability (Reliability) in Chemical Process Industry in Korea. This paper describes the HRA analysis result of PIF(Performance Influencing Factor) evaluation, HEP(Human Error Probability) and root cause of accidents by applying a Chemical Process Industry related accident data. This analysis result should present a scheme that, by controlling human error factor other than putting safety management funds into the machinery in plants, can reduce cost and maximize the safety in Chemical Process Industry.

• Nuclear Engineering and Technology
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• v.47 no.2
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• pp.187-195
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• 2015

Human-induced initiating events, also called Category B actions in human reliability analysis, are operator actions that may lead directly to initiating events. Most conventional probabilistic safety analyses typically assume that the frequency of initiating events also includes the probability of human-induced initiating events. However, some regulatory documents require Category B actions to be specifically analyzed and quantified in probabilistic safety analysis. An explicit modeling of Category B actions could also potentially lead to important insights into human performance in terms of safety. However, there is no standard procedure to identify Category B actions. This paper describes a systematic procedure to identify Category B actions for low power and shutdown conditions. The procedure includes several steps to determine operator actions that may lead to initiating events in the low power and shutdown stages. These steps are the selection of initiating events, the selection of systems or components, the screening of unlikely operating actions, and the quantification of initiating events. The procedure also provides the detailed instruction for each step, such as operator's action, information required, screening rules, and the outputs. Finally, the applicability of the suggested approach is also investigated by application to a plant example.

• Journal of the Ergonomics Society of Korea
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• v.30 no.1
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• pp.99-108
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• 2011

Almost all companies have paid much attention to the safety management ranging from maintenance to operation even at the stage of designing in order to prevent accidents, but fatal accidents continue to increase throughout the world. In particular, it is essential to systematically prevent such fatal accidents as fire, explosion or leakage of toxic gas at factories in order to not only protect the workers and neighbors but also prevent economic losses and environmental pollution. Though it is well known that accident probability is very low in NPP(Nuclear Power Plants), the reason why many researches are still being performed about the accidents is the results may be so severe. HRA is the main process to make preparation for possibility of human error in designing of the NPP. But those techniques have some problems and limitation as follows; the evaluation sensitivity of those techniques are out of date. And the evaluation of human error is not coupled with the design process. Additionally, the scope of the human error which has to be included in reliability assessment should be expanded. This work focuses on the coincidence of human error and mechanical failure for some important performance shaping factors to propose a method for improving safety effectively of the process industries. In order to apply in these purposes into the thesis, I found 63 critical Performance Shaping Factors of the eight dimensions throughout studies that I executed earlier. In this study, various analysis of opinion of specialists(Personal Factors, Training, Knowledge or Experience, Procedures and Documentation, Information, Communications, HMI, Workplace Design, Quality of Environment, Team Factors) and the guideline for construction of PSF were accomplished. The selected method was AHP which simplifies objective conclusions by maintaining consistency. This research focused on the implementation process of PSF to evaluate the process of PSF at each phase. As a result, we propose an evaluation model of PSF as a tool to find critical problem at each phase and improve on how to resolve the problems found at each phase. This evaluation model makes it possible to extraction of PSF succesfully by presenting the basis of assessment which will be used by enterprises to minimize the trial and error of construction process of PSF.

• Journal of Navigation and Port Research
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• v.43 no.6
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• pp.395-402
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• 2019

The development and operation of the MASS (Maritime Autonomous Surface Ship) is being actively discussed for more efficient and safer maritime transportation solutions. The autonomous navigation technology has positive aspects such as the prevention of marine accidents, improvement of fuel efficiency of ships and cost reduction, and negative aspects such as job loss, task change, and security problems. It is expected that there will be new human element issues such as the situation awareness of remote operators, because the shore-based control will be conducted when fully autonomous ships are in operation. In this paper, we consider major human element issues that should be factored in the development and operation of MASS, and suggest a method of HRA (Human Reliability Analysis) for P IFs (Performance Influencing Factors) of the remote operators that are expected according to the shore-based control.

• Proceedings of the ESK Conference
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• 1997.04a
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• pp.56-60
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• 1997

The study of human erroneous actions has traditionally taken place along two different lines of approach. One has been concerned with finding and explaining the causes of erroneous actions, such as studies in the psychology of "error". The other has been concerned with the qualitative and quantitative prediction of possible erroneous actions, exemplified by the field of human reliability analysis (HRA). Another distinction is also that the former approach has been dominated by an academic point of view, hence emphasising theories, models, and experiments, while the latter has been of a more pragmatic nature, hence putting greater emphasis on data and methods. We have been developing a method to make predictions about error modes. The input to the method is a detailed task description of a set of scenarios for an experiment. This description is then analysed to characterise thd nature of the individual task steps, as well as the conditions under which they must be carried out. The task steps are expressed in terms of a predefined set of cognitive activity types. Following that each task step is examined in terms of a systematic classification of possible error modes and the likely error modes are identified. This effectively constitutes a qualitative analysis of the possibilities for erroneous action in a given task. In order to evaluate the accuracy of the predictions, the data from a large scale experiment were analysed. The experiment used the full-scale nuclear power plant simulator in the Halden Man-Machine Systems Laboratory (HAMMLAB) and used six crews of systematic performance observations by experts using a pre-defined task description, as well as audio and video recordings. The purpose of the analysis was to determine how well the predictions matiched the actually observed performance failures. The results indicated a very acceptable rate of accuracy. The emphasis in this experiment has been to develop a practical method for qualitative performance prediction, i.e., a method that did not require too many resources or specialised human factors knowledge. If such methods are to become practical tools, it is important that they are valid, reliable, and robust.