• 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.

• Journal of the Korean Society of Safety
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• v.35 no.4
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• pp.1-8
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• 2020

Intensity of accidents associated with dangerous machines and devices are (hereafter items), in general, high compared to other industrial accidents. This study focuses on cause analysis of accidents associated with items that are subject to safety certification. The method is based on automated analysis of abstracts of accidents written in descriptive format. The analysis results indicate that more than 50% of accidents associated with items are caused by technical reasons and nearly 50% of accidents were preventable. More effective prevention of industrial accidents would then be realized by safety certification at the stage of danger generation. Transition from the direct regulation on users to manufacturers is also needed to improve the effectiveness and efficiency of industrial safety system in Korea.

• Journal of Power System Engineering
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• v.9 no.1
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• pp.57-63
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• 2005

In the calendar and the advertising catalog, the surface is usually coated by coating polypropylene film. The delamination failure of coating film depends on surface roughness and quality of the substrate paper. In this paper, the mechanisms of delamination failure between the coating film and the paper is investigated by using the root cause analysis as one of techniques of reliability evaluation. The papers used in failure analysis are three kind products made by two domestic and one foreign companies. It found that the main causes of delamination failure between the coating film and the paper were the creation of microvoids caused by shape of filler and their growth caused by contraction of paper.

• Journal of the Korean Institute of Gas
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• v.18 no.4
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• pp.86-94
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• 2014

To develop a Root Cause Analysis Map which determines the cause of the accident in chemical laboratory, The Root Cause Analysis(RCA) Map for the laboratory areas was sketched from Phase 1 of the accident element to Phase 3 of the accident element, based on the RCA Map which is applied in the petrochemical industry. On the basis of laboratory RCA Map which was classified by using such method. The root causes of the 211 accident cases in laboratories were classified from Phase 4 to Phase 5 by the Cause Factor Charting technique and The cause of the accident data were inputted to EXCEL program. After that, The causes of the accident data were sorted and classified by type and each step. So 'Approximate Primary RCA Map Draft' was written. In addition, it was reaffirmed whether the root causes of 211 accidents of laboratory were appropriate to 'Primary RCA Map Draft'. By complementing the cause which was expected to cause future accidents, the RCA Map for chemical laboratories was developed. Based on 'RCA Map' proposed in this study, the causes of accidents were analysed management systems 35%, monitoring 12.2%, Human Factor Eng. 15.1% and education training 12.1% by the size of the frequency from Phase 1 to Phase 5.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.2
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• pp.129-137
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• 2016

To identify the cause of the error and maintain the health of system, an administrator usually analyzes event log data since it contains useful information to infer the cause of the error. However, because today's systems are huge and complex, it is almost impossible for administrators to manually analyze event log files to identify the cause of an error. In particular, as OpenStack, which is being widely used as cloud management system, operates with various service modules being linked to multiple servers, it is hard to access each node and analyze event log messages for each service module in the case of an error. For this, in this paper, we propose a novel message-based log analysis method that enables the administrator to find the cause of an error quickly. Specifically, the proposed method 1) consolidates event log data generated from system level and application service level, 2) clusters the consolidated data based on messages, and 3) analyzes interrelations among message groups in order to promptly identify the cause of a system error. This study has great significance in the following three aspects. First, the root cause of the error can be identified by collecting event logs of both system level and application service level and analyzing interrelations among the logs. Second, administrators do not need to classify messages for training since unsupervised learning of event log messages is applied. Third, using Dynamic Time Warping, an algorithm for measuring similarity of dynamic patterns over time increases accuracy of analysis on patterns generated from distributed system in which time synchronization is not exactly consistent.

• Journal of the Korean Institute of Gas
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• v.4 no.4 s.12
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• pp.65-70
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• 2000

We develop the database program for accident cause analysis which can help to increase domestic safety custom and prevent recurrence of gas accident and analyze accidents easily The program developed in this study consists of two parts. one part uses accident case database applied if than rule, so it finds root causes by inference of some input values. The other uses Root Cause Analysis Map which divided human errors and equipment difficulties and so we get general root cause by reply some proper questions.

• 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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.2
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• pp.84-94
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• 2018

In recent years, the diminishing of operation and maintenance cost using advanced maintenance technology is attracting many companies' attention. Especially, the heavy machinery industry regards it as a crucial problem since a failure of heavy machinery requires high cost and long downtime. To improve the current maintenance process, the heavy machinery industry tries to develop a methodology to predict failure in advance and to find its causes using usage data. A better analysis of failure causes requires more data so that various kinds of sensor are attached to machines and abundant amount of product usage data is collected through the sensor network. However, the systemic analysis of the collected product usage data is still in its infant stage. Many previous works have focused on failure occurrence as statistical data for reliability analysis. There have been less works to apply product usage data into root cause analysis of product failure. The product usage data collected while failures occur should be considered failure cause analysis. To do this, this study proposes a methodology to apply product usage data into failure cause analysis. The proposed methodology in this study is composed of several steps to transform product usage into failure causes. Various statistical analysis combined with product usage data such as multinomial logistic regression, T-test, and so on are used for the root cause analysis. The proposed methodology is applied to field data coming from operated locomotive and the analysis result shows its effectiveness.

• 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.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.1
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• pp.25-28
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• 2014

Background: This study analyzed whether socio-economic factors affect the cause specific survival of soft tissue sarcoma (STS). Methods: Surveillance, Epidemiology and End Results (SEER) soft tissue sarcoma (STS) data were used to identify potential socio-economic disparities in outcome. Time to cause specific death was computed with Kaplan-Meier analysis. Kolmogorov-Smirnov tests and Cox proportional hazard analysis were used for univariate and multivariate tests, respectively. The areas under the receiver operating curve were computed for predictors for comparison. Results: There were 42,016 patients diagnosed STS from 1973 to 2009. The mean follow up time (S.D.) was 66.6 (81.3) months. Stage, site, grade were significant predictors by univariate tests. Race and rural-urban residence were also important predictors of outcome. These five factors were all statistically significant with Cox analysis. Rural and African-American patients had a 3-4% disadvantage in cause specific survival. Conclusions: Socio-economic factors influence cause specific survival of soft tissue sarcoma. Ensuring access to cancer care may eliminate the outcome disparities.