This study explores the use of a Deep Autoencoder model to predict depression among plant and machine operators, utilizing data from the Korean National Health and Nutrition Examination Survey (KNHANES, n=3,852). The Deep Autoencoder model outperformed the Logistic Regression, Naive Bayes, XGBoost, and LightGBM models, achieving an accuracy of 86.5%. Key factors influencing depression included work stress, exposure to hazardous substances, and ergonomic conditions. The findings highlight the potential of the Deep Autoencoder model as a robust tool for early identification and intervention in workplace mental health.

This study examines factors influencing occupational injuries among plant and machine operators using the Semi-supervised MarginBoost algorithm. Data from the 2007-2009 Korean National Health and Nutrition Examination Survey (KNHANES) were analyzed, covering 4,062 employed participants. The MarginBoost model achieved 84.3% accuracy, outperforming other models. Key factors identified included exposure to hazardous substances, ergonomic conditions, and psychosocial stress. The findings emphasize the need for targeted interventions to enhance workplace safety and offer a robust predictive tool for the effective management of occupational health.

Considering the difficulties of the manufacturing industry by improving production efficiency in the era of high wages and aging in domestic automation facilities, automation facilities are considered an irreversible trend, but many serious related disasters are occurring due to the problems of increasing automation facilities due to the enlargement of manufacturing processes, line-up, and automation. The purpose of this study is to review the usage conditions and safety measures for industrial robots that are experiencing serious industrial accidents and are expected to continue to increase in facilities among automation facilities at the automation industrial site and propose ways to ensure the fundamental safety of the facilities at all times The suggestions are as follows. The purpose is to prevent safety accidents in advance by applying safety door aids to industrial sites and installing additional safety devices in safety slide door lock systems applied to safety fence doors of new and already installed facilities to detach safety keys and ensure that workers carry them at all times.

In the era of the 4th Industrial Revolution, Logistic 4.0 using data-based technologies such as IoT, Bigdata, and AI is a keystone to logistics intelligence. In particular, the AI technology such as prognostics and health management for the maintenance of logistics facilities is being in the spotlight. In order to ensure the reliability of the facilities, Time-Based Maintenance (TBM) can be performed in every certain period of time, but this causes excessive maintenance costs and has limitations in preventing sudden failures and accidents. On the other hand, the predictive maintenance using AI fault diagnosis model can do not only overcome the limitation of TBM by automatically detecting abnormalities in logistics facilities, but also offer more advantages by predicting future failures and allowing proactive measures to ensure stable and reliable system management. In order to train and predict with AI machine learning model, data needs to be collected, processed, and analyzed. In this study, we have develop a system that utilizes an AI detection model that can detect abnormalities of logistics rotational equipment and diagnose their fault types. In the discussion, we will explain the entire experimental processes : experimental design, data collection procedure, signal processing methods, feature analysis methods, and the model development.

In this study, alternative seismic force-resisting systems for plant structure supporting equipment were designed, and the seismic performance thereof was compared using nonlinear dynamic analysis. One alternative seismic force-resisting system was designed per the requirement for ordinary moment-resisting and concentrically braced frames but with a reduced base shear. The other seismic force-resisting system was designed by accommodating seismic details of intermediate and unique moment-resisting frames and special concentrically braced frames. Different plastic hinge models were applied to ordinary and ductile systems based on the validation using existing test results. The control model obtained by code-based flexible design and/or reduction of base shear did not satisfy the seismic performance objectives, but the alternative structural system did by strengthened panel zones and a reduced effective buckling length. The seismic force to equipment calculated from the nonlinear dynamic analysis was significantly lower than the equivalent static force of KDS 41 17 00. The comparison of design alternatives showed that the seismic performance required for a plant structure could be secured economically by using performance-based design and alternative seismic-force resisting systems adopting minimally modified seismic details.

This paper is to study the technology of inspection and history management systems for wind power that are continuously increasing around the world. In the past, inspections and analysis of major devices in renewable energy system have been operated in an analog way that identifies problems through photography and passive method. To improve this problem, we conduct a study on VR-based inspection history management system using 3D texturing technique of drone image. The paper describes the current status and prospects of wind power, research and development of wind power blade inspection and history management systems, experiments and reviews in the field, and expected effects and future utilization of this technology. It is expected that the latest technology for inspection and management of renewable system will be secured and introduced to the site through the development research of this system to reduce maintenance costs and power generation costs.

The railroad facilities are intended for long-term operation as the initial acquisition costs necessary for infrastructure construction are high. Therefore, regular maintenance of railroad facilities is essential, and furthermore, system reliability through systematic performance evaluation is required. In this study, the signal control system of railroad electrical equipment was selected as the subject of research and the performance evaluation target facility selection study was conducted using AHP. The results of the study can contribute to the reliability of the signal control system as well as to the reliability of the railroad system, which is a higher system.

최근 환경규제가 강화됨에 따라 액화천연가스(Liquefied Natural Gas)를 이용하여 전력을 생산해내는 신규발전설비인 부유식 LNG 발전설비(floating LNG power plant)가 개발되고 있다. 부유식 LNG 발전설비는 운용 시 증발가스가 발생하고 이를 제거하거나 회수할 수 있는 시스템의 설계가 필요하다. 그러나 해양플랜트는 해상요건에 따라 설계가 상이하고, 부유식 LNG 발전설비의 설계 전 시행착오를 줄이기 위해 지속적으로 수정이 가능한 BOG 회수시스템 공정모사 모델이 필요하다. 따라서 본 연구에서는 상용공정시뮬레이션 프로그램을 통해 부유식 LNG 발전설비에 적합한 모델을 모델링하고자 냉매사용 유무에 따라 서로 다른 BOG(Boil-Off Gas) 회수시스템을 모델링하여 BOG의 회수율과 액화점을 비교 및 분석하였으며, 그 결과 질소냉매를 사용한 BOG 회수시스템 모델을 부유식 LNG 발전설비용 BOG 회수시스템 모델로 제안하고자 한다.

Pumps for hazardous materials handling areas of self service stations are still scattered in the country, generator room, engine room of the small vessels, etc. are installed inside buildings against big is the risk of fire extinguishers are installed only. These facilities are in severe climate change because it is an open space area, as well as a water based fire extinguishers may not be suitable for that type of gas extinguishing system is also adaptable. This study features a compressed air port operation principles and characteristics, equipment, fire extinguishers, which can minimize the casualties and property losses from fire against hazardous substances in small business, design requirements, domestic contain fire extinguishers laws and foreign Compression Four fire extinguishers through the air and foreign regulations comparative analysis of the compressed air port installations such as fire extinguishers and applied to study the measures to be included are fire extinguishers installed in the country. Climate change is a big country review In winter, water based fire extinguishers are also concerned about the freeze, but compared to the foreign installations were exploring ways to work in the country. CAF is especially preferred that the fire extinguishing performance and to demonstrate the protective space as there is a risk of frost risk significantly less compressed air port digestion plant.