• Title/Summary/Keyword: Defect printing

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Analysis of Defective Causes in Real Time and Prediction of Facility Replacement Cycle based on Big Data (빅데이터 기반 실시간 불량품 발생 원인 분석 및 설비 교체주기 예측)

  • Hwang, Seung-Yeon;Kwak, Kyung-Min;Shin, Dong-Jin;Kwak, Kwang-Jin;Rho, Young-J;Park, Kyung-won;Park, Jeong-Min;Kim, Jeong-Joon
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.19 no.6
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    • pp.203-212
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    • 2019
  • Along with the recent fourth industrial revolution, the world's manufacturing powerhouses are pushing for national strategies to revive the sluggish manufacturing industry. Moon Jae-in, the government is in accordance with the trend, called 'advancement of science and technology is leading the fourth round of the Industrial Revolution' strategy. Intelligent information technology such as IoT, Cloud, Big Data, Mobile, and AI, which are key technologies that lead the fourth industrial revolution, is promoting the emergence of new industries such as robots and 3D printing and the smarting of existing major manufacturing industries. Advances in technologies such as smart factories have enabled IoT-based sensing technology to measure various data that could not be collected before, and data generated by each process has also exploded. Thus, this paper uses data generators to generate virtual data that can occur in smart factories, and uses them to analyze the cause of the defect in real time and to predict the replacement cycle of the facility.