DOI QR코드

DOI QR Code

A Study on the Influence of Automatic Control System on the Production of Chemical Propylene

자동제어 시스템이 케미칼 프로플린 생산에 미치는 영향 연구

  • Lee, Oh Sick (Department of Convergence Technology & Management Engineering, Yonsei University) ;
  • Leem, Choon Seong (Department of Industrial Engineering, College of Engineering, Yonsei University)
  • 이오식 (연세대학교 일반대학원 융합기술경영공학과) ;
  • 임춘성 (연세대학교 공과대학 산업공학과)
  • Received : 2018.12.28
  • Accepted : 2019.02.20
  • Published : 2019.02.28

Abstract

In this study, we analyzed the effects of the automatic control system on the reactor operation. The Propyrene Reactor process is complex and typically is inefficient and costly due to the lack of productivity. In this study, a research model was presented with the aim of supplementing obstacles to enhance operational efficiency and increase productivity. The configuration of the existing processes was analyzed to complement the hardware and software systems with original models. The composition of the facility is applied to eight reactor units producing 600,000 ton/year propylene per year. As a result of applying the research model, efficiency of operation was increased, and production volume increased from 90 to 95%, along with 91% Reliability. Future studies will present a research model to improve productivity by 100 percent. In addition, we will study the stability and productivity improvement of PSA (Pressure Swing Adsorption) systems, which are the hydrogen production process of propylene by-products.

본 연구에서는 자동제어시스템이 리액터 운전에 미치는 영향을 분석해 보았다. Propylene 리액터 공정은 복잡하게 구성되어 일반적으로 효율이 낮고, 생산성이 떨어지는 문제로 인해 경제적 손실이 많다. 본 연구에서는 장애요인을 보완하여 운전효율을 높이고, 생산성을 향상시키는 목적으로 연구 모델을 제시하였다. 기존 공정의 구성을 분석하여 하드웨어 시스템 및 소프트웨어 시스템을 독창성 있는 모델로 보완하였다. 설비의 구성을 연간 60 만톤/Year 프로플린을 생산하는 리액터 8기를 기준으로 적용하였다. 연구 모델 적용결과 운전 효율이 높아졌고, 안정성 91%과 더불어 생산량이 90~95% 으로 증가하였다. 향후 연구는 생산성 100% 향상을 위한 연구모델을 제시할 예정이다. 추가적으로 프로플린 부산물인 수소 생산공정인 PSA 시스템의 안정성과 생산성 향상 방안에 대해 연구하고자 한다.

Keywords

JKOHBZ_2019_v9n2_34_f0001.png 이미지

Fig. 1. Existing System Configuration Model

JKOHBZ_2019_v9n2_34_f0002.png 이미지

Fig. 2. Existing System Logic Model

JKOHBZ_2019_v9n2_34_f0003.png 이미지

Fig. 3. Reactor Propylene Process

JKOHBZ_2019_v9n2_34_f0004.png 이미지

Fig. 4. Reactor Valve Application Concept

JKOHBZ_2019_v9n2_34_f0005.png 이미지

Fig. 5. Reactor Cycle Time Period (24min)

JKOHBZ_2019_v9n2_34_f0006.png 이미지

Fig. 6. Reactor Internal Temp(Lummus)

JKOHBZ_2019_v9n2_34_f0007.png 이미지

Fig. 7. CATOFIN Reactor cycle sequence

JKOHBZ_2019_v9n2_34_f0008.png 이미지

Fig. 8. RVCS Configuration Model

JKOHBZ_2019_v9n2_34_f0009.png 이미지

Fig. 9. 2oo3 Close Condition Logic Model

JKOHBZ_2019_v9n2_34_f0010.png 이미지

Fig. 10. 2oo3 Open Condition Logic Model

JKOHBZ_2019_v9n2_34_f0011.png 이미지

Fig. 11. HMI System Modeling in Monitor

JKOHBZ_2019_v9n2_34_f0012.png 이미지

Fig 12. Result of Proplyene Production(Ton/Year)

JKOHBZ_2019_v9n2_34_f0013.png 이미지

Fig 13. Performance Rate of Productivity(%)

JKOHBZ_2019_v9n2_34_f0014.png 이미지

Fig.14 Reliability Performance Curve

Table. 1 Close Condition Cause & Effect Table

JKOHBZ_2019_v9n2_34_t0001.png 이미지

Table. 2 2oo3 Open Condition Cause & Effect

JKOHBZ_2019_v9n2_34_t0002.png 이미지

References

  1. S. T. Seo, W. G. Won, K. S. Lee, C. S. Jung & S. H. Lee. (2007). Repetitive Control of CATOFIN process. Korean Journal of Chemical Engineering, 24(6), 921-926. https://doi.org/10.1007/s11814-007-0098-3
  2. J. B. Park, B. M. Kim, Jiam Shen, D. S. Rho. (2011). Development of Remote Monitoring and Control Device of 50KW Photovoltaic System. Journal of Korea Convergence Society, 2(3), 1-14. https://doi.org/10.15207/JKCS.2011.2.3.001
  3. S. Y. Jung. (2010). Feedback Load Control Mechanism for Real-Time Web Services. Journal of Korea Convergence Society, 1(1), 1-21. https://doi.org/10.15207/JKCS.2010.1.1.001
  4. J. H. Ko. (2011). A Study On Dual System for Fault Tolerance of PLC. Journal of the Korea Institute of electronic Communication Sciences, 6(3), 397-404. https://doi.org/10.13067/JKIECS.2011.6.3.397
  5. CB&I USA. (2013). Reactor Automated Emergency Shutdown System. Los Angeles : Lumus Technology.
  6. Y. G. Hyun & J. Y. Lee. (2018). Trends Analysis and Future Direction of Business Process Automation, RPA(Robotic Process Automation) in the Times of Convergence. Journal of Digital Convergence, 16(11), 313-327. https://doi.org/10.14400/JDC.2018.16.11.313
  7. H. S. Lee & Y. W. Seo. (2018). An Analysis of the proliferation Case of TOPCIT(Test of Practical Competency in ICT) and policy implications. Journal of Digital Convergence, 16(5), 1-12. https://doi.org/10.14400/JDC.2018.16.5.001
  8. Y. K. Lee & H. S. Yang. (2016). A Study for Secure the Reliability of Automated Warehouse System. Journal of Digital Convergence, 14(10), 253-259. https://doi.org/10.14400/JDC.2016.14.10.253
  9. D. K. Choi & H. S. Roh. (2003). A Study on the Effect of Factory Automation Level on Cost Structure and Business Performance. Doctoral Dissertation. Dong-A University, Busan.
  10. H. J. Lee, M. Y. Jung, C. G. Kim & H. J. Kim. (2019). A Study on Energy Saving Monitoring System of Data Center based on Context Awareness. Journal of Convergence for Information Technology, 9(1), 19-27. https://doi.org/10.22156/CS4SMB.2019.9.1.019