• Proceedings of KOSOMES biannual meeting
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• 2004.11a
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• pp.89-94
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• 2004

For many years, fatigue was discounted as a potential cause of or contributor to human error. However, resent accident data and research point to fatigue as a cause of and/or contributor to human error precisely because of its impact on performance. The goal of this study is to analyze and examine of the fatigue factors related to human error. For this, we carried out the questionnaire survey which concerned with the fatigue factors.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.6
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• pp.1025-1033
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• 2010

This paper proposes a method to improve and analysis error cause of FI(Fault Indicator) information to be used for detecting fault section in distribution automation system. FI error cause is made by consideration fault current magnitude and time. So, a new method to prevent FI error is proposed to include fault current magnitude, time and direction. Therefore, it's considered network environments that grounded and ungrounded network in distribution automation system. The proposed method is proved by Matlap Simulink. By the result in this research, it's possible to quickly restoration, supplying stability and reliability power to customer.

• Proceedings of the Safety Management and Science Conference
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• 2008.04a
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• pp.19-33
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• 2008

The study on semiconductor industrial accident in korea has been focused on frequencies of each type, employee, characteristics, cause and un-safety condition, behaviour and so on. Those attributes of semiconductor industrial accidents were usually analyzed independently, so that it was hard to provides a well-process and systematic guide lines for efficient safety management. There fore, there were a few studies based on comprehensive survey in terms of sharp-type of safe management. The questionnaire survey carried out for the workers(284) who were responsible for safety management in to center with corporate company with semiconductor industry the factor analysis showed that there were three factor of safety management. They were 1) Investment and operation and management for accident prevention, 2) Unsafe, safety management 3) General human error and behavior the industries of respondents were correlative with three group. Three Groups showed a statistically significant differences on the number of cases. Actually, the group with the larger investment and the better unsafe cause, human error a of accident prevention had a smaller cause of accident cases.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.115-118
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• 2005

A workpiece with a large surface area is likely to be uneven due to form error and waviness. These geometric disturbances can cause inaccurate micro shapes to be formed when micro features are micro-grooved into the surface and cause the resulting workpiece to fail to function as desired. Thus, real-time measurement and compensation is required to guarantee the form accuracy of micro features while machining a workpiece with a large surface area. In this study, a method is suggested for real-time measurement of geometric error for the micro grooving of a large flat surface using a laser displacement sensor. The measurements are demonstrated for the workpieces with large surface areas and the experimental results show that the waviness and form error are well detected.

• Journal of Korea Society of Industrial Information Systems
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• v.9 no.4
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• pp.56-67
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• 2004

This study analyzes human error of workers performing simple repetitive tasks, and in order to prepare preventative measures, 486 people were used as subjects. The results of the study are like the following. First, the biggest cause of human error showed to be the worker himself in $77.8\%$ of the cases, machinery showed to be the cause in $16.3\%$ of the cases and management showed to be the cause in $6.0\%$ of the cases. The results show that most of the human error occurred due to the worker performing simple repetitive tasks and the human errors showed to be caused more by bad ergonomics and long hours rather than by problems with machinery. In addition, the area with the highest rate of human error showed to be the Human Information Processing System with Task Input Error being the highest with $46.9\%$, followed by Judgement and Memory Error with $36.4\%$ and Recognition Verification Error with $16.7\%$. Although fully automated tasks may reduce the rate of human error we must focus on lowering the rate of problems arising from spontaneous errors caused by workers performing simple repetitive tasks by continuously renewing plans and budgets in order to standardize tasks by incorporating cyclic positioning according to experience and positional exchange and by inspecting the workplace to increase efficiency of the workers.

• Journal of the Ergonomics Society of Korea
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• v.34 no.2
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• pp.103-113
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• 2015

Objective: This study proposes a systematic process to present the analysis methods and solutions of organizational root causes to human errors on the railroad. Background: In fact, organizational root cause such as organizational culture is an important factor in the safety concerns on human errors in the nuclear power plant, railroad and aircraft. Method: The proposed process is as follows: 1) define analysis boundary 2) select human error taxonomy 3) perform accident analysis 4) draw root causes with FGI 5) review root causes analysis with survey 6) chart analysis of root causes, and 7) propose alternatives and solutions. Results: As a result, root causes of the organizations like railroad and nuclear power plant came from the educational problems, violations, payoff system, safety culture and so forth. Conclusion: The proposed process does predict potential railroad accident through retrospect error analysis by building new human error taxonomies and problem solution. Application: This study would contribute to examination of the relationship between human error-based accidents and organizational root causes.

• Journal of the Ergonomics Society of Korea
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• v.27 no.3
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• pp.43-52
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• 2008

Human errors are now considered as the most significant source of accidents or incidents in large-scale systems such as aircraft, vessels, railway, and nuclear power plants. As 61% of the train accidents in Korea railway involving collisions, derailments and fires were caused by human errors, there is a strong need for a systematic research that can help to prevent human errors. Although domestic railway operating companies use a variety of methods for analyzing human errors, there is much room for improvement. Especially, because most of them are based on written papers, there is a definite need for a well-developed computerized system supporting human error analyzing tasks. The purpose of this study is to propose a framework for a computerized human error analysis system focused on the railway industry on the basis of human error analysis mechanism. The proposed framework consists of human error analysis (HEA) module, similar accident tracking (SAT) module, cause factor recommendation (CFR) module, cause factor management (CFM) module, and statistics (ST) module.

• Journal of Wellbeing Management and Applied Psychology
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• v.7 no.1
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• pp.27-33
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• 2024

Purpose: This study investigates human error accidents in the Korean railway sector, emphasizing the need for systematic management to prevent such incidents, which can have fatal consequences, especially in driving-related jobs. Research design, data and methodology: This paper analyzed data from the Aviation and Railway Accident Investigation Board and the Korea Transportation Safety Authority, examining 240 human error accidents that occurred over the last five years (2018-2022). The analysis focused on accidents in the driving, facility, electric, and control fields. Results: The findings indicate that the majority of human error accidents stem from negligence in confirmation checks, issues with work methods, and oversight in facility maintenance. In the driving field, errors such as signal check neglect and braking failures are prevalent, while in the facility and electric fields, the main issues are maintenance delays and neglect of safety measures. Conclusions: The paper concludes that human error accidents are complex and multifaceted, often resulting from a high workload on engineers and systemic issues within the railway system. Future research should delve into the causal relationships of these accidents and develop targeted prevention strategies through improved work processes, education, and training.

• Transactions of the Korean Society of Automotive Engineers
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• v.25 no.2
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• pp.133-139
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• 2017

The timing chain system, which is a typical power transmission technology applied to a vehicle, has been widely used by the automotive industry because it is normally designed to last a car's lifetime. However, the timing chain system may cause some problems due to the shape of the chains and the polygonal behavior on contact between the chain and the sprocket. In addition, noise and vibration caused by transmission error are the most typical problems encountered by major automotive manufacturers and they are considered as the main source of customer complaint. The initial tension of the chain-sprocket system is thought to be the main cause of transmission error, and it is regarded as the source of engine vibration and noise. The initial tension of the chain system should be controlled carefully since a low initial tension can cause twisting, which may lead to a system malfunction, while a high initial tension can reduce the service life due to a worn down contact surface. In this paper, the kinematic analysis model is generated with various initial tensions, which are controlled by changing the shape of the fixed guide with the largest contact surface with chain. The results showed that the transmission error was minimized on a particular range of initial tension, and the tendency showed that the error changed with a higher sensitivity at a lower initial tension.

• Survey Research
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• v.11 no.3
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• pp.33-55
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• 2010

In this study, we newly define the Total Survey Error(TSE) in exit poll and investigate the TSEs of the exit poll survey for the 18th general election of 2008 to analyse the cause of the exit poll prediction error. To explore the main cause and effect of the total survey error, the total survey error was divided by the sampling error which comes from sampling process of poll stations and the non-sampling error which comes from selecting voter and collecting responses from sampled voters in each electoral district. We consider the relationship between non-response rates and total survey error as well as non-sampling error. Also, we study the representativeness of the exit poll sample by comparing the sex/age distribution of the exit poll data and the National Election Commission poll data.