터널과지하공간 (Tunnel and Underground Space)

  • 제32권1호
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  • Pages.78-92
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  • 2022
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  • 1225-1275(pISSN)
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  • 2287-1748(eISSN)
한국암반공학회 (Korean Society for Rock Mechanics and Rock Engineering)
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광산 현장의 스마트 마이닝 기술 수준 진단평가 모델 개발

Development of Smart Mining Technology Level Diagnostics and Assessment Model for Mining Sites

  • 박세범 (부경대학교 에너지자원공학과) ;
  • 최요순 (부경대학교 에너지자원공학과)
  • Park, Sebeom (Department of Energy Resources Engineering, Pukyong National University) ;
  • Choi, Yosoon (Department of Energy Resources Engineering, Pukyong National University)
  • 투고 : 2022.01.24
  • 심사 : 2022.02.21
  • 발행 : 2022.02.28
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초록

본 연구에서는 스마트 마이닝 기술의 수준을 체계적이고 구조화된 방법으로 평가할 수 있는 스마트 마이닝 기술 수준 진단평가 모델을 제안하였다. 이를 위해 스마트 마이닝의 성숙도를 정의하였으며, 제조업에서 활용되는 스마트 공장 진단평가 모델(KS X 9001-3)을 참조하여 스마트 마이닝 기술 수준 진단평가 모델의 세부평가항목 도출하였다. 기존의 체계를 유지하면서 기존 46개의 세부평가항목을 광업에 적합하도록 수정하였으며 추진전략, 프로세스, 정보시스템과 자동화, 성과 부문에서 총 29개의 세부 평가 항목을 도출하였다. 이를 토대로 스마트 마이닝 기술 수준 진단평가 설문지를 설계하였고, 국내의 철광산을 연구지역으로 설정한 다음 스마트 마이닝 기술 수준을 평가하였다. 연구지역의 스마트화 수준은 레벨 2로 나타났으며, 일반 제조업의 평균 스마트 수준과 비교했을 때 40% 정도 낮은 수준에 있음을 유추할 수 있었다. 또한, 개발된 모델을 이용하여 스마트 마이닝의 도입, 운영, 고도화의 단계별로 광산의 취약한 부분을 인지하고 투자 및 개선 방향을 제시할 수 있었다.

In this study, we proposed a diagnostics and assessment model for mining sites that can evaluate the smart mining technology level in a systematic and structured way. For this, the maturity of the smart mining was defined, and detailed assessment items of the diagnostics and assessment model for smart mining were derived by considering the smart factory diagnostics and assessment model (KS X 9001-3) used in the manufacturing industry. While maintaining the existing system, the existing 46 detailed assessment items were modified to be suitable for mining. As a result, a total of 29 detailed assessment items were derived in the areas of promotion strategy, process, information system and automation, and performance. Based on this, a questionnaire was designed to diagnose the level of smart mining technology, and assessment was performed by applying it to domestic iron mines. The level of smart mining technology in the study area was found to be level 2, and it could be inferred that it was about 40% lower than the average smart level of the general manufacturing industry. In addition, by using the developed model, it was possible to recognize the weak points of the mine at each stage of the introduction, operation, and advancement of smart mining, and to suggest investment and improvement directions.

키워드

과제정보

본 연구는 2022년도 정부(산업통상자원부)의 재원으로 해외자원개발협회의 지원을 받아 수행되었다(과제명: 자원개발 산학협력 컨소시엄-스마트 마이닝 전문 인력 양성).

참고문헌

  1. Cho, W., 2021, Development of Domestic Standardization in Smart Factory and Manufacturing Data, Journal of the KIECS, 16(5), 783-788.
  2. Hartman, H.L., and Mutmansky, J.M., 2002, Introductory mining engineering, John Wiley & Sons.
  3. Jang, H., 2019, Australian Mining Transformation and Future Prospects in Response to the 4th Industrial Revolution, Journal of the Korean Sociery of Mineral and Energy Resources Engineers, 56(5), 490-513. https://doi.org/10.32390/ksmer.2019.56.5.490
  4. Jung, J., and Choi, Y., 2017, Measuring transport time of mine equipment in an underground mine using a bluetooth beacon system, Minerals, 7(1), 1. https://doi.org/10.3390/min7010001
  5. Kim, H.D., Kim, D.M., Lee, K.G., Yoon, J.W., and Youm, S., 2019, Development of Smart Factory Diagnostic Model Reflecting Manufacturing Characteristics and Customized Application of Small and Medium Enterprises, Journal of the Society of Korea Industrial and Systems Engineering, 42(3), 25-38. https://doi.org/10.11627/jkise.2019.42.3.025
  6. Korean Agency for Technology and Standards, 2016a, Smart Factory-Part 1 : Basic Concepts and Structure, KS X 9001-1.
  7. Korean Agency for Technology and Standards, 2016b, Smart Factory-Part 2 : Terminology, KS X 9001-2.
  8. Korean Agency for Technology and Standards, 2016c, Smart Factory-Part 3 : Operation Management System(Diagnostics and Assessment Model), KS X 9001-3.
  9. Lee, H., Yoo, S.K., and Kim, Y.W., 2019, The Trend of Smart Manufacturing Standardization, TTA Journal, 181, 26-34.
  10. Narendran, T.V., and Weinelt, B., 2019, Digital transformation initiative mining and metals industry, In World Econ. Forum. https://reports.weforum.org/digital-transformation/wp-content/blogs.dir/94/mp/files/pages/files/wef-dti-mining-and-metals-white-paper.pdf.
  11. Park, J.K., and Jung, K.Y., 2020, Construction of Precise Mine Geospatial Information and Ore Modeling for Smart Mining, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, 38(6), 725-731. https://doi.org/10.7848/KSGPC.2020.38.6.725
  12. Park, S., and Choi, Y., 2021a, Bluetooth Beacon-Based Mine Production Management Application to Support Ore Haulage Operations in Underground Mines, Sustainability, 13(4), 2281. https://doi.org/10.3390/su13042281
  13. Park, S., and Choi, Y., 2021b, Analysis and Diagnosis of Truck Transport Routes in Underground Mines Using Transport Time Data Collected through Bluetooth Beacons and Tablet Computers, Applied Sciences, 11(10), 4525. https://doi.org/10.3390/app11104525
  14. Park, Y.K., Song, H.D., and Woo, Y.S., 2017, A Study on Industry 4.0 and Standardization for Smart Factory in Korea, Journal of Standards and Standardization, 7(3), 79-85.
  15. So, B.E., and Shin, S.S., 2017, The Built of Smart Factory Using Sensors and Virtual Process Design, Journal of the KIECS, 12(6), 1071-1080.
  16. Woo, J.H., Chung, H., and Kim, Y.M., 2018, A Study on Smart Factory Diagnostics for Smart Shipyard Construction, Bulletin of the Society of Naval Architects of Korea, 55(4), 16-23.