• Safety and Health at Work
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• v.9 no.1
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• pp.42-52
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• 2018

Background: Maintenance operations on-board ships are highly demanding. Maintenance operations are intensive activities requiring high man-machine interactions in challenging and evolving conditions. The evolving conditions are weather conditions, workplace temperature, ship motion, noise and vibration, and workload and stress. For example, extreme weather condition affects seafarers' performance, increasing the chances of error, and, consequently, can cause injuries or fatalities to personnel. An effective human error probability model is required to better manage maintenance on-board ships. The developed model would assist in developing and maintaining effective risk management protocols. Thus, the objective of this study is to develop a human error probability model considering various internal and external factors affecting seafarers' performance. Methods: The human error probability model is developed using probability theory applied to Bayesian network. The model is tested using the data received through the developed questionnaire survey of >200 experienced seafarers with >5 years of experience. The model developed in this study is used to find out the reliability of human performance on particular maintenance activities. Results: The developed methodology is tested on the maintenance of marine engine's cooling water pump for engine department and anchor windlass for deck department. In the considered case studies, human error probabilities are estimated in various scenarios and the results are compared between the scenarios and the different seafarer categories. The results of the case studies for both departments are also compared. Conclusion: The developed model is effective in assessing human error probabilities. These probabilities would get dynamically updated as and when new information is available on changes in either internal (i.e., training, experience, and fatigue) or external (i.e., environmental and operational conditions such as weather conditions, workplace temperature, ship motion, noise and vibration, and workload and stress) factors.

• Nuclear Engineering and Technology
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• v.45 no.2
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• pp.151-164
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• 2013

A key input for the assessment of Human Error Probabilities (HEPs) with Human Reliability Analysis (HRA) methods is the evaluation of the factors influencing the human performance (often referred to as Performance Shaping Factors, PSFs). In general, the definition of these factors and the supporting guidance are such that their evaluation involves significant subjectivity. This affects the repeatability of HRA results as well as the collection of HRA data for model construction and verification. In this context, the present paper considers the TAsk COMplexity (TACOM) measure, developed by one of the authors to quantify the complexity of procedure-guided tasks (by the operating crew of nuclear power plants in emergency situations), and evaluates its use to represent (objectively and quantitatively) task complexity issues relevant to HRA methods. In particular, TACOM scores are calculated for five Human Failure Events (HFEs) for which empirical evidence on the HEPs (albeit with large uncertainty) and influencing factors are available - from the International HRA Empirical Study. The empirical evaluation has shown promising results. The TACOM score increases as the empirical HEP of the selected HFEs increases. Except for one case, TACOM scores are well distinguished if related to different difficulty categories (e.g., "easy" vs. "somewhat difficult"), while values corresponding to tasks within the same category are very close. Despite some important limitations related to the small number of HFEs investigated and the large uncertainty in their HEPs, this paper presents one of few attempts to empirically study the effect of a performance shaping factor on the human error probability. This type of study is important to enhance the empirical basis of HRA methods, to make sure that 1) the definitions of the PSFs cover the influences important for HRA (i.e., influencing the error probability), and 2) the quantitative relationships among PSFs and error probability are adequately represented.

• Journal of Navigation and Port Research
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• v.47 no.2
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• pp.93-99
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• 2023

This study aimed to determine relationships among risk factors influencing container port operation using Bayesian network. Risk factors identified from prior studies were classified into five groups: human error, machinery error, environmental risk, security risk, and natural disasters. P anel experts discussed identified risk factors to fulfil conditional probability tables of the interdependence model. The interdependence model was also validated by sensitivity analysis and provided an interrelation of factors influencing the direction of each other. Results of the interdependence model were partially in line with results from prior studies while practices in the global port industry confirmed interrelationships of risk factors. In addition, the relationship between top-ranked risk factors can provide a schematic drawing of the model. Accordingly, results of this study can expand the prior research in the Korean port industry, which may help port authorities improve risk management and reduce losses from the risk.

• Journal of Korean Society for Quality Management
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• v.24 no.2
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• pp.54-64
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• 1996

The inspection policy and inspection error are very critical factors which influence the outgoing quality. In other words, such factors influence the acceptance rate of the incoming matarials. Hence, the outgoing lot size is varied. This paper presents a method to compute the break-even point(pb1, pb2) under these two factors, which canbe used to determine the economic acceptance inspection type.

• Journal of Mechanical Science and Technology
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• v.18 no.4
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• pp.606-621
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• 2004

A dynamic analysis using a hybrid finite element method was performed to characterize the effects of a number of manufacturing errors on bearing forces and critical tooth stress in the elements of a planetary gear system. Some tolerance control guidelines for managing bearing forces and critical stress are deduced from the results. The carrier indexing error for the planet assembly and planet runout error are the most critical factors in reducing the planet bearing force and maximizing load sharing, as well as in reducing the critical stress.

• International Journal of Advanced Culture Technology
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• v.8 no.1
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• pp.173-181
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• 2020

This study examines whether unmanned aircraft systems (UAS) operated in the context of UAS traffic management (UTM) can be properly operated in its flight environment. In detail, this study examines the influencing navigation factors affecting UASs during flight and examines factors affecting the navigation of UASs under UTM. After deriving various factors affecting navigation, their importance are determined by applying the analytic hierarchy process technique, and the important influencing factors are examined. For low-altitude UAS navigation, errors are classified into navigation-system and flight-technical errors, and a hierarchy is constructed for their sub-factors affecting the influencers. Through this, influencing factors for precise navigation of low-altitude UAS are analyzed, and high importance items are identified.

• Journal of the Korea Safety Management & Science
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• v.16 no.2
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• pp.1-9
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• 2014

This study tried to propose plan to prevent human error of railroad driver among human error of railroad worker which takes great share in railroad accident. For this, in order to maintain correlation between the accident actually occurred after the opening of high-speed railroad and experience of accident that did not happened, survey on respondent was analyzed by conducting survey on KTX captain who is working in driving work of high-speed railroad, and instruction management team manager who manages KTX captain and captain. This thesis classified the factors by human factor, job factor, environment factor, organization factor, and established human error management model by comparing and analyzing how each factors have spatial interrelations with a railroad accident. The purpose of this study is to contribute to make safe railroad, and reliable railroad by preventing human error accident by minimizing human error of high-speed railroad drivers, and improving driving workers to cope accurately and fast with irregularities through various institutional improvement, improvement of driving facilities, improvement of operating room environment, and improvement of education system.

• Journal of the Korean Society of Safety
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• v.29 no.1
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• pp.47-53
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• 2014

The application of advanced Main Control Room(MCR) is accompanied with lots of changes and different forms and features through the virtue of new digital technologies. The characteristics of these digital technologies and devices give many opportunities to the interface management, and can be integrated into a compact single workstation in advanced MCR so that workers can operate the plant with minimum physical burden under any operation conditions. However, these devices may introduce new types of human errors and thus a means to evaluate and prevent such errors is needed, especially those related to characteristics of digital devices. This paper reviewed the new type of human error hazards of tasks based on digital devices and surveyed researches on physiological assessment related to human error. An experiment was performed to verify human error hazards by physiological responses such as EEG which was measured to evaluate the cognitive workload of operators. And also, the performances of four tasks which are representative in human error hazard tasks based on digital devices were compared. Response time, ${\beta}$ power spectrum rate of each task by EEG, and mental workload by NASA-TLX were evaluated. In the results of the experiment, the rate of the ${\beta}$ power was increased in the task 1 and task 4 which are searching and navigating task and memory task of hierarchical information, respectively. In case of the mental workload, in most of evaluation items, task 1 and 4 were highly rated comparatively. In this paper, human error hazards might be identified by highly cognitive workload. Conclusively, it was concluded that the predictive method which is utilized in this paper and an experimental verification can be used to ensure the safety when applying the digital devices in Nuclear Power Plants (NPPs).

• Journal of the Korea Society for Simulation
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• v.20 no.3
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• pp.59-67
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• 2011

This paper proposes a model to analyze the fault factors of air-to-ground weapon delivery utilizing software fault localization methods. In the previous study, to figure out the factors to affect the accuracy of air-to-ground weapon delivery, the FBEL (Factor-based Error Localization) method had been proposed and the fault factors were analyzed based on the method. But in the study, the correlation between weapon delivery accuracy and the fault factors could not be revealed because the firing accuracy among several factors was fixed. In this paper we propose a more precise fault analysis model driven through a study of the correlation among the fault factors of weapon delivery, and a method to estimate the possibility of faults with the limited number of test cases utilizing the model. The effectiveness of proposed method is verified through the simulation utilizing real delivery data. and weapons delivery testing in the evaluation of which element affecting the accuracy of analysis that was available to be used successfully.

• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.1362-1365
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• 2008

ED-2523 (Measuring methods for matr ix reflective LCD modules) was published by JEITA (Japan Electronics and Information Technology Industries Association) in 2001. Since then, round robin tests had been done and the accuracy of measurement values had been discussed. In this paper, considerations for error factors in four measurement systems are showed.