의무 안전교육의 효과성에 관한 연구 : 타워크레인 설치 · 해체 자격 보수교육 사례

문효식,윤여송 한국설비안전학회 2025 한국설비안전학회지 Vol.30 No.4

This study examined the effectiveness of mandatory refresher training for tower crane workers, a high-risk occupation under Korean safety regulations. We compared course satisfaction between participants from the previous curriculum cycle (2020–2024, n=188) and the revised cycle (2025, n=118), and measured learning outcomes through pre- and post-training surveys with 227 revised program participants across self-efficacy, safety knowledge, and regulatory compliance domains. Independent samples t-tests showed significantly increased course satisfaction after curriculum revision, particularly in lecture quality and textbook adequacy. However, paired samples t-tests revealed no significant overall changes in learning outcomes. When participants were divided by pre-training performance levels, the below-mean group showed significant improvements across all domains, while the above-mean group exhibited significant declines. These findings demonstrate that mandatory safety education can enhance satisfaction and learning outcomes, but effectiveness varies by trainees' baseline levels. Results suggest implementing stratified program design with basic competency reinforcement for low-level groups and advanced modules for high-level groups. Study limitations include reliance on self-reported data and absence of long-term outcome measures, indicating need for future longitudinal studies.

정부지원이 중소제조기업 성과에 미치는 영향과 스마트제조 기술 도입의 매개효과

이록 한국설비안전학회 2025 한국설비안전학회지 Vol.30 No.3

This study aims to analyze the impact of government support on the performance of small and medium-sized manufacturing enterprises (SMEs) and to verify the mediating effect of smart manufacturing technology adoption. SMEs face financial, technological, and human resource constraints during digital transformation, and we found that policy support plays a key role in driving manufacturing innovation and performance. This study conducted a survey of SMEs in the southeastern region, using 246 responses for the final analysis. The results were interpreted using structural equation modeling (SEM). The analysis revealed that both government support and smart manufacturing technology adoption had a positive impact on corporate performance, with smart manufacturing technology adoption demonstrating a significant mediating effect in both relationships. Furthermore, the study demonstrated that government support not only directly promoted performance but also indirectly enhanced performance through the adoption of smart manufacturing technology. This suggests that government support goes beyond mere financial assistance and serves as a strategic tool for promoting the internalization of smart manufacturing technology and enhancing competitiveness in SMEs. This provides practical implications for effectively designing government policies and operational strategies to foster a smart manufacturing innovation ecosystem.

모터 생산 열박음 공정에서의 AI 를 활용한 불량검출 효과성 검증에 대한 연구

문명국 한국설비안전학회 2025 한국설비안전학회지 Vol.30 No.3

The purpose of this study is to assess the effectiveness of data management and system performance through AI-based analysis in order to maintain consistent quality and minimize defect rates on shrink fit process of motor production. To achieve this objective, we developed a data collection and storage device specifically designed for the manufacturing processes of motor shrink fit equipment, and data was collected in two phases. The collected data was analyzed using various machine learning models, including KNeighbors Classifier, Gaussian Naive Bayes, Support Vector Machines, Decision Tree Classifier, Logistic Regression, Deep Neural Networks (LSTM), and Random Forest Classification. Evaluation results indicated that all models demonstrated high predictive accuracy. It is anticipated that the application of these models in process management will facilitate effective data-driven management of the finished motors in the future.

조선업 스마트안전 시스템 도입방안에 관한 연구

양세훈,윤여송 한국설비안전학회 2025 한국설비안전학회지 Vol.30 No.3

This study defines the concept of smart safety within the context of the shipbuilding industry and comprehensively analyzes the necessity of its adoption. The core of smart safety lies in overcoming the limitations of existing industrial safety management methods and leveraging Fourth Industrial Revolution technologies to establish a more effective disaster prevention and management system. The convergence of cutting-edge technologies, such as Internet of Things (IoT)-based sensors, artificial intelligence (AI), digital twins, and real-time location systems (RTLS), contributes to proactively managing shipyards unique risks, enhancing worker safety, and enhancing operational efficiency. This report details the technological components of smart safety and its application in the shipbuilding industry, discusses its expected benefits, and presents future development directions and challenges. Through this, it emphasizes that smart safety is no longer an option but a necessity, and provides guidelines for building a safe and productive shipbuilding environment.

스마트제조에 관한 논문의 주제어 연관성 분석

양병학 한국설비안전학회 2025 한국설비안전학회지 Vol.30 No.3

Smart manufacturing is a trend of the times that must be introduced for the survival of the nation and companies. This study analyzed the research on smart manufacturing conducted by Korean companies and researchers through social network analysis. First, we collected papers related to smart manufacturing published in Korea and classified them into qualitative analysis, survey, IT, literature review and quantitative analysis according to their content. Second, as a result of investigating the research techniques used in each paper, the most frequently used techniques were Survey, Software development, Literature review, Hardware development and Case study. Third, the keywords used in the same paper were connected to a network and the correlation between the keywords was visualized. Finally, keywords that have a large influence on other keywords were selected by utilizing the centrality of social network analysis. Keywords with high centrality were selected as Manufacturing innovation, Jacobi Algorithm, Smart Car, Small and Medium-sized Enterprises, Cyber physical system, ICT, 4th Industrial Revolution, IoT, Smart manufacturing, and Smart factory.

철도차량 유지보수 옥상 작업의 추락 위험 요인 분석 및 예방 대책에 관한 연구

박진만,김대민 한국설비안전학회 2025 한국설비안전학회지 Vol.30 No.3

Rooftop work for railway vehicles has a high risk of falling due to its curved structure and narrow space. In order to prevent such a crash, this study identified major risk factors through field survey and work posture analysis, and derived an improvement plan based on this. As a result of the fact-finding survey, major risk factors were non-fixed footholds, non-certified complaint workbench, not wearing protective equipment, and irregular work surfaces. The derived improvement plan consisted of ceiling rail-type safety belts, flexible guard systems, safety difficulties, work mats, and reinforcement of wearing protective equipment. Each improvement plan was designed by comprehensively reviewing legal standards, previous studies, and commercial product cases, and feasibility and safety were reviewed through expert evaluation. As a result of the evaluation, the flexible guard system and the ceiling rail system received the highest score. The proposed plan is expected to be effectively applied not only to railway vehicle maintenance work but also to a similar height work environment.

국내 물류센터 위험요인 분석을 통한 스마트안전관리 추진 방안

갈원모,장미화 한국설비안전학회 2025 한국설비안전학회지 Vol.30 No.3

According to the industrial accident report from January 2022 to March 2023, 17.9% (16,438 cases) of the total 91,662 accidents were related to logistics operations, indicating a higher accident rate compared to other industries. This study aims to analyze task-specific risk factors in logistics centers, compare domestic risk assessment methods, and propose a risk assessment system applicable to logistics centers. Additionally, the research suggests using a smartphone-based safety system to improve logistics safety. This system allows workers to actively participate in safety inspections, effectively reducing risk factors.

인적오류 분석을 통한 작업자 운영정보 실시간 공유방안 연구

구혁서,김태윤,염병수 한국설비안전학회 2025 한국설비안전학회지 Vol.30 No.4

Railway shunting operations, which involve organizing trains within station yards, require complex coordination among local traffic controllers, shunting operators, and shunting planners who share real-time track information to manage train movements. This study analyzes the collaboration structure and information flow among the key operational roles in shunting yards and proposes a practical improvement model to reduce human-error-related incidents. A field-oriented research methodology was applied, including literature review, on-site observations, interviews, accident case analysis, and expert review. The results show that real-time information sharing, rapid communication, and immediate delivery of safety-critical information are essential. The findings emphasize that critical information must be mutually verified and supported by intuitive user interfaces and role-based access control with enhanced data security. This study provides practical implications for improving the safety and efficiency of railway shunting operations through a real-time operational information-sharing system. Future work should include field implementation, technology integration, and empirical validation.

수직형 자동화 컨테이너터미널에서 재배치작업을 반영한 무간섭 이중 ASC의 주기시간 분석

배종욱,이병권,박영만 한국설비안전학회 2025 한국설비안전학회지 Vol.30 No.4

This study investigates the effect of pre-marshalling in container handling on cycle time estimation for various operations of twin Automated Stacking Cranes(ASC). An automated container yard is typically organized into several blocks, with transfer points located at both ends of each block. The blocks are arranged perpendicular to the quay. Twin ASC, which are the primary container-handling equipment installed in each block, perform various operations through interactions with trucks. This study develops cycle time estimation models that incorporate pre-marshalling and compares them to the previous model by Lee and Kim(2007). Additionally, a comparative analysis is conducted to examine the expected cycle times and their variances across different block sizes. Sensitivity analysis reveals the impact of pre-marshalling on reducing cycle times for twin ASC as well as truck waiting times.

딥러닝 기반 도로 손상 탐지를 위한 파이프라인 연구

김재훈,진서훈 한국설비안전학회 2025 한국설비안전학회지 Vol.30 No.4

The rapid and precise automatic detection of road surface damage is a key aspect of efficient road maintenance and safety assurance. This study proposes an integrated deep learning pipeline that precisely detects major damage types using instance segmentation and automatically determines their severity, based on real-world domestic road images. To this end, recent instance segmentation models were comparatively analyzed to select Mask2Former as the optimal model, and a three-stage post-processing algorithm was designed to increase the accuracy of the detection results. Subsequently, an EfficientNet-B0-based binary classifier was applied to classify the severity of detected damages as ‘Caution’ or ‘Severe’, and the classification performance was improved by optimizing the threshold. By establishing an integrated analysis system that simultaneously provides precise damage area information and an objective severity assessment, this study is expected to contribute to the automation of road management systems and the advancement of preventive maintenance systems.