• Title/Summary/Keyword: Smart-Factory

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Analysis of Vulnerability of Devices in Smart Factory (스마트 팩토리 디바이스의 보안 취약성 분석)

  • Lee, Yong-Joo;Woo, Sung-Hee
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2018.05a
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    • pp.503-506
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    • 2018
  • The concern about Smart Factory has increased according to the 4th revolution. The number of security threats targeting Smart Factory devices has increased over the last years and it is possible to cause the vulnerability of security about industry secret data. In this paper, we devide security requirements into four and analyze security vulnerability of Smart Factory devices and describe the attack type newly happened.

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The Success of Smart Factory Adoption: Firm's Dynamic Capability Perspective

  • Kim, Gyeung-min;Nam, Mi-Jeong
    • Journal of Information Technology Applications and Management
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    • v.28 no.4
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    • pp.45-57
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    • 2021
  • This research explores how the success of smart factory adoption is influenced by firm's dynamic capability. This research describes the underlying processes on how organizations manipulate or adapt organizational elements harmoniously to implement smart factory successfully. Although understanding of these processes is essential to many researchers and practitioners in the field, the information system research literature contains very few examples of this type. The research is conducted in the following sequence: first, the concept of dynamic capability is presented followed by research methodology; and then the analyses of case data are presented followed by discussions and future directions. The results of this research show that the firms with higher dynamic capability adopted smart factory more easily through alignment of various organizational elements.

Anomaly Detection of Facilities and Non-disruptive Operation of Smart Factory Using Kubernetes

  • Jung, Guik;Ha, Hyunsoo;Lee, Sangjun
    • Journal of Information Processing Systems
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    • v.17 no.6
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    • pp.1071-1082
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    • 2021
  • Since the smart factory has been recently recognized as an industrial core requirement, various mechanisms to ensure efficient and stable operation have attracted much attention. This attention is based on the fact that in a smart factory environment where operating processes, such as facility control, data collection, and decision making are automated, the disruption of processes due to problems such as facility anomalies causes considerable losses. Although many studies have considered methods to prevent such losses, few have investigated how to effectively apply the solutions. This study proposes a Kubernetes based system applied in a smart factory providing effective operation and facility management. To develop the system, we employed a useful and popular open source project, and adopted deep learning based anomaly detection model for multi-sensor anomaly detection. This can be easily modified without interruption by changing the container image for inference. Through experiments, we have verified that the proposed method can provide system stability through nondisruptive maintenance, monitoring and non-disruptive updates for anomaly detection models.

Design and Implementation of Real Time Device Monitoring and History Management System based on Multiple devices in Smart Factory (스마트팩토리에서 다중장치기반 실시간 장비 모니터링 및 이력관리 시스템 설계 및 구현)

  • Kim, Dong-Hyun;Lee, Jae-min;Kim, Jong-Deok
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.1
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    • pp.124-133
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    • 2021
  • Smart factory is a future factory that collects, analyzes, and monitors various data in real time by attaching sensors to equipment in the factory. In a smart factory, it is very important to inquire and generate the status and history of equipment in real time, and the emergence of various smart devices enables this to be performed more efficiently. This paper proposes a multi device-based system that can create, search, and delete equipment status and history in real time. The proposed system uses the Android system and the smart glass system at the same time in consideration of the special environment of the factory. The smart glass system uses a QR code for equipment recognition and provides a more efficient work environment by using a voice recognition function. We designed a system structure for real time equipment monitoring based on multi devices, and we show practicality by implementing and Android system, a smart glass system, and a web application server.

Developing a Framework for Assessing Smart Factory Readiness of SMEs and Case Study (중소기업을 위한 스마트공장 도입 준비도 진단 체계 개발 및 적용사례연구)

  • Cho, Ji-Hoon;Shin, Wan-Seon
    • Journal of Korean Society for Quality Management
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    • v.47 no.1
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    • pp.1-15
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    • 2019
  • Purpose: The purpose of this study is to support SMEs' introduction of smart factories during the $4^{th}$ Industrial Revolution era. Through this study, we developed the readiness assessment framework for SMEs. This study draws practical implications for improving the readiness of SMEs to introduce smart factories. Methods: Readiness Assessment Framework Design method, Case Studies Analysis Results: This study identified SMEs suitable for smart factories and identified key issues for nonconforming companies. And the diagnostic framework has been determined whether it works in a real-life SME environment. Conclusion: In order to succeed in the smart factory deployment, readiness assessment for SMEs should be performed as necessary. Prior to the introduction of smart factories, quality innovation activities should be carried out according to factory level.

Developing a Classification of Vulnerabilities for Smart Factory in SMEs: Focused on Industrial Control Systems (중소기업용 스마트팩토리 보안 취약점 분류체계 개발: 산업제어시스템 중심으로)

  • Jeong, Jae-Hoon;Kim, Tae-Sung
    • Journal of Information Technology Services
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    • v.21 no.5
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    • pp.65-79
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    • 2022
  • The smart factory has spread to small and mid-size enterprises (SMEs) under the leadership of the government. Smart factory consists of a work area, an operation management area, and an industrial control system (ICS) area. However, each site is combined with the IT system for reasons such as the convenience of work. As a result, various breaches could occur due to the weakness of the IT system. This study seeks to discover the items and vulnerabilities that SMEs who have difficulties in information security due to technology limitations, human resources, and budget should first diagnose and check. First, to compare the existing domestic and foreign smart factory vulnerability classification systems and improve the current classification system, the latest smart factory vulnerability information is collected from NVD, CISA, and OWASP. Then, significant keywords are extracted from pre-processing, co-occurrence network analysis is performed, and the relationship between each keyword and vulnerability is discovered. Finally, the improvement points of the classification system are derived by mapping it to the existing classification system. Therefore, configuration and maintenance, communication and network, and software development were the items to be diagnosed and checked first, and vulnerabilities were denial of service (DoS), lack of integrity checking for communications, inadequate authentication, privileges, and access control in software in descending order of importance.

ASS Design to Collect Manufacturing Data in Smart Factory Environment (스마트 팩토리 환경에서 제조 데이터 수집을 위한 AAS 설계)

  • Jung, Jin-uk;Jin, Kyo-hong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.10a
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    • pp.204-206
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    • 2022
  • Digital twin, which is evaluated as the core of smart factory advancement, is a technology that implements a digital replica in the virtual world with the same properties and functions of assets in the real world. Since the smart factory to which digital twin is applied can support services such as real-time production process monitoring, production process simulation, and predictive maintenance of facilities, it is expected to contribute to reducing production costs and improving productivity. AAS (Asset Administration Shell) is an essential technology for implementing digital twin and supports a method to digitally represent physical assets in real world. In this paper, we design AAS for manufacturing data gathering to be used in real-time CNC (Computer Numerical Control) monitoring system in operation by considering manufacturing facility in smart factory as assets.

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ICT-Based Smart Farm Factory Systems through the Case of Hydroponic Ginseng Plant Factory (수경인삼 식물공장 사례를 통한 ICT 기반 스마트 팜 팩토리 시스템)

  • Hwang, Sung-Il;Joo, Jong-Moon;Joo, Seong-Yong
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.40 no.4
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    • pp.780-790
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    • 2015
  • Studies for a plants factory is progressing for cultivating various plants by the needs of the times and industry around world. However most studies is carried out only in lab sized plants factory. It does not consider an economic feasibility. The study for a large scale plants factory is very required to get an economic gain. In this paper we has been studying a smart farm factory based on ICT using the hydroponics ginseng. The smart farm factory is to extend a concept of the general plants factory to full automated factory. The factory can collect the information about growing of plants and automate operating and management of factory like the existing plants factory. Also it is the total plants factory management system, which analyzes the collected information for optimized growth and development of plants and applies the result to the system back.

Convergence Security Technology of OPC-UA Protocol Gateway based on DPI & Self-Similarity for Smart Factory Network (스마트 팩토리 망에서 DPI와 자기 유사도 기술 기반의 OPC-UA 프로토콜 게이트웨이 융합 보안 기술)

  • Shim, Jae-Yoon;Lee, June-Kyoung
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.26 no.5
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    • pp.1305-1311
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    • 2016
  • The smart factory, a combination of ICT technology to the entire production process of a product, means can you intelligent factory is to achieve such reduction and process improvement of the production cost. To implement the smart factory, inevitably must have an internal equipment connections to the external network, this is by equipment which is operated by the existing closure network is exposed to the outside network, the security vulnerability so that gender is increased. In order to solve this problem, it is possible to apply security solutions that are used in normal environments. However, it is impossible to have just completely blocking security threats that can occur in a smart factory network. Further, considering the economic damage that can occur during security breach accident, which cannot be not a serious problem. Therefore, in this paper, a look to know the security measures that can be applied to smart factory, to introduce the main fusion security technology necessary to smart factory dedicated security gateway.

Major Technologies and Introduction of Smart Factory (스마트 팩토리의 주요기술과 도입사례)

  • Woo, Sung-Hee;Cho, Young-Bok
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2018.05a
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    • pp.487-490
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    • 2018
  • As the fourth industrial revolution 4.0 era arrives, the role of smart factory is emerging, which establishes a communication system between production devices and products through the Internet of Things and optimizes the entire production process. Germany wants to use smart factory technologies and data to upgrade and standardize the industry as a whole to create factories around the world, and the United States is aiming to create new business models and revenue streams by analyzing big data and improving productivity based on the technological prowess and innovation across ICT. In addition, Japan and China are also working to change and upgrade their manufacturing industries through smart factories. Accordingly, Korea is attempting to introduce smart factory based on the production industry 3.0. Therefore, this study describes the industrial trends of the fourth industrial revolution and smart factory and compares the major underlying technologies and introduction cases of smart factory.

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