This study analyzes the importance-performance analysis (IPA) of the 10 dimensions of the smart construction safety management system, and analyzes which dimensions are important and which dimensions are performing to determine key improvement tasks, incremental improvement tasks, Maintenance and reinforcement tasks and continuous maintenance tasks were derived. Among the 10 dimensions of the smart construction safety management system, the dimensions that are recognized as important by all field managers and field workers and have high performance are the automatic risk displacement measurement system, smart environmental sensor system, and heavy equipment seizure prevention system. However, areas that were perceived as having high importance but low performance were worker location tracking systems, smart safety helmet chin muscles, and smart safety ring fastening. Among the smart construction safety management systems perceived by field managers, areas for key improvement with high importance and low performance included worker location tracking system and smart safety ring fastening. Among the smart construction safety management systems perceived by field workers, the area for key improvement with high importance and low performance was the automatic risk displacement measurement system.

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.

The need for an intelligent information-based ship accident prevention and control system for various marine accidents is very clearly emerging. As it is a variety of marine accidents, the causes are diverse. Therefore, it can be said that it is very important to prevent these marine accidents and their causes in advance. Therefore, a study was conducted on an intelligent information-based ship safety management decision support system that provides information necessary for decision-making at sea and land through an integrated management device for ships that informs safety-related risks in real-time ship operation. In the future, we intend to pursue the development of a system that can aim for safer and more economical ship operation by linking it to navigation instruments through the evaluation and analysis of AI, IoT, and big data.

This study examined the certification effects of safety and health management system (SHMS) on the establishment level of SHMS and accident statistics in construction industry. This study obtained the establishment level of SHMS for 106 construction companies surveyed from our previous study. In addition, three major accident statistics (mortality rate, accidental mortality rate, and injury rate) for the companies were collected from the database in Korean Occupational Safety and Health Agency. The statistical analysis results revealed that the establishment level for SHMS certified companies was significantly higher than those for uncertified or certification preparing companies. Furthermore, SHMS certified companies showed significantly smaller accident statistics compared to uncertified or certification preparing companies. The results of this study support the positive effects of SHMS on reducing major industrial accidents in construction companies.

There has been a steady rate of accident in Coal Thermal Power Plants which have relatively higher chance of mortality. However, neither the systematic view of safety management nor the methodology such as safety factors or system requirements are yet to be studied in detail. Therefore, this study aims to propose a methodology to preemptively deal with safety issues and to secure fact focused responsibility in safety. It consists of two main parts. First, the Safety Measurement Index(SMI) with total 50 factors is proposed by analyzing the key factors that contribute to safety accidents based on failure mode and effect analysis (FMEA) and quality function deployment (QFD). To analyze the safety requirements, index presented by major countries and organizations are discussed. Second, main features of intelligent CCTV are studied to determine their relative importance for the framework of Smart Safety Management System (SSMS). Main features are discussed with four technological steps. Also, QFD was held to analyze to analyze how key technologies deal with Quality Measurement Index(QMI). The research results of this study reveal that scientific approaches could be utilized in integrating CCTV technologies into a smart safety management system in the era of Industry 4.0. Moreover, this reasearch provides an specific approach or methodology for dealing with safety management in Coal Thermal Power Plant.

1996년도를 기점으로 공정안전관리제도는 화재·폭발 및 독성물질 누출사고를 예방하자는 목적으로 시작되었다. 현재는 정유, 석유화학 등 업종대상 사업장과 유해·위험물질 51종을 규정량 이상 사용하는 사업장 대상으로 나뉘며 총 2,000여개 사업장에 현재 적용중이다. 또한 전국 6군데 주요 화학공장 밀집 지역을 기반으로 중대산업사고예방센터를 운영하는 등 중대산업사고를 예방하기 위한 정부차원의 다양한 노력이 진행되고 있다. 덕분에 관련사고의 감소는 물론 수십명의 사상자를 야기하는 초대형 사고를 예방할 수 있는 기반과 대상 사업장에서 안전관리 체계를 구축 할 수 있는 계기가 되었다. 하지만 안타깝게도 매년 10여건의 중대산업사고가 발생하고 있는 점은 간과할 수 없는 현실이다. 따라서 본 연구에서는 현행제도를 보다 최신화하기 위한 첫 걸음으로 사고유발 인적요인을 분석해내고 최근 시작되고 있는 증강현실, 사물인식 기술 등과의 융합을 통한 차세대 공정안전관리 시스템에 대해서 검토하고자 한다.

This study aims to provide a real-time information to the driver by effectively operating the advanced safety device attached to the freight vehicle, thereby minimizing insecure behavior of the driver such as speeding, rapid acceleration, sudden braking, And improve driving habits to prevent accidents and save energy. Advanced safety equipment is a device that warns the driver that the vehicle leaves the driving lane regardless of the intention of the driver and reduces the risk of traffic accidents by mitigating or avoiding collision by detecting a frontal collision during driving.The main contents of this report are as follows: In case of installing a warning device on a lane departing vehicle (excluding a light vehicle) and a lorry or special vehicle with a total weight exceeding 3.5 tonnes, the driver must continue to operate unless the driver releases the function.In addition, when the automatic emergency braking system is installed, the structure should be such that the braking device is operated automatically after warning the driver when the risk of collision with the running or stopped vehicle in the same direction is detected in front of the driving lane.

This study aims to provide a real-time information to the driver by effectively operating the advanced safety device attached to the freight vehicle, thereby minimizing insecure behavior of the driver such as speeding, rapid acceleration, sudden braking, And improve driving habits to prevent accidents and save energy. Advanced safety equipment is a device that warns the driver that the vehicle leaves the driving lane regardless of the intention of the driver and reduces the risk of traffic accidents by mitigating or avoiding collision by detecting a frontal collision during driving.The main contents of this report are as follows: In case of installing a warning device on a lane departing vehicle (excluding a light vehicle) and a lorry or special vehicle with a total weight exceeding 3.5 tonnes, the driver must continue to operate unless the driver releases the function.In addition, when the automatic emergency braking system is installed, the structure should be such that the braking device is operated automatically after warning the driver when the risk of collision with the running or stopped vehicle in the same direction is detected in front of the driving lane.

It is a system that supports efficient sharing of information by real-time communication through application and web-based collaborative work space. IOT / ICT technology into the construction site to manage the entire process in real time. It is possible to predict and prevent accidents by using real time accumulated big data information, and it is necessary to diversify research using data.

As the demand for automation (or autonmation) or clean workplace has grown, the interest in the knowledge and skill regarding safety is rising in manager duty. Moreover, the importance of severity rate of injury has increased due to the enlargement of industry scale, even safety management area has developed. Thus, it is important that production managers, the core of the line process, realize the safety in their production line, even if a safety manager acts as a staff. However, in the duty oriented National Competency Standard (NCS), the education about the safety duty of production management part is insufficient. According to NCS, it is calculated production managers receive only 6.7% of whole safety education regarding the duty related the safety management for production manager in mechanical industry. However, the ability in safety is more demanded from production managers as the concept of “production and safety” turns into the concept of “production with safety”. And then in this paper, we will compare and analyze the safety management duty in Korean NCS and the safety management duty in State Leaders Connecting Learning to Work in US manufacturing industry, in terms of the duty of the production manage in mechanical industry (05). And, we will develop the safety duty education system for production manager, by classifying the safety education in domestic mechanical industry into knowledge education, skill education, and attitude education with using AHP(Analytic Hierarchy Process).