• Safety and Health at Work
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• v.12 no.4
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• pp.505-510
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• 2021

Background: Factors related to root causes can cause commonly occurring accidents such as falls, slips, and jammed injuries. An important means of reducing the frequency of occupational accidents in small- to medium-sized enterprises (SMSEs) of South Korea is to perform intensity analysis of the root cause factors for accident prevention in the cause and effect model like decision models, epidemiological models, system models, human factors models, LCU (life change unit) models, and the domino theory. Especially intensity analysis in a robot system and smart technology as Industry 4.0 is very important in order to minimize the occupational accidents and fatal accident because of the complexity of accident factors. Methods: We have developed the modern cause and effect model that includes factors of root cause through statistical testing to minimize commonly occurring accidents and fatal accidents in SMSEs of South Korea and systematically proposed educational policies for accident prevention. Results: As a result, the consciousness factors among factors of root cause such as unconsciousness, disregard, ignorance, recklessness, and misjudgment had strong relationships with occupational accidents in South Korean SMSEs. Conclusion: We conclude that the educational policies necessary for minimizing these consciousness factors include continuous training procedures followed by periodic hands-on experience, along with perceptual and cognitive education related to occupational health and safety.

• Proceedings of the Safety Management and Science Conference
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• 2007.04a
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• pp.113-123
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• 2007

Through so that accident of semiconductor industry deduces unsafe factor of the person center on unsafe behaviour that incident history and questionnaire and I made starting point that extract very important factor. It served as a momentum that make up base that analyzes factors that happen based on factor that extract factor cause classification for the first factor, the second factor and the third factor and presents model of human error. Factor for whole defines factor component for human factor and to cause analysis 1 stage in human factor and step that wish to do access of problem and it do analysis cause of data of 1 step. Also, see significant difference that analyzes interrelation between leading persons about human mistake in semiconductor industry and connect interrelation of mistake by this. Continuously, dictionary road map to human error theoretical background to basis traditional accidental cause model and modern accident cause model and leading persons. I wish to present model and new model in semiconductor industry by backbone that leading persons of existing scholars who present model of existent human error deduce relation. Finally, I wish to deduce backbone of model of pre-suppression about accident leading person of the person center.

• Convergence Security Journal
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• v.6 no.4
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• pp.161-169
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• 2006

According to the development of information system, many information system and application soft-ware are develop. However, cyber attack and incident have more increased to the development of them. To defend from cyber attack and incident, many organizations has run information security systems, such as Intrusion Detection System, Firewall, VPN etc, and employed information Security person till now But they have many difficulty in operating these information security component because of the lack of organizational management and analysis of each role. In this paper, We propose the formal Cause-Effect Model related with the information security system and administrative mission per each security. In this model, we regard information system and information system operator as one information component. It is possible to compose the most suitable information component, such as information system, human resource etc., according to the analysis of Cause-Effect Model in this paper. These analysis and approaching methodology can make effective operation of each limited resource in organization and effective defense mechanism against many malicious cyber attack and incident.

• IE interfaces
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• v.25 no.4
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• pp.382-392
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• 2012

Reactor protection system to keep nuclear safety and operational economy of plants requires high reliability. Such a high reliability of the system can be achieved through the redundant design of components. However, common cause failures of components reduce the benefits of redundant design. Thus, the common cause failure analysis, to accurately calculate the reliability of the reactor protection system, is carried out using alpha-factor model. Analysis results to 24 operating months are that 1) the system reliability satisfies the reliability goal of EPRI-URD and 2) the common cause failure contributes 90% of the system unreliability. The uncertainty analysis using alpha factor parameters of 0.05 and 0.95 quantile values shows significantly large difference in the system unreliability.

• The Korean Journal of Health Service Management
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• v.13 no.3
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• pp.13-26
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• 2019

Objectives: To investigate whether medical institutions can prevent accidents by analyzing the root cause of a medical accident and identifying the tendencies. Methods: A total of 345 medical cases were used for the RCA(Root Cause Analysis). The root causes were classified using the SHELL model. The suitability of the model was confirmed by SPSS's MDPREF and Euclidean distance. An SPSS20.0 hierarchical regression analysis was used as an influencing factor on the degree of injury resulting from medical accidents. Results: The SHELL model was suitable for classification. The rates of accident causes were LS49%, L34%, LL10.2%, LE3.7%, LH2.3%. The order in which the degree of a patient's injury was affected were: Risk Threshold (${\beta}=.180$), Time (${\beta}=.175$), Surgical stage (${\beta}=-.166$), Do not use procedure (${\beta}=.147$). Conclusions: Health care institutions should remove priorities through system improvement and training. For patients' safety, the five factors of the SHELL model should be managed in harmony.

• Communications for Statistical Applications and Methods
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• v.26 no.6
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• pp.557-573
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• 2019

Mortality study is an essential component of actuarial risk management for life insurance policies, annuities, and pension plans. Life expectancy has drastically increased over the last several decades; consequently, longevity risk associated with annuity products and pension systems has emerged as a crucial issue. Among the various aspects of mortality study, a consideration of the cause-of-death mortality can provide a more comprehensive understanding of the nature of mortality/longevity risk. In this case study, the cause-of-mortality data in Korea and the US were analyzed along with a multinomial logistic regression model that was constructed to quantify the impact of mortality reduction in a specific cause on actuarial values. The results of analyses imply that mortality improvement due to a specific cause should be carefully monitored and reflected in mortality/longevity risk management. It was also confirmed that multinomial logistic regression model is a useful tool for analyzing cause-of-death mortality for actuarial applications.

• Journal of the Korea Safety Management & Science
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• v.17 no.2
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• pp.241-247
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• 2015

The purpose of the warranty data analysis can be classified into two categories. Two goals is a failure cause analysis and life prediction analysis. In this paper first, we applied multivariate analysis method that can be estimated in consideration of various factors on the failure cause warranty data. In particular, we apply the Tree model and Cox model. The advantage of the Tree is easy to interpret this result as compared to other models. In addition Cox model can quantitatively express the risk. Second, this paper proposed a multivariate life prediction model (AFT) considering a variety of factors. By applying the actual warranty data confirmed the usability.

• Nuclear Engineering and Technology
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• v.24 no.1
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• pp.14-29
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• 1992

COMCAF, a computer code for the common-cause failure analysis, is developed to treat the common-cause failures in nuclear power plants. In the treatment of common-cause failures, the minimal cut sets of the system are obtained first without changing the fault-tree structure. The occurrence probabilities of the minimal cut sets are then calculated accounting for the common-cause failures among components in the same minimal cut set or in different minimal cut sets. The basic parameter model is used to model the common-cause failures between similar or identical components. For dissimilar components, the assumption of symmetry used in the basic parameter model is applied to the basic events affecting two or more components. The top event probability is evaluated using the inclusion-exclusion method. In addition to the common-cause failures of components in the same minimal cut sets, failures of components in the different minimal cut sets are also easily accounted for by this method. This study applied this common-cause failure analysis to the PWR auxiliary feedwater system. The results in the top event probability for the system are compared with those of no common-cause failures.

• International Journal of Advanced Culture Technology
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• v.11 no.3
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• pp.297-301
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• 2023

The study identified the various causes of odor problems, the discomfort they cause, and the importance of the public health and environmental issues associated with them. To solve the odor problem, you must identify the cause and perform an accurate analysis. Therefore, we proposed a CNN-Transformer hybrid model (CTHM) that combines CNN and Transformer and evaluated its performance. It was evaluated using a dataset consisting of 120,000 odor samples, and experimental results showed that CTHM achieved an accuracy of 93.000%, a precision of 92.553%, a recall of 94.167%, an F1 score of 92.880%, and an RMSE of 0.276. Our results showed that CTHM was suitable for odor analysis and had excellent prediction performance. Utilization of this model is expected to help address odor problems and alleviate public health and environmental concerns.

• Safety and Health at Work
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• v.12 no.1
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• pp.42-50
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• 2021

Introduction: Despite huge investments in new technology and transportation infrastructure, terrible accidents still remain a reality of traffic. Methods: Severe traffic accidents were analyzed from four prevailing modes of today's transportations: sea, air, railway, and road. Main root causes of all four accidents were defined with implementation of the approach, based on Flanagan's critical incident technique. In accordance with Molan's Availability Humanization model (AH model), possible preventive or humanization interventions were defined with the focus on technology, environment, organization, and human factors. Results: According to our analyses, there are significant similarities between accidents. Root causes of accidents, human behavioral patterns, and possible humanization measures were presented with rooted graphs. It is possible to create a generalized model graph, which is similar to rooted graphs, for identification of possible humanization measures, intended to prevent similar accidents in the future. Majority of proposed humanization interventions are focused on organization. Organizational interventions are effective in assurance of adequate and safe behavior. Conclusions: Formalization of root cause analysis with rooted graphs in a model offers possibility for implementation of presented methods in analysis of particular events. Implementation of proposed humanization measures in a particular analyzed situation is the basis for creation of safety culture.