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A Case Study on Smart Factory Extensibility for Small and Medium Enterprises

중소기업 스마트 공장 확장성 사례연구

  • Kim, Sung-Min (Department of Industrial & Systems Engineering, Graduate School of Public Policy and Information Technology, Seoul National University of Science of Technology) ;
  • Ahn, Jaekyoung (Department of Industrial & Systems Engineering, Graduate School of Public Policy and Information Technology, Seoul National University of Science of Technology)
  • 김성민 (서울과학기술대학교 IT정책전문대학원 산업정보시스템전공) ;
  • 안재경 (서울과학기술대학교 IT정책전문대학원 산업정보시스템전공)
  • Received : 2021.03.04
  • Accepted : 2021.04.20
  • Published : 2021.06.30

Abstract

Smart factories can be defined as intelligent factories that produce products through IoT-based data. In order to build and operate a smart factory, various new technologies such as CPS, IoT, Big Data, and AI are to be introduced and utilized, while the implementation of a MES system that accurately and quickly collects equipment data and production performance is as important as those new technologies. First of all, it is very essential to build a smart factory appropriate to the current status of the company. In this study, what are the essential prerequisite factors for successfully implementing a smart factory was investigated. A case study has been carried out to illustrate the effect of implementing ERP and MES, and to examine the extensibilities into a smart factory. ERP and MES as an integrated manufacturing information system do not imply a smart factory, however, it has been confirmed that ERP and MES are necessary conditions among many factors for developing into a smart factory. Therefore, the stepwise implementation of intelligent MES through the expansion of MES function was suggested. An intelligent MES that is capable of making various decisions has been investigated as a prototyping system by applying data mining techniques and big data analysis. In the end, in order for small and medium enterprises to implement a low-cost, high-efficiency smart factory, the level and goal of the smart factory must be clearly defined, and the transition to ERP and MES-based intelligent factories could be a potential alternative.

Keywords

Acknowledgement

This study has been supported by a Research Fund of Seoul National University of Science & Technology, Korea.

References

  1. Cha, S.K., Yoon, J.Y., Hong, J.K., Kang, H.G., and Cho, H.C., The System Architecture and Standardization Production IT Convergence for Smart Factory, Journal of the Korean Society for Precision Engineering, 2015, Vol. 31, No. 1, pp. 17-24.
  2. Cho, Y.J., The Strategy for Smart Factory of Korea in the Era of the Industry 4.0, Journal of Computing Science and Engineering, 2017, Vol. 35, No. 6, pp. 40-48.
  3. Choi, K.S., Park, K.A., and Yun, Y.S., A Methodology for Productivity Improvement using Simulation Technique in Small and Medium Enterprise, Journal of Industrial Economics and Business, 2011, Vol. 24, No. 4, pp. 1969- 1987.
  4. Hahm, H.J., A Study of Smart Factory Policy For ICT-Based, Journal of The e-Business Studies, 2017, Vol. 18, No. 6, pp. 363-380. https://doi.org/10.20462/TeBS.2017.12.18.6.363
  5. He, Q.P. and Wang, J., Statistical Process Monitoring as a Big Data Analytics Tool for Smart Manufacturing, Journal of Process Control, 2018, Vol. 67, pp. 35-43. https://doi.org/10.1016/j.jprocont.2017.06.012
  6. Hwang, S., Kim, J., and Hwangbo, H., A Study on Sensor Data Analysis and Product Defect Improvement for Smart Factory, The Korean Journal of Bigdata, 2018, Vol. 3, No. 1, pp. 95-103. https://doi.org/10.36498/kbigdt.2018.3.1.95
  7. Industry 4.0 Smart Factory & Safety Monitoring System, http://www.hellot.net/_UPLOAD_FILES/conference/smartB_6.pdf.
  8. Institute for International Trade, The Era of the 4th Industrial Revolution, Manufacturing Innovation and Reshoring, 2021, Vol. 5, pp. 1-26.
  9. Jang, W.J., Cho, S.I., Kim, S.S., and Gim, G.Y., A Study on the Implementation of Big Data Infrastructure in Smart Factory, Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology, 2018, Vol. 8, No. 10, pp. 11-23.
  10. Jun et al., Data Mining-Based Methodology for Performance Prediction of Geothermal Heat Pump System, The Society of Air-Conditioning and Refrigerating Engineers of Korea, 2015, pp. 557-560.
  11. Jun, C., Kim, B.H., and Lee, J.Y., A Big Data Analysis Platform based on the Manufacturing Specialized Library : A Case Study on Implementation of the Platform for Quality Problems, Journal of the Korean Institute of Industrial Engineers, 2017, Vol. 43, No. 5, pp. 380-387. https://doi.org/10.7232/JKIIE.2017.43.5.380
  12. Kang, H.M. and Hwang, K.T., Analysis of Research Trends of Cyber Physical System (CPS) in the Manufacturing Industry, Informatization Policy, 2018, Vol. 25, No. 3, pp. 3-28. https://doi.org/10.22693/NIAIP.2018.25.3.003
  13. Kim, B.G., MES-based Smart Factory, Korean Institute of Industrial Engineers, 2015, pp. 2077-2104.
  14. Kim, E.Y. and Park, M.S., A Study on the Limits of Manufacturing Innovation and Policy Direction of SMEs in the 4 th Industrial Revolution, Journal of Science and Technology Studies, 2018, Vol. 18, No. 2, pp. 269-306. https://doi.org/10.22989/JSTS.2018.18.2.007
  15. Kim, H.I., Smart Factory has Wings with Artificial Intelligence, PORSI ISSUE REPORT, 2017, pp. 3-8.
  16. Kim, S.M. and Ahn, J.K., Verification of ERP Standard Time Using TOC Technique and Improvement of MES Routing Point, Society of Korea Industrial and Systems Engineering, 2018, Vol. 41, No. 4, pp. 22-33. https://doi.org/10.11627/jkise.2018.41.4.022
  17. Koh, J.Y. and Cho, T.H., A Simulation of Production Planning Strategies for the Improvement of a Manufacturing Process, The Jounal of The Korea Society For Simulation, 1999, Vol. 8, No. 2, pp. 87-100.
  18. Korea Development Bank, The Possibility of a Smart Factory as a way to Upgrade the Domestic Manufacturing industry, 2015.
  19. Lee et al., A Study on ICT-Based Manufacturing Innovation and Reshoring, Ministry of Science and ICT, 2018, Vol. 307, pp. 4-116.
  20. Lee, D.H., Lee, J.Y., and Back, W.J., Design of MES Interlocking Welding Monitoring System for Welding Process Smart Factory, Journal of the Institute of Electronics and Information Engineers, 2018, pp. 877-880.
  21. Lee, H.J., Kim, Y.J., Yim, J.I., Kim, Y.W., and Lee, S.H., Analysis of Field Conditions and Requirements for Deploying Smart Factory, Journal of the Korean Society for Precision Engineering, 2017, Vol. 34, No. 1, pp. 29-34. https://doi.org/10.7736/KSPE.2017.34.1.29
  22. Lee, J.C., Build of Smart Factory Step-by-Step Promotion Points, Industrial Engineering Magazine, 2018, Vol. 25, No. 4 pp. 31-37.
  23. Lee, S., Kim, J.Y., and Lee, W., Smart Factory Literature Review and Strategies for Korean Small Manufacturing Firms, Journal of Information Technology Applications and Management, 2017, Vol. 24, No. 4, pp. 133-152. https://doi.org/10.21219/JITAM.2017.24.4.133
  24. Lim et al., A Case Study for the Smart Factory Application in the Manufacturing Industry, Korean Journal of Business Administration, 2017, Vol. 30, No. 9, pp. 1609-1630.
  25. Mail Business News Korea, https://mk.co.kr/news/business/view/2020/06/596473/.
  26. Noh, K.S. and Park, S.H., An Exploratory Study on Application Plan of Big Data to Manufacturing Execution System, Journal of Digital Convergence, 2014, Vol. 12, No. 1, pp. 305-311.
  27. Noh, S.D., Smart Factory and Cyber Physics System Technology, The Journal of The Korean Institute of Communication Sciences, 2016, Vol. 33, No. 11, pp. 3-7.
  28. Park et al., Development of Manufacturing Big Data Analysis Library for Smart Factory Upgrade, The Korean Operations Research and Management Science Society, 2018, pp. 1527-1541.
  29. Park, J.K. and Chang, T.W., Review of Domestic Research on Smart Manufacturing Technologies, Journal of Society for e-Business Studies, 2019, Vol. 23, No. 2, pp. 123-133.
  30. Park, S.B., Enhancing Productivity of Steel Coil Slitting and Shearing Line Using ARENA Simulation, The Journal of Korean Institute of Industrial Engineers, 2019, pp. 482-496. https://doi.org/10.7232/JKIIE.2017.43.6.482
  31. Park, S.G., Smart Factory for Small Companies, Electronics and Telecommunications Trends, 2016, pp. 39-47.
  32. Radziwon, A., Bilberg, A., Bogers, M., and Madsen, E.S., The Smart Factory : Exploring Adaptive and Flexible Manufacturing Solutions, Procedia Engineering, 2014, Vol. 69, pp. 1184-1190. https://doi.org/10.1016/j.proeng.2014.03.108
  33. Riew, M.C. and Lee, M.K., A Case Study of the Construction of Smart Factory in a Small Quantity Batch Production System : Focused on IDIS Company, Journal of the Korean Society for Quality Management, 2018, Vol. 46, No. 1, pp. 11-26. https://doi.org/10.7469/JKSQM.2018.46.1.011
  34. Schlechtendahl, J., Keinert, M., Kretschmer, F., Lechler, A., and Verl, A., Making Existing Production Systems Industry 4.0-ready, Production Engineering Research and Development, 2015, Vol. 9, pp. 143-148. https://doi.org/10.1007/s11740-014-0586-3
  35. Science Times, https://www.sciencetimes.co.kr/?p=166570.
  36. Shin et al., Smart Manufacturing, First ed., epress, 2017.
  37. Shin, S.J., Self-Learning Factory Structure and Operation Procedure Design for Cyber-Physical Production System, Proceedings of the Fall Conference of the Korean Institute of Industrial Engineers, 2018, pp. 1282-1299.
  38. Shin, S.J., Woo, J.Y., and Seo, W.C., Developing a Big Data Analytics Platform Architecture for Smart Factory, Journal of Korea Multimedia Society, 2016, Vol. 19, No. 8, pp. 1516-1529. https://doi.org/10.9717/kmms.2016.19.8.1516
  39. Sim, H.S. and Won, J.Y., Implementation and Effectiveness of Flexible Manufacturing Execution System, Journal of the Korea Management Engineers Society, 2016, Vol. 21, No. 2, pp. 57-71.
  40. Sim, J.H., Yoon, M.S., Ahn, J.B., Yu, B.D., and Hwang, I.K., A Study on Smart Factory Construction in Small and Medium Manufacturers, Journal of the Korean Institute of Plant Engineering, 2017, Vol. 22, No. 1. pp. 87-97.
  41. So, B.E. and Shin, S.S., The Built of Smart Factory Using Sensors and Virtual Process Design, The Journal of the Korea Institute of Electronic Communication Sciences, 2017, Vol. 12, No. 6, pp. 1071-1080. https://doi.org/10.13067/JKIECS.2017.12.6.1071
  42. Thoben, K.D., Wiesner, S., and Wuest, T., Industrie 4.0 and Smart Manufacturing, A Review of Research Issues and Application Examples, 2017, Vol. 11, No. 1, pp. 4-16.
  43. Wang, L., Torngren, M., and Onori, M., Current Status and Advancement of Cyberphysical Systems in Manufacturing, Journal of Manufacturing Systems, 2015, Vol. 37, pp. 517-527. https://doi.org/10.1016/j.jmsy.2015.04.008
  44. Yin, S. and O. Kaynak, Big Data for Modern Industry : Challenges and Trends [Point Of View], Proceedings of the IEEE, 2015, Vol. 103, No. 2, pp. 143-146. https://doi.org/10.1109/JPROC.2015.2388958
  45. Yoon, J.H. and Park, T.J., Manufacturing Innovation Trends and Prospects through CPS and IoT Technology, The Journal of The Korean Institute of Communication Sciences, 2016, Vol. 33, No. 11, pp. 23-28.
  46. Yu, S.J., Kang, B.S., and Hong, H.K., Building the Quality Management System for Compact Camera Module (CCM) Assembly Line, Journal of Intelligence and Information Systems, 2008, Vol. 14, No. 4, pp. 89-101.
  47. Yun, J.S., An, H.T., and Choi, Y.R., A Machine Learning Based Facility Error Pattern Extraction Framework for Smart Manufacturing, The Jounal of Society for e-Business Studies, 2018, Vol. 23, No. 2, pp. 97-110.