• Title/Summary/Keyword: smart factory utilization

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Implementation of Smart Automatic Warehouse to Improve Space Utilization

  • Hwa-La Hur;Yeon-Ho Kuk;Myeong-Chul Park
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.10
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    • pp.171-178
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    • 2023
  • In this paper, we propose a smart automated warehouse to maximize space utilization. Previous elevator-type automatic warehouses were designed with a maximum payload of 100kg on trays, which has the problem of extremely limiting the number of pallets that can be loaded within the space. In this paper, we design a smart warehouse that can maximize space utilization with a maximum vertical stiffness of 300kg. As a result of the performance evaluation of the implemented warehouse, the maximum payload was 500.6kg, which satisfied the original design and requirements, the lifting speed was 0.5m/s, the operating noise of the device was 67.1dB, the receiving and forwarding time of the pallet was 36.92sec, the deflection amount was 4mm, and excellent performance was confirmed in all evaluation items. In addition, the PLC control method, which designs the control UI and control panel separately, was integrated into the PC system to improve interoperability and maintainability with various process management systems. In the future, we plan to develop it into a fully automatic smart warehouse by linking IoT sensor-based logistics robots.

Development of Distributed Smart Data Monitoring System for Heterogeneous Manufacturing Machines Operation (이종 공작기계 운용 관리를 위한 분산 스마트 데이터 모니터링 시스템 개발)

  • Lee, Young-woon;Choi, Young-ju;Lee, Jong-Hyeok;Kim, Byung-Gyu;Lee, Seung-Woo;Park, Jong-Kweon
    • Journal of Digital Contents Society
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    • v.18 no.6
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    • pp.1175-1182
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    • 2017
  • Recent trend in the manufacturing industry is focused on the convergence with IoT and Big Data, by emergence of the 4th Industrial Revolution. To realize a smart factory, the proposed system based on MTConnect technology collects and integrates various status information of machines from many production facilities including heterogeneous devices. Also it can distribute the acquisited status of heterogeneous manufacturing machines to the remote devices. As a key technology of a flexible automated production line, the proposed system can provide much possibility to manage important information such as error detection and processing state management in the unmanned automation line.

A Study of Resource Utilization Improvement on Cloud Testing Platform

  • Kuo, Jong-Yih;Lin, Hui-Chi;Liu, Chien-Hung
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.7
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    • pp.2434-2454
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    • 2021
  • This paper developed the software testing factory-cloud testing platform (STF-CTP) to address the software compatible issues in various smart devices. Software developers who only require uploading the application under test (AUT) and test script can test plenty of smart devices in STF-CTP. The challenge for the cloud test platform is how to optimize the resource and increase the performance in the limited resource. This paper proposed a new scheduling mechanism and a new process of the system operation which is based on the OpenStack platform. We decrease about 40% memory usage of OpenStack server, increase 3% to 10% Android device usage of STF-CTP, enhance about 80% test job throughput and reduces about 40% test job average waiting time.

Development of Smart Warehouse (스마트 적재창고 개발에 관한 연구)

  • Hwa-La Hur;Yeon-Ho Kuk;Myeong-Chul Park
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2023.07a
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    • pp.591-592
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    • 2023
  • 본 논문에서는 다양한 시장 요구사항에 따른 공간적 효율성과 유연한 관리 시스템이 내장된 스마트 적재창고를 제안한다. 적재창고는 공간 활동의 최적화를 요구하는 동시에 높은 수준의 비용 효율성을 갖추어야 한다. 그리고 자동화된 애플리케이션이 기존 창고 및 공급만 운영보다 중요하며 스마트 팩초리와 연계하여 부품 재고파악과 입출고를 효율적으로 담당해야 한다. 본 논문에서는 수직강성을 최대 300kg를 견딜 수 있는 수직형 자동적재창고를 구현한다. 연구의 결과는 스마트팩토리 등의 자동화 장비 구축을 통한 생산성 향상에 도움이 될 것으로 사료된다.

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Intelligent Sensor Technology Trend for Smart IT Convergence Platform (스마트 IT 융합 플랫폼을 위한 지능형 센서 기술 동향)

  • Kim, H.J.;Jin, H.B.;Youm, W.S.;Kim, Y.G.;Park, K.H.
    • Electronics and Telecommunications Trends
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    • v.34 no.5
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    • pp.14-25
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    • 2019
  • As the Internet of Things, artificial intelligence and big data have received a lot of attention as key growth engines in the era of the fourth industrial revolution, data acquisition and utilization in mobile, automotive, robotics, manufacturing, agriculture, health care and national defense are becoming more important. Due to numerous data-based industrial changes, demand for sensor technologies is exploding, especially for intelligent sensor technologies that combine control, judgement, storage and communication functions with the sensors's own functions. Intelligent sensor technology can be defined as a convergence component technology that combines intelligent sensor units, intelligent algorithms, modules with signal processing circuits, and integrated plaform technologies. Intelligent sensor technology, which can be applied to variety of smart IT convergence services such as smart devices, smart homes, smart cars, smart factory, smart cities, and others, is evolving towards intelligent and convergence technologies that produce new high-value information through recognition, reasoning, and judgement based on artificial intelligence. As a result, development of intelligent sensor units is accelerating with strategies for miniaturization, low-power consumption and convergence, new form factor such as flexible and stretchable form, and integration of high-resolution sensor arrays. In the future, these intelligent sensor technologies will lead explosive sensor industries in the era of data-based artificial intelligence and will greatly contribute to enhancing nation's competitiveness in the global sensor market. In this report, we analyze and summarize the recent trends in intelligent sensor technologies, especially those for four core technologies.

A Study on Smart Factory System Design for Screw Machining Management (나사 가공 관리를 위한 스마트팩토리 시스템 설계에 관한 연구)

  • Lee, Eun-Kyu;Kim, Dong-Wan;Lee, Sang-Wan;Kim, Jae-joong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2018.10a
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    • pp.329-331
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    • 2018
  • In this paper, we propose a monitoring system that starts with the supply of raw materials for threading, is processed into a lathe machine, and checks for defects of the product are automatically performed by the robot with Smart Factory technology through assembly and disassembly. Completion check according to the production instruction quantity and production instruction is made by checking the production status according to whether or not the raw material is worn by the displacement sensor, and checking the pitch and the contour of the processed female and male to determine OK and NG. The robotic system acts as a relay for loading and unloading of raw materials, pallet transfer, and overall process, and it acts as an intermediary for organically driving. The location information of the threaded products is collected by using the non-contact wireless tag and the energy saving system Production efficiency and utilization rate were checked. The environmental sensor collects the air-conditioning environment data (temperature, humidity), measures the temperature and humidity accurately, and checks the quality of product processing. It monitors and monitors the driving hazard level environment (overheating, humidity) of the product. Controls for CNC and robot module PLC as a heterogeneous system.

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A Study on Big Data Analysis of Related Patents in Smart Factories Using Topic Models and ChatGPT (토픽 모형과 ChatGPT를 활용한 스마트팩토리 연관 특허 빅데이터 분석에 관한 연구)

  • Sang-Gook Kim;Minyoung Yun;Taehoon Kwon;Jung Sun Lim
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.46 no.4
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    • pp.15-31
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    • 2023
  • In this study, we propose a novel approach to analyze big data related to patents in the field of smart factories, utilizing the Latent Dirichlet Allocation (LDA) topic modeling method and the generative artificial intelligence technology, ChatGPT. Our method includes extracting valuable insights from a large data-set of associated patents using LDA to identify latent topics and their corresponding patent documents. Additionally, we validate the suitability of the topics generated using generative AI technology and review the results with domain experts. We also employ the powerful big data analysis tool, KNIME, to preprocess and visualize the patent data, facilitating a better understanding of the global patent landscape and enabling a comparative analysis with the domestic patent environment. In order to explore quantitative and qualitative comparative advantages at this juncture, we have selected six indicators for conducting a quantitative analysis. Consequently, our approach allows us to explore the distinctive characteristics and investment directions of individual countries in the context of research and development and commercialization, based on a global-scale patent analysis in the field of smart factories. We anticipate that our findings, based on the analysis of global patent data in the field of smart factories, will serve as vital guidance for determining individual countries' directions in research and development investment. Furthermore, we propose a novel utilization of GhatGPT as a tool for validating the suitability of selected topics for policy makers who must choose topics across various scientific and technological domains.

Development of Cyber-Physical Production System based Manufacturing Control System for Aircraft Parts Plant (가상물리제조 기반 항공기 부품공장 생산통제시스템 개발)

  • Kim, Deok Hyun;Lee, In Su;Cha, Chun Nam
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.43 no.1
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    • pp.143-150
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    • 2020
  • To enhance the effectiveness of the FMS (flexible manufacturing system), it is necessary for the manufacturing control system to be upgraded by integrating the cyber and the physical manufacturing systems. Using the CPPS (Cyber-Physical Production System) concept, this study proposes a 4-stage vertical integration and control framework for an aircraft parts manufacturing plant. In the proposed framework, the process controller prepares the operations schedule for processing work orders generated from the APS (advanced planning & scheduling) system. The scheduled operations and the related control commands are assigned to equipments by the dispatcher of the line controller. The line monitor is responsible for monitoring the overall status of the FMS including work orders and equipments. Finally the process monitor uses the simulation model to check the performance of the production plan using real time plant status data. The W-FMCS (Wing rib-Flexible Manufacturing Control & Simulation) are developed to implement the proposed 4-stage CPPS based FMS control architecture. The effectiveness of the proposed control architecture is examined by the real plant's operational data such as utilization and throughput. The performance improvement examined shows the usefulness of the framework in managing the smart factory's operation by providing a practical approach to integrate cyber and physical production systems.

A Study on the Straight Path Prediction Technology of White LED Marker-based AGV in Indoor Environment (실내 환경에서 White LED 마커 기반 무인 운반차의 직진경로 예측 기술 연구)

  • Woo, Deok gun;vinayagam, Mariappan;Kim, Young min;Cha, Jae sang
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.17 no.5
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    • pp.48-54
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    • 2018
  • With the 4th industry era, smart factories are emerging. In the era of multi-product small scale production, unmanned transportation vehicles are rapidly increasing in utilization of unmanned transportation vehicles that carry and arrange goods in the work space. The conventional unmanned vehicle detected its position by using the guided line method and the position based method for indoor location recognition and movement. This method has disadvantages of initial high cost and maintenance / maintenance. In this paper, to solve the disadvantages, the method of predicting the direct path of the unmanned vehicle through the Kalman filter is verified using the white LED marker of the warehouse and the position data and the image data of the white LED marker recognition image. Through this, the reliability of the linear movement which occupies the most part in the lattice structure is secured. It is also expected that the reliance on additional position sensors will also be reduced.

3D Simulation Study to Develop Automated System for Robotic Application in Food Sorting and Packaging Processes (식품계량 및 포장 공정 로봇 적용 자동화 시스템 개발을 위한 3D 시뮬레이션 연구)

  • Seunghoon Baek;Seung Eel Oh;Ki Hyun Kwon;Tae Hyoung Kim
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.16 no.5
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    • pp.230-238
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    • 2023
  • Small and medium-sized food manufacturing enterprises are largely reliant on manual labor, from inputting raw materials to palletizing the final product. Recently, there has been a trend toward smartness and digitization through the implementation of robotics and sensor data technology. In this study, we examined the effectiveness of improvement through 3D simulation on two repetitive work processes within a food manufacturing company. These processes involve workers whose speed cannot match the capacity of the applied equipment. Two manual processes were selected: the weighing and packing process performed by workers after skewer assembly, and the manual batch process of counting randomly delivered frozen foods, packing (both internal and external), and palletizing. The production volume, utilization rate, and number of workers were chosen as verification indicators. As a result of the simulation for improving the 3D process, production increased by 13.5% and 56.8% compared to the existing process, respectively. This was particularly evident in the process of applying palletizing robots. In both processes, as the utilization rate and number of input workers decreased, robots could replace tasks with high worker fatigue, thereby reducing work overload. This study demonstrates the potential to visually compare the process flow improvement using 3D simulations and confirms the possibility of pre-validation for improvement.