In the past, measures for the reduction of industrial accidents has led the safety and health policy of construction sites by the guidance, supervision and the regulation according to「Occupation Safety and Health Act」handled by Ministry of Employment and Labor (MOEL). Nowadays companies realize that due to the factors such as diversification of employment types, outsourcing of hazardous work, new construction method and complicated types of construction, etc., there is a limit on safety management for construction sites as far as it is passively led by the governmental safety management policy and regulation. In this study, in order to practice the autonomous safety management escaping from the government-led safety management, improvement plans are proposed and applied by analyzing the basic cause of the all kinds of fall accidents that could possibly occur in the apartment construction sites and by verifying the hazardous factors and risks by fields.

목적: 물리 치료사의 업무 중 근골격계 장애를 유발하는 환경 적 요인 및 자세 요인에 대한 실태 조사 및 결과를 분석하고 산업안전공단 근골격계 질환 예방 메뉴얼에 따른 개선 방안을 제시하고 그 결과를 알아보기 위해 실시하였다. 방법: 본 연구에서는 신경계 치료 분야 종사자 30 명, 근골격 치료 분야 종사자 30명, 총 60명을 대상으로 하였다. 측정 방법은 물리 치료사의 치료 영상을 30 분 동안 촬영했다. 작업 자세는 2분 간격으로 15번 절단하여 분석하였다. 평가 도구는 OWAS 및 REBA를 사용한 자세 분석을 사용하였다. 근골격계 및 신경계 대상자들은 문제점을 파악하고 그에 맞는 산업안전공단 근골격계 질환 예방 매뉴얼을 통해 2주간 중재 후 변화를 측정하였다. 결과: 신체 부위 별 유병률과 특징적 분포는 신경계와 근골격계에서 허리 통증의 비율이 가장 높았다. OWAS 기준에 따른 작업 자세 분포는 신경계 분야에서 신체, 다리, 체중, 활동에서 유의한 감소를 보였으며(p <0.05), 근골격계 분야에서 다리와 활동에서 유의한 감소를 보였다(p <0.05). REBA 평가 기준에 따른 근무 태도 분포는 모두 유의한 감소를 보였다(p <0.05). 결론: 본 연구에서는 작업 관련 근골격계 증상 예방을 위한 부적절한 작업 자세 예방 교육의 중요한 기초 자료로 활용될 수 있다. 근골격계 예방 교육을 마련하고 질병을 줄이기위한 환경 적 요인과 자세 요인을 바꾸는 것이 가능할 것으로 보인다.

본 연구에서는 활성탄소를 이용하여 해양환경으로 유출된 침강 HNS를 현장에서 대응하기 위한 기술 개발을 목적으로, 활용 가능한 활성탄소의 조건을 검토하고 예상 소요량을 산출하였다. 입자 크기별 7종의 활성탄소들을 대상으로 침강 속도를 측정하였고, 침강 HNS로 분류된 클로로포름(CHCl3)에 대한 흡착용량을 실험실 규모 실험(lab-scale test)으로 측정하였다. 또한 7종 활성탄소들에 대하여 유해 물질함량과 용출 실험을 실시하여 용출된 유해물질 함량을 정량 분석하였다. 평균 침강속도(Mean particle-settling velocity)는 0.5~8 cm/sec의 범위로 8-20 mesh 경우를 제외하고 입자의 크기가 클수록 침강속도가 빨랐으며, 클로로포름에 대한 흡착효율은 대체로 입자가 작을수록 표면적이 넓어져 증가되었다. 또한 현장 투입 후 2차 오염가능성 확인을 위한 유해물질함량과 용출 실험 실험에서 >100 mesh의 활성탄소는 전함량분석결과가 아연(Zn)과 비소(As)가 수처리제기준보다 높고, 용출실험결과에서도 크롬(Cr), 아연(Zn), 비소(As)가 다른 활성탄소에 비해 높은 농도로 용출되었다. 흡착효율, 침강속도, 유해성분 용출량 등을 종합적으로 고려하여 현장 처리 적용 가능한 활성탄소는 20-60, 20-40, 2mm&down mesh 이었으며, 흡착용량을 최우선으로 판단하여 투입물량을 계산하면 최소 현장 투입 물량은 각각 0.82, 0.90, 1.28 ton/㎘ 이다.

PURPOSES : This study primarily aims to develop and evaluate a Smart Station - a novel underground pipeline measure system - to overcome the challenges of conventional surveying methods. METHODS : This study built two prototypes of the Smart Station. By reflecting issues revealed through the field tests of the first prototype, this study produced the second Smart Station prototype. The organization of the hardware units in the second prototype was reconfigured to maximize its usability for operators in the field. Furthermore, by developing the ‘Digital Twin X’, an integrated Smart Station management software suite, the second prototype was capable of 1) producing a digital workbook for field operators, 2) managing underground pipeline information, and 3) displaying 3-dimensional maps in and around an underground pipeline. The applicability of the second prototype was examined through three field tests conducted in one open space location, where no urban valley effects were expected, and two locations in a downtown area, with urban valley effects. Given the actual field installation of underground pipelines, this study collected data via both conventional surveying methods and the Smart Station to evaluate the performance of the Smart Station. Analyzing the field data, this study examined the data collection time and position accuracy of an underground pipeline measured by the Smart Station. RESULTS : The field test results revealed that both the conventional surveying method and the Smart Station produced similar performances in data collection time and measurement accuracy in the open space test location. However, in the case of downtown locations affected by urban valley effects, the Smart Station achieved 100 % measurement accuracy while the conventional surveying method achieved 93 % accuracy. It was also observed during the field test that no data were collected due to the constraints of the work schedule and various field conditions (e.g., weather and/or traffic congestion). The data collection times at the open space locations were 10 s for both the conventional surveying method and the Smart Station. However, the data collection times at the downtown locations appeared to be 10 s and 360 s by the Smart Station and the conventional surveying methods, respectively, thereby proving that the Smart Station outperforms the conventional method in its measurement efficiency. CONCLUSIONS : It is envisioned that the Smart Station produces higher work efficiency for field operators as it enables them to collect high accuracy data in a timely and quick manner and not only build a database for the collected data but also vividly visualize it in the field. In the future, it is necessary to conduct additional field tests under various conditions for the in-depth investigation of a Smart Station. In addition, it is expected that the Smart Station will be enhanced by coupling augmented reality (AR) technologies.

PURPOSES : The purpose of this study is to measure and analyze the fugitive dust generated by each process through field tests to develop a technology to reduce fugitive dust generated during excavation-restoration work on road pavements. METHODS : The testbed was constructed based on a typical excavation-restoration construction section and comprised five sections for reproducibility and repeated measurements. The excavation-restoration work was divided into pavement cutting, pavement crushing, pavement removal, excavation, and restoration processes and fugitive dust generated by each process was measured. Fugitive dust (TSP, PM10, PM2.5, and PM1) was measured using a GRIMM particle spectrometer, which applies the principle of a light scattering spectrometer and can be measured in real-time. RESULTS : Analyses of the average mass concentration of PM10 generated by the excavation-restoration process are as follows: 1286.3 μg/m³ from pavement cutting, 246.8 μg/m³ from pavement crushing, 697.0 μg/m³ from pavement removal, 747.9 μg/m³ from excavation process, and 350.6 μg/m³ from the restoration process. In addition, the average particle size distribution of the excavationrestoration construction was in the order of PM10~PM2.5 (67 %), PM1 or less (24 %), and PM2.5~PM1 (9 %). The pavement cutting process is characterized by the emission of high concentrations of fugitive dust over a short time, compared to other processes. The pavement crushing process has the characteristic of steadily generating fugitive dust for a long period, although the emission concentration is small. CONCLUSIONS : In this study, it was found that the concentration and characteristics of fugitive dust generated during road pavement excavation-restoration works vary by process and the reduction technology for each process should be developed accordingly.

The fourth industrial revolution encourages manufacturing industry to pursue a new paradigm shift to meet customers' diverse demands by managing the production process efficiently. However, it is not easy to manage efficiently a variety of tasks of all the processes including materials management, production management, process control, sales management, and inventory management. Especially, to set up an efficient production schedule and maintain appropriate inventory is crucial for tailored response to customers' needs. This paper deals with the optimized inventory policy in a steel company that produces granule products under supply contracts of three targeted on-time delivery rates. For efficient inventory management, products are classified into three groups A, B and C, and three differentiated production cycles and safety factors are assumed for the targeted on-time delivery rates of the groups. To derive the optimized inventory policy, we experimented eight cases of combined safety stock and data analysis methods in terms of key performance metrics such as mean inventory level and sold-out rate. Through simulation experiments based on real data we find that the proposed optimized inventory policy reduces inventory level by about 9%, and increases surplus production capacity rate, which is usually used for the production of products in Group C, from 43.4% to 46.3%, compared with the existing inventory policy.