• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1447-1452
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• 2022

Seoul Special City, one of the world's top 10 cities and Metro City, has traditional urban manufacturing industries such as printing, sewing, and mechanical metals. Small business owners in these manufacturing clusters have developed in the form of mutual assistance. Due to the nature of the agglomeration site, each process is handled by an individual company. It is difficult for relatively small business owners to prepare order processing services that provide real-time logistics movement information between processes. This paper collects and analyzes existing logistics data for smooth order and delivery of small business owners in package manufacturing and special printing fields We design an artificial intelligence Fulfillment Service Platform system with CRNN, k-NN, and ID3 Decision Tree Algorithm. Through this study, it is expected that it will greatly contribute to increasing sales and improving capabilities by allowing small business owners in integrated areas to use individual orders and delivery customized services through the Cloud network.

• Structural Engineering and Mechanics
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• v.38 no.4
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• pp.443-457
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• 2011

The loss of strength in a structure as a result of cyclic loads over a period of life time is an important phenomenon for the life-cycle analysis. Service loads are accentuated at the areas of stress concentration, mainly at the connection of components. Structural components unavoidably are affected by defects such as surface scratches, surface roughness and weld defects of random sizes, which usually occur during the manufacturing and handling process. These defects are shown to have an important effect on the fatigue life of the structural components by promoting crack initiation sites. The value of equivalent initial flaw size (EIFS) is calculated by using the back extrapolation technique and the Paris law of fatigue crack growth from results of fatigue tests. We try to analyze the effect of EIFS distribution in a multiple site damage (MSD) specimen by using the extended finite element method (XFEM). For the analysis, fatigue tests were conducted on the centrally-cracked specimens and MSD specimens.

• The Journal of Korean Institute for Practical Engineering Education
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• v.5 no.1
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• pp.20-27
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• 2013

The counter balancing is a technique to control a load which is acting to actuator when the load changes from a resistance state to over running state according to the structural change of the load for the case of lifting or carrying a heavy load in industrial site. Even though this technique is frequently used in industrial site, there is no widely known design procedure and educational equipment in home and abroad. Therefore, in this study a new idea was presented to develop an counter balancing educational equipment. The idea was realized through the process of system modeling and simulation, drawing out of design parameters, manufacturing of a prototype. Finally the usefulness of this developed educational equipment was demonstrated by experiments. It is expected that by using this equipment a big help would be given to students who should understand the counter balancing equipment which is frequently encountered in industrial site.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.4
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• pp.109-115
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• 2005

In the study, Methods for operating measures in equipment security to find out dangerousness timely in the system and to need for the prevention and measures. The method for analyzing and reconstructing the causes of accident of equipment in site, and try to save the information of site in real-time and to analyze the state of equipment to look for the factors of accidents. By this analysis, one plan for efficiency of production, Equipment Fault Diagnosis Management and security is integrating and building module of using the Fuzzy Inference based on fuzzy theory. The case study is applied to the industrial electric motors that are necessarily used to all manufacturing equipment. Using the sensor for temperature is attached to gain the site information in real time and to design the hardware module for signal processing. In software, realize the system supervising and automatically saving to management data base by the algorithm based in fuzzy theory from the existing manual input system

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.148-154
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• 2021

We propose the AI Smart Factory Model for integrated management of production processes in this paper .It is an integrated platform system for the production of food packaging containers, consisting of a platform system for the main producer, one or more production partner platform systems, and one or more raw material partner platform systems while each subsystem of the three systems consists of an integrated storage server platform that can be expanded infinitely with flexible systems that can extend client PCs and main servers according to size and integrated management of overall raw materials and production-related information. The hardware collects production site information in real time by using various equipment such as PLCs, on-site PCs, barcode printers, and wireless APs at the production site. MES and e-SCM data are stored in the cloud database server to ensure security and high availability of data, and accumulated as big data. It was built based on the project focused on dissemination and diffusion of the smart factory construction, advancement, and easy maintenance system promoted by the Ministry of SMEs and Startups to enhance the competitiveness of small and medium-sized enterprises (SMEs) manufacturing sites while we plan to propose this model in the paper to state funding projects for SMEs.

• Nuclear Engineering and Technology
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• v.56 no.1
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• pp.222-232
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• 2024

New modular factory-built methodologies implemented in the construction and industrial plant industries may bring down costs for modular reactors. A factory-built environment brings about benefits such as; improved equipment, tools, quality, shift patterns, training, continuous improvement learning, environmental control, standardisation, parallel working, the use of commercial off shelf equipment and much of the commissioning can be completed before leaving the factory. All these benefits combine to reduce build schedules, increase certainty, reduce risk and make financing easier and cheaper.Currently, the construction and industrial chemical plant industries have implemented successful modular design and construction techniques. Therefore, the objectives of this paper are to understand and analyse the state of the art research in these industries through a systematic literature review. The research can then be assessed and applied to modular reactors.The literature review highlighted analysis methods that may prove to be useful. These include; modularisation decision tools, stakeholder analysis, schedule, supply chain, logistics, module design tools and construction site planning. Applicable research was highlighted for further work exploration for designers to assess, develop and efficiently design their modular reactors.

• Journal of the Korea Safety Management & Science
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• v.23 no.4
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• pp.31-42
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• 2021

Recently, virtual reality (VR) and augmented reality (AR) technologies are attracting attention as core technologies in the era of the 4th industrial revolution. These virtual and augmented reality technologies are being used in a variety of industries, including the construction industry, healthcare industry, and manufacturing industry, to innovate in communication and collaboration, education and simulation, customer service and reinvention of the customer experience. In this paper, VR-based experiential safety education was conducted for workers of shipbuilding companies in Ulsan city, and for them, the educational effectiveness such as immersion, site applicability, safety accident prevention, education satisfaction, overall performance, and safety behavior in VR-based safety experience education were measured. In addition, we examined whether the immersion of VR-based safety experience education affects site applicability, safety accident prevention, educational satisfaction, overall performance, and safety behavior. Furthermore, it was analyzed whether site applicability plays a mediating role in the relationship between immersion and safety accident prevention. As a result, it was found that the immersion of VR-based safety experience education affects site applicability, safety accident prevention effect, education satisfaction, overall performance, and safety behavior, and that site applicability mediates between immersion and safety accident prevention. Based on these results, we suggests a direction for the development of VR-based contents in the field of safety and health and the transformation of safety and health education in the future.

• 한국문화재보존과학회:학술대회논문집
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• 2006.11a
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• pp.23-28
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• 2006

• Proceedings of the Korean Institute of Industrial Safety Conference
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• 2001.11a
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• pp.31-35
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• 2001

Recent trends require that access to the device/equipment information be provided from several locations or anywhere in the enterprise. One example is virtual machine/manufacturing system (VMS) where predictive maintenance is performed both on factory floor and in remote site through internet ［1］. Internet access is increasingly available and affordable, and along with the "internet" is the backbone of modern enterprise data networks. Typical functions of such a system includes monitoring and control for diagnosis and remedy action in realizing preventive maintenance.(omitted)

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1243-1244
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• 2022

In recent years, the growing interest in off-site construction has led to factories scaling up their manufacturing and production processes in the construction sector. Consequently, continuous large-scale site monitoring in low-variability environments, such as prefabricated components production plants (precast concrete production), has gained increasing importance. Although many studies on computer vision-based site monitoring have been conducted, challenges for deploying this technology for large-scale field applications still remain. One of the issues is collecting and transmitting vast amounts of video data. Continuous site monitoring systems are based on real-time video data collection and analysis, which requires excessive computational resources and network traffic. In addition, it is difficult to integrate various object information with different sizes and scales into a single scene. Various sizes and types of objects (e.g., workers, heavy equipment, and materials) exist in a plant production environment, and these objects should be detected simultaneously for effective site monitoring. However, with the existing object detection algorithms, it is difficult to simultaneously detect objects with significant differences in size because collecting and training massive amounts of object image data with various scales is necessary. This study thus developed a large-scale site monitoring system using edge computing and a small-object detection system to solve these problems. Edge computing is a distributed information technology architecture wherein the image or video data is processed near the originating source, not on a centralized server or cloud. By inferring information from the AI computing module equipped with CCTVs and communicating only the processed information with the server, it is possible to reduce excessive network traffic. Small-object detection is an innovative method to detect different-sized objects by cropping the raw image and setting the appropriate number of rows and columns for image splitting based on the target object size. This enables the detection of small objects from cropped and magnified images. The detected small objects can then be expressed in the original image. In the inference process, this study used the YOLO-v5 algorithm, known for its fast processing speed and widely used for real-time object detection. This method could effectively detect large and even small objects that were difficult to detect with the existing object detection algorithms. When the large-scale site monitoring system was tested, it performed well in detecting small objects, such as workers in a large-scale view of construction sites, which were inaccurately detected by the existing algorithms. Our next goal is to incorporate various safety monitoring and risk analysis algorithms into this system, such as collision risk estimation, based on the time-to-collision concept, enabling the optimization of safety routes by accumulating workers' paths and inferring the risky areas based on workers' trajectory patterns. Through such developments, this continuous large-scale site monitoring system can guide a construction plant's safety management system more effectively.