• Title/Summary/Keyword: Smart Factory Platform

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The Convergence between Manufacturing and ICT: The Exploring Strategies for Manufacturing version 3.0 in Korea (제조업과 정보통신기술의 융합: 스마트 팩토리 4.0에 기반한 한국 제조업 3.0 성공 전략)

  • Yim, Myung-Seong
    • Journal of Digital Convergence
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    • v.14 no.3
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    • pp.219-226
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    • 2016
  • The aim of this study is to suggest the strategic implications for manufacturing 3.0 in Korea by reviewing an innovation approaches of German that is a source of manufacturing innovation in Europe. Today, growth potential of korean economy has been weakened by the rise of emerging economies. Furthermore, technological advantage of emerging economies has been strengthened. In this situation, Korea needs to make efforts to enhance global competitiveness. The growth of developing countries provides a new opportunities for Korea for export demand. However, this situation can be recognized as threats for Korea because Korea has to compete with those countries to expand market share. In this regard, reviewing the approaches of manufacturing innovation in German is important because German keeps remaining a high levels of competitiveness in spite of a rise of emerging economies and European recession. To do this, this research can give hints to advance the industrial policy improvements.

Design and Implementation of a Real-Time Product Defect Detection System based on Artificial Intelligence in the Press Process (프레스 공정에서 인공지능기반 실시간 제품 불량탐지 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.9
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    • pp.1144-1151
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    • 2021
  • The pressing process is a compression process in which a product is made by applying force to a heated or unheated material to transform it into the desired shape. Due to the characteristics of press equipment that produces products through continuous compression for a short time, product defects occur continuously, and systems for solving these problems are being developed using various technologies. This paper proposes a real-time defect detection system based on an artificial intelligence algorithm that detects defects. By attaching various sensors to the press device, the relationship between equipment status and defects is defined and collected based on a big data platform. By developing an artificial intelligence algorithm based on the collected data and implementing the developed algorithm using an embedded board, we will show the practicality of the system by applying it to the actual field.