In response to the global transition towards carbon neutrality, there's an increasing emphasis on sustainable energy solutions, with offshore wind power playing a crucial role, especially in South Korea. This study presents an AI-based safety management system specifically designed for offshore wind operators. At the heart of this system is a machine learning algorithm that processes sensor data to automatically recognize human behavior and improve the accuracy of predicting worker actions and conditions. Such predictive analytics not only refines the analysis of behavioral patterns, but also increases the effectiveness of accident prevention. The results of this research are expected to significantly improve safety measures in offshore wind facilities and further sustainable energy initiatives.

Determining the number of operators who set up the machines in a human-machine system is crucial for maximizing the benefits of automated production machines. A man-machine chart is an effective tool for identifying bottlenecks, improving process efficiency, and determining the optimal number of machines per operator. However, traditional man-machine charts are lacking in accounting for idle times, such as interruptions caused by other material handling equipment. We present an adjusted man-machine chart that determines the number of machines per operator, incorporating idleness as a penalty term. The adjusted man-machine chart efficiently deploys and schedules operators for the hole machining process to enhance productivity, where operators have various idle times, such as break times and waiting times by forklifts or trailers. Further, we conduct a simulation validation of traditional and proposed charts under various operational environments of operators’ fixed and flexible break times. The simulation results indicate that the adjusted man-machine chart is better suited for real-world work environments and significantly improves productivity.

With the wide use of greenhouses, the working hours have been increasing inside the greenhouse for workers. In the closed ventilated greenhouse, the internal environment has less affected to external weather during making a suitable temperature for crop growth. Greenhouse workers are exposed to organic dust including soil dust, pollen, pesticide residues, microorganisms during tillage process, soil grading, fertilizing, and harvesting operations. Therefore, the health status and working environment exposed to workers should be considered inside the greenhouse. It is necessary to secure basic data on particulate matter (PM) concentrations in order to set up dust reduction and health safety plans. To understand the PM concentration of working environment in greenhouse, the PM concnentrations were monitored in the cut-rose and Hallabong greenhouses in terms of PM size, working type, and working period. Compare to no-work (move) period, a significant increase in PM concentration was found during tillage operation in Hallabong greenhouse by 4.94 times on TSP (total suspended particle), 2.71 times on PM-10 (particle size of 10 μm or larger), and 1.53 times on PM-2.5, respectively. During pruning operation in cut-rose greenhouse, TSP concentration was 7.4 times higher and PM-10 concentration was 3.2 times higher than during no-work period. As a result of analysis of PM contribution ratio by particle sizes, it was shown that PM-10 constitute the largest percentage. There was a significant difference in the PM concentration between work and no-work periods, and the concentration of PM during work was significant higher (p < 0.001). It was found that workers were generally exposed to a high level of dust concentration from 2.5 μm to 35.15 μm during tillage operation.

Since cranes are a kind of complex human-machine systems, it is almost impossible to completely secure safety with current technologies. Therefore, managerial interventions to prevent human errors are needed for safely operating a crane. The Occupational Safety and Health law states that cabin-type crane operators should have crane drivers’ licence and crane-related operators (e.g., pendent-type crane operators, slinging workers) should take a special safety training. However, statistics on industrial accidents showed that fatalities due to crane accidents (185 accidents occurred during 2013~2017) were the highest among hazardous machinery and equipment. To effectively control the crane-related accidents, voices of crane workers need to be analyzed to investigate the current status. This study surveyed perceived causes of crane accidents and status of special safety training for crane workers of 387. The survey revealed that 24.3% of the respondents experienced crane accidents and 31.4% eye-witnessed crane accidents. 79% of the respondents pointed human errors such as improper crane operation and improper slinging as the first cause. Lastly, only 16.7% of the respondents took a professional special safety training; but the rest took lecture-based or incomplete education. The findings of the present study can be applied to improve crane-related policies and special safety training systems.

본 연구는 양계사내에서 작업자의 위치를 예측하기 위해 BLE 비콘을 이용한 위치 서비스 시스템을 제안한다. 애플리케이션을 개발하여 스마트 단말기로 비콘의 데이터를 수집하고, 수집한 데이터를 기반으로 핑거프린트 알고리즘을 이용한 스코어맵을 생성하였다. 작업자의 위치 예측은 스코어맵과 양계사내에서 실시간으로 수집한 데이터를 유사도 알고리즘을 이용하여 예측하였다. 실험대상 양계사에서 작업자 위치를 예측한 결과 일반 데이터는 위치 예측 시 많은 오차와 낮은 정확도를 보이고, 일반데이터에 필터링을 적용한 알고리즘을 적용 시 위치 예측 정확도가 개선됨을 알 수 있다. 따라서 양계사내에서 BLE 비콘을 이용한 위치기반 서비스 제공이 가능함을 확인하였고, 스코어맵 기반 위치 예측 시스템만 적용했을 때 위치예측 결과보다 필터를 적용한 결과가 더 나은 결과를 보였다. 본 연구는 양계사내에서 BLE 비콘을 이용한 위치 예측이 강점을 가질 수 있는 것으로 보인다.

선박은 크고, 복잡한 구조로 되어 있기 때문에 다른 작업자의 위치를 알아내기 어려우며, 특히 작업자가 쓰러진 경우에는 발견하기가 쉽지 않아 신속한 대처가 어렵다. 그리하여, 신체에 디바이스를 부착하는 방법이나 카메라를 이용하여 쓰러짐을 검출하기 위한 연구가 진행되고 있다. 기존의 영상기반 쓰러짐 검출은 사람의 신체부위를 검출하여 쓰러짐을 판단하였으나, 조선소에서는 다양한 복장과 자세로 작업으로 인해 검출하기가 어렵다. 본 논문에서는 쓰러짐 영역 전체를 추출하여 딥러닝 학습으로 선박 작업자의 쓰러짐을 이미지 기반으로 검출하였다. 학습에 필요한 데이터는 조선소의 건조중인 선박에서 쓰러진 모습을 연출하여 획득하였으며, 이미지를 좌우대칭, 크기조절, 회전하여 학습 데이터의 수를 증가하였다. 성능평가는 정밀도, 재현율, 정확도 그리고 오차율로 평가하였으며, 데이터의 수가 많을수록 정밀도가 향상되었다. 다양한 데이터를 보강하면 카메라를 이용한 쓰러짐 검출 모델의 실효성이 향상됨으 로서 안전 분야에 기여할 수 있을 것으로 사료된다.

Korea’s elevator industry is one of the world’s eighth-largest industrial sectors and the third largest in the world by new installations. This year, the number of elevators has exceeded 700,000, and the number of new installations is 30,000-40,000 every year. However, the news of elevator-related accidents is reported continuously through the media and the accident rate is not decreasing. In particular, among the recent accidents related to elevators, accidents related to elevator workers are increasing, causing social problems. This year, the National Assembly’s Environmental Labor Relations Commission’s National Auditors lost five lives a year and 12 elevator workers were killed in fall and stenosis accidents during the installation, maintenance and replacement of the elevators for about two years since 2018. It took place to adopt the representatives of four domestic elevator companies as witnesses. An elevator worker is a collective term for workers involved in the design, manufacturing, installation, replacement, maintenance, inspection, management, and supervision related to the elevator industry, and the related accidents are called elevator worker accidents. Analysis of elevator-related accidents in the past has shown that the fault of the user accounted for 70% of the total, and the fault of the worker accounted for about 2.5%, and the accident occurred to the user or the user due to carelessness of the worker during the lift-related work. Currently, elevator-related accidents are reported by the Korea Elevator Safety Agency under Article 48 of the Elevator Safety Management Act under the Ministry of Interior and Safety. If deemed necessary for the prevention and prevention of recurrence of an elevator accident, the cause and condition of the elevator accident may be investigated. However, the current draft law is limited only to elevators after installation inspection, and is separated from the Ministry of Employment and Labor’s data on accidents occurring in the manufacturing and installation stages related to the elevator industry. This study analyzes the recent safety accidents of elevator workers and prepares safety measures to prevent them through the risk analysis, and also draws out the problems and improvements of the current elevator worker accident investigation to find the elevator worker accident rate that is on the increase trend.

The purpose of this study is to illustrate the design of safety suits based on energy-harvesting technology, particularly targeting street cleaners who must work at night with high mobility. The design focuses on applying lightweight energyharvesting tools and illuminant into the wear. The design development reflects feedback from testers collected via survey constituting a key methodology. The development process has two main stages. Each stage uses a process of design prototyping, internal examination, test sampling, test wearing, and wearers’ feedback via survey that consists of questions on visibility, wearing convenience, and washability. The first stage results show the design of safety suits with energy-harvested LED illuminant inserted and the survey results collected from street cleaners dressed in 4 sample and 80 actual suits in total. Improved based on the first-stage survey results, the second stage designs the suits with detachable energy-harvested EL tape. From these 5 sample and 30 actual second-stage suits, the additional survey indicates that this second-stage design facilitates more visibility and convenience in washing and wearing than the first-stage design. Accordingly, one can expect that this new design can apply not only to safety suits for night workers but also to handicapped or outdoor sportswear applications in the future.

최근 평창 동계올림픽을 준비하기 위해 영동고속도로가 정비 중이다. 뿐만 아니라 과거에도 수 차례 고속도로 확장, 고속도로 보수 등 도로 작업자들이 고속도로 위에서 작업을 하는 일이 많다. 그러나 도로 작업자들의 안전은 보장받지 못하고 있다. 2015년 국정감사 자료를 보면 도로 작업자들이 얼마나 사망 위험에 노출되어 있는지 알 수 있다. 2015년 국정감사에서는 지난 2010년부터 2015년 7월까지 5년간 고속도로 작업구간에서의 사고를 다루는데, 모두 212건의 사고가 발생하였으며 이 중 사망 사고는 79건이 발생한 것으로 나타났다. 고속도로 내 작업장 교통사고 사망률은 2012년 29%, 2013년 41%, 2014년 48%로 지속적으로 증가했으며, 평균 사망률은 37.3%로 작업장 내 교통사고 발생 시에 3명 중 1명은 목숨을 잃는 통계 수치를 기록했다. 이와 같은 통계를 볼 때, 도로 작업자들은 항상 위험한 상황에 노출되고 있다. 사고를 대비하기 위해 도로 작업을 하는 구간 이전부터 교통콘을 세우거나 도로 차단용 싸인카를 이용하여 고속도로 운전자들에게 작업 구간의 위험성을 알리지만, 고속도로 운전자의 전방주시태만, 졸음운전, 음주운전 등으로 사고는 꾸준히 발생한다. 이러한 운전자 부주의에 따른 사고를 예방하기 위해 이동식 방호울타리를 개발하였고, 도로 작업 구간에 이동식 방호울타리를 배치함으로써 도로 작업자들의 상해위험을 예방할 수 있다. 이동식 방호울타리의 안전성 검증은 ㈜스마트에어챔버 자체충돌시험장 실차충돌실험, 시뮬레이션 해석검증실험으로 안전성을 평가하였으며, 개발 제품에 대한 명확한 검증 기준이 없으므로 ‘도로안전시설 설치 및 관리지침 -차량방호 안전시설 편’의 차량 방호울타리 탑승자 보호 성능 평가 기준을 참고하였다 실차충돌실험은 이동식 방호울타리를 배치하고 1300kg 내외 무게의 승용차와 충돌시켜 탑승자 보호 성능 평가 기준을 만족하는지 보았으며, 6번의 실험을 진행하였고 모두 탑승자 보호 성능 평가 기준을 만족하였다. 해석검증실험은 가상의 공간이므로 1300kg 내외 무게의 승용차가 아닌 8t 트럭으로 충돌시켰으며, 이동식 방호울타리와 8t 트럭이 충돌 후 이동식 방호울타리의 변형거리를 알아보았다. 변형거리는 약 571mm 변형되는 것으로 확인되었다. 이번 실차충돌실험과 해석검증실험을 통해서 이동식 방호울타리를 고속도로 작업 구간에 배치 시, 도로 작업자들이 안전하게 작업할 수 있고 사고가 났을 때에도 작업자들이 상해를 입지 않을 것으로 판단되었다.

The efficiency of the purchasing and procurement logistics is important in automotive industry. The rationalization of production system is directly impact on productivity and quality. For this reason importance of logistics is high. Despite we are continuously making effort, our country are still below the level than developed country on logistics efficiency. Rising labor costs is an important factor in increasing logistics costs. So workforce reduction in logistics department is a large part. We deal with A-company inbound logistics, especially procurement logistics in automotive logistics as research object. So in this study we do research on work load balance about workers. We do research on 1,475 kinds of components in procurement process. We applied work load balance algorithm on chassis, final, sequence, trim warehouses workers. According to number of workers and average M/H, algorithm is applied in two ways. After applied work load balance algorithm we reduced numbers of workers from 28 to 20 and improved worker load balance rate from 47.1% to 93.7%