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제조 실행 시스템 기반 정밀 가공 생산 시스템 연구

Research on Precision Processing Production System based on Manufacturing Execution System

  • 신성욱 (한국공학대학교 IT반도체공학과) ;
  • 이현무 (한국공학대학교 나노반도체공학과) ;
  • 박승호 (한국공학대학교 IT반도체공학과)
  • Seong-Uk Shin (Department of IT Convergence Semi-Conductor Engineering, Tech. University of Korea) ;
  • Hyun-Mu Lee (Department of Nano Semi-Conductor Engineering, Tech. University of Korea) ;
  • Seung-Ho Park (Department of IT Convergence Semi-Conductor Engineering, Tech. University of Korea)
  • 투고 : 2023.11.24
  • 심사 : 2023.12.28
  • 발행 : 2023.12.28

초록

본 논문에서는 중소 규모의 정밀 가공 기업에 대한 생산 가공의 개선을 위하여 기존 공정 방식에 제조 실행 시스템을 적용하고 정밀가공의 데이터를 통합하였다. 이에 따른 기업 내 공정 관리 시스템의 강화, 장비 운용 효율의 증대, 불량률 감소를 통한 생산성 향상 및 작업 공수 감소에 따른 원가 절감률의 차이를 비교 분석하였다. 그 결과 제조 실행 시스템 도입으로 인해 생산 업무 생산성이 7.0% 향상되었고, 제품 불량률은 0.1%p 개선되었다. 제조원가 절감은 10.0%, 납기 준수율은 1.1% 개선되었음을 확인하였다. 추후 본 연구에서 제안한 제조 실행 시스템을 기반으로 추가적인 스마트팩토리 기술을 적용하는 경우 PQCD 지표의 상승으로 인한 가공 산업의 매출 및 이익 증대가 예상된다.

In this paper, in order to improve production processing for small and medium-sized precision processing companies, we apply a manufacturing execution system to existing process methods and integrate precision processing data to strengthen process management within the company, increase facility operation efficiency, and realize a reduction in defect rates. The differences in productivity improvement and cost reduction rates were compared and analyzed. As a result, production productivity improved by 7.0% and product defect rate improved by 0.1% point due to the introduction of the manufacturing execution system. It was confirmed that manufacturing cost reduction improved by 10.0% and delivery compliance rate improved by 1.1%. If additional smart factory technology is applied based on the manufacturing execution system proposed in this study in the future, sales and profits in the processing industry are expected to increase due to an increase in the PQCD index.

키워드

과제정보

This work was supported by the Korea Environmental Industry & Technology Institute(KEITI) funded by the Ministry of Environment(MOE) (Training DX-based carbon supply network environmental experts). This work was supported by the Korea Institute of Energy Technology Evaluation and Planning(KETEP) and the Ministry of Trade, Industry & Energy(MOTIE) of the Republic of Korea (No. 20224000000200).

참고문헌

  1. Y. Yoon. (2020). Technology Innovation, Decentralization and Creativity in the Era of the 4th Industrial Revolution. Journal of Culture Industry, 20(3), 23-33 DOI : 10.35174/JKCI.2020.09.20.3.23 
  2. J. W. Byun. (2021). Analysis and Implications of Smart Factory Policy in the 4th Industrial Revolution: Case Studies of Germany and the USA. Journal of Culture Industry, 21(3), 143-150 DOI : 10.35174/JKCI.2021.09.21.3.143 
  3. B. K. Oh. (2018). An Analysis on Adapted Relative Rankings using the Fourth Industrial Revolution Categories among the Regions of South Korea. Journal of Industrial Economics and Business, 31(1), 275-292 DOI : 10.22558/jieb.2018.02.31.1.275 
  4. H. Lim & C.K. Suh. (2022). Visualization of the Intellectual Structure on the Internetof Things Focuses on the Industry 4. Journal of the Korea Industrial Information Systems Research, 27(6), 127-140 DOI : 10.9723/jksiis.2022.27.6.127 
  5. H. Yang. (2020). Policy Measures for Revitalizing the Artificial Intelligence-Based Smart Factory. The Journal of Korean Institute of Communications and Information Sciences, 45(9), 1659-1665 DOI : 10.7840/kics.2020.45.9.1659 
  6. J. Lim, D. Jo, S. Lee, H, Park & J. Park. (2017). A Case Study for the Smart Factory Application in the Manufacturing Industry. Korean Journal of Bussiness Administration, 30(9), 1609-1630 DOI : 10.18032/kaaba.2017.30.9.1609 
  7. H. Kim. (2020). A Study of the Effect of Smart Factory Quality on Efficiency and Utilization, Journal of Korean Corporation Management Association, 27(4), 145-161 DOI : 10.21052/KCMR.2020.27.4.08 
  8. Y. J. Park. (2020). A study on the improvement of mold production system by applying smart factory. Master dissertation. Korea Polytechnic University. Siheung. 
  9. H. G. Kim. (2019). An Empirical Study on Continuous Use Intention and Switching Intention of the Smart Factory. Journal of Korea Society of Industrial Information Systems, 24(2), 65-80 DOI : 10.9723/jksiis.2019.24.2.065 
  10. B. W. Jeon, K.Y. Shin, D.G. Hong & S.H. Suh. (2015). A Study on Application of Systems Engineering Approach to Design of Smart Manufacturing Execution System. Journal of the Korea Society of Systems Engineering, 11(2), 95-105 DOI : 10.14248/JKOSSE.2015.11.2.0 
  11. Y. K. Kim, M. S. Kang & B. K. Kim. (2002). Design and Implementation of Web-based Factory Monitoring System for Complement MES. Journal of KIPS Transactions on Software and Data Engineering, 9(4), 667-676 DOI : 10.3745/KIPSTD.2002.9D.4.6 
  12. J. B. Go, G. H. Kim, & I. S. Yun. (2003). The Study on Ultra-Precision Cutting Characteristics Evaluation of Non-Ferrous Metals Using Attractor Quadrant Method. Journal of the Korean Society for Precision Engineering, 20(6), 20-26. 
  13. M. K. Park & B. G. Lee. (2018). A Study on the Structural Analysis of the Spindle of Swiss Turn Type Lathe for Ultra Precision Convergence Machining. Journal of the Korea Convergence Society, 9(5), 145-150 DOI : 10.15207/JKCS.2018.9.5.145 
  14. K. Lee, K. H. Ko, Y. H. Huh, C. J. Park & L. R. Cho. (2022). Effect of milling and sintering process on integrity of zirconia prosthesis: a literature review. Journal of Dental Rehabilitation and Applied Science 38(3), 127-137. DOI : 10.14368/jdras.2022.38.3.127 
  15. K. Lee, S. Park, S. H. Sung & D. Park. (2019). A Study on the Prediction of CNC Tool Wear Using Machine Learning Technique. Journal of the Korea Convergence Society, 10(11), 15-21 DOI : 10.15207/JKCS.2019.10.11.015