Radioactive waste can be classified according to the concentration level for radionuclides, and the disposal method is different through the level. Gamma analysis is inevitably performed to determine the concentration of radioactive waste, and when a large amount of radioactive waste is generated, such as decommissioning nuclear facilities, it takes a lot of time to analyze samples. The performance of a lot of analysis can cause human errors and workload. In general, gamma analysis is performed using by HPGe detector. Recently, for convenience of analysis, commercial automatic sample changers applicable to the HPGe detectors were developed. The automatic sample changers generate individual analysis reports for each sample. In this study, gamma analysis procedure was improved using the application of the automatic sample changer and the automated data parsing using by Python. The application of automatic sample changers and data parsing technique can solve the problems. The human errors were reduced to 0% compared to the previous method by improving the gamma analysis procedure, and working time were also dramatically reduced. This automation of analysis procedure will contribute to reducing the burden of analysis work and reducing human errors through various improvements.

본 연구의 목적은 과거 12년(2010~2021년)간 발생한 상선의 충돌사고 668건을 조사하여 충돌의 원인요인을 조사하고 이를 통계 적으로 분석하여 항해사의 인적과실 예방 충돌회피(HEPCA) 모델을 제안하는 것이다. 중앙해양안전심판원의 통계연보 및 충돌사건 재결서 를 조사하여 상선의 충돌 원인요인 데이터를 수집하고 통계분석 도구인 SPSS를 이용하여 빈도분석을 수행하였다. 1단계 분석으로 상선 충 돌사고 668건을 대상으로 충돌원인을 분석하였고, 2단계 분석에서는 식별된 최대빈도 원인요인을 세부적으로 분석하였다. 분석결과, 충돌 원인은 항해사의 인적과실이 98 %인 것으로 식별되었으며, 빈도 높은 요인 순서는 경계소홀 〉항행법규위반 〉조선 부적절 순이었다. 경계 소홀의 원인 요인은 주로 상대선 초인 후 지속감시 소홀이었으며 상대선박의 존재를 인식하지 못한 원인은 주로 당직시간에 다른 작업을 한 요인이었다. 분석결과를 적용하여 인적과실 예방을 위한 HEPCA 모델을 제안하였고, 이를 재결서의 충돌사건에 적용해보았다. 본 연구결과는 해기사 교육기관 및 실무에서 항해사의 인적과실로 발생하는 충돌사고를 방지하기 위한 교육 자료로 활용이 가능할 것으로 기대된다.

Despite the maritime industry’s significant role in the global economy, maritime accidents are a threat to life at sea and maritime economic performance. Furthermore, the human factor still accounted for as the main factor causing maritime accidents. Every year, many maritime accidents occur in Japan and Hong Kong, with collisions being the most common. In this study, Human Error Assessment and Reduction Technique (HEART) method is applied to the collisions data to identify the common mistakes committed by seafarers by determining the generic task, error-producing conditions and the value of Human Error Probability (HEP). This study aims to find the causes of collision in Japan and Hong Kong, compare them between the two countries, and apply HEART methodology to various maritime accidents. The data was sourced from the maritime accident data report of the Japan Transportation and Safety Board and the Government of the Hong Kong Special Administrative Region of the Marine Department from 2008 to 2016. There are 27 collision cases for Japan and 21 for Hong Kong. In general, human error is the most common factor leading to collisions. In conclusion, in Japan’s collision assessment, fairly simple tasks performed rapidly or with scant attention are identified as the most common generic task. However, in Hong Kong, most of the accidents occur during complex tasks. Japan has 101 EPCs for 27 cases while there are 115 EPCs for 21 cases that occurred in Hong Kong. Both Japan and Hong Kong have the time shortage, inadequate checking of progress, and poor information exchange among seafarers on the bridge as the common error-producing conditions occurred.

Occupational fatal injury rate per 10,000 population of Korea is still higher among the OECD member countries. To prevent fatal injuries, the causes of accidents including human error should be analyzed and then appropriate countermeasures should be established. There was an severe converter furnace accident resulting in five people death by chocking in 2013. Although the accident type of the furnace accident was suffocation, many safety problems were included before reaching the death of suffocation. If the safety problems are reviewed throughly, the alternative measures based on the review would be very useful in preventing similar accidents. In this study, we investigated the converter furnace accident by using human error analysis and accident scenario analysis. As a result, it was found that the accident was caused by some human errors, inappropriate task sequence and lack of control in coordinating work by several subordinating companies. From the review of this case, the followings are suggested: First, systematic human error analysis should be included in the investigation of fatal injury accidents. Second, multi man-machine accident scenario analyis is useful in most of coordinating work. Third, the more provision of information on system state will lessen human errors. Fourth, the coordinating control in safety should be performed in the work conducting by several different companies.

Because the damages of corrosion resulting from the chloride ion are very serious, many research studies have been performed to measure the penetration depth of the chloride ion. However, there is a problem with data selection obtained from collection during experiments. In this study, it appears that the collected data are not conformed to a normal distribution. The result of this study will play a very important role, as a first step for the development and construction of a forecasting system to help determine a reliable service lifetime of marine structures.

In recent years, accident induced by human error is increasing in the chemical plant. Human error analysis of the chemical plant was conducted on the basis of past accident. Some company called by A for the basis of a chemical accident. Factor analysis of human errors was separated in plant operation and work. Agency's work of occupational safety & health was classified into four types. It is based on the work before, during work, recovery work, and discontinue work. It was still separated work of human error by analysis and then was derived factor and issue. The human error factor and priority for accident prevention in the chemical plant is presented.

  Enhanced machine reliability has dramatically reduced the rate and number of railway accidents but for further reduction human error should be considered together that accounts for about 20% of the accidents. Therefore, the objective of this study was t

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.

Basis frame-work's base in a semiconductor industry have gas, chemical, electricity and various facilities in bring to it. That it is a foundation by fire, power failure, blast, spill of toxicant huge by large size accident human and physical loss and damage because it can bring this efficient, connect with each kind mechanical, physical thing to prevent usefully need that control finding achievement factor of human factor of human action. Large size accident in a semiconductor industry to machine and human and it is involved that present, in system by safety interlock defect of machine is conclusion for error of behaviour. What is not construing in this study, do safety in a semiconductor industry to do improvement. Control human error analyzes in human control with and considers mechanical element and several elements. Also, apply achievement factor using O'conner Model by control method of human error. In analyze by failure mode effect using actuality example.

Accident analyses are used to identify common factors contributing to occupational accidents and to give recommendations for accident prevention. In this study we developed a human error analysis system that can be used easily at the industries. This accident analysis system can be used to develop accident prevention programs to reduce human initiated accidents.

The management of safety at sea is based on a set of internationally accepted regulations and codes, governing or guiding the design and operation of ships. The regulations most directly concerned with human safety and protection of the environment are, in general, agreed internationally through the International Maritime Organization(IMO). IMO has continuously dealt with safety problems and, recognized that the human element is a key factor in both safety and pollution prevention issues(IMO, 2010). This paper proposes a human error analysis methodology which is based on the human error taxonomy and theories (SHELL model, GEMS model and etc.) that were discussed in the IMO guidelines for the investigation of human factors in marine casualties and incidents. In this paper, a cognitive process model, a human error analysis technique and a marine accident causal chains focused on human factors are discussed, and towing vessel collision accidents are analyzed as a case study in order to examine the applicability of the human error analysis technique to marine accidents. Also human errors related to those towing vessel collision accidents and their underlying factors are discussed in detail.