Journal of Convergence for Information Technology (융합정보논문지)

Convergence Society for SMB (중소기업융합학회)
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A Model Design for Enhancing the Efficiency of Smart Factory for Small and Medium-Sized Businesses Based on Artificial Intelligence

인공지능 기반의 중소기업 스마트팩토리 효율성 강화 모델 설계

  • Jeong, Yoon-Su (Department of information Communication Convergence Engineering, Mokwon University)
  • 정윤수 (목원대학교 정보통신융합공학부)
  • Received : 2019.02.04
  • Accepted : 2019.03.20
  • Published : 2019.03.28
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Abstract

Small and medium-sized Korean companies are currently changing their industrial structure faster than in the past due to various environmental factors (such as securing competitiveness and developing excellent products). In particular, the importance of collecting and utilizing data produced in smart factory environments is increasing as diverse devices related to artificial intelligence are put into manufacturing sites. This paper proposes an artificial intelligence-based smart factory model to improve the process of products produced at the manufacturing site with the recent smart factory. The proposed model aims to ensure the increasingly competitive manufacturing environment and minimize production costs. The proposed model is managed by considering not only information on products produced at the site of smart factory based on artificial intelligence, but also labour force consumed in the production of products, working hours and operating plant machinery. In addition, data produced in the proposed model can be linked with similar companies and share information, enabling strategic cooperation between enterprises in manufacturing site operations.

우리나라 중소기업은 현재 국내 외 다양한 환경 요인(경쟁력 확보 및 우수 제품 개발 등)으로 인하여 산업 구조가 과거에 비해 빠르게 변화하고 있는 상황이다. 특히, 인공지능과 관련된 다양한 장비가 제조현장에 투입되면서 스마트팩토리 환경에서 생산되는 데이터 수집 및 활용의 중요성이 점점 증가하고 있다. 본 논문에서는 최근 중소기업 제조 현장이 스마트팩토리화 되면서 제조 현장에서 생산되는 제품의 프로세스를 향상시키기 위한 인공지능 기반 스마트팩토리 모델을 제안한다. 제안 모델은 갈수록 치열해지는 제조 환경의 경쟁력 확보 및 생산 비용 절감을 최소화시키는 것이 목적이다. 제안 모델은 인공지능 기반의 스마트팩토리 현장에서 생산되는 제품의 정보뿐만 아니라 제품 생산에 소비되는 노동력, 노동 근무 시간 및 가동 공장기계 상태 등을 모두 고려하여 관리한다. 또한, 제안 모델에서 생산되는 데이터는 유사 기업과 시스템 연계 및 정보 공유가 가능하기 때문에 제조 현장 운영의 기업간 전략적 협력이 가능하다.

Keywords

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Fig. 1 Gathering and sharing information at manufacturing sites

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Fig. 2 Intelligent Smart Factory Model Process

Table 1. Factory automation vs. Smart Factory

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References

  1. R. N. Kanungo. (1982). Measurement of job and work involvement. Journal of Applied Psychology, 67(3), 341-349. https://doi.org/10.1037/0021-9010.67.3.341
  2. B. J. Babin & J. S. Boles. (1996). The effects of perceived co-worker involvement and supervisor support on service provider role stress, performance and job satisfaction. Journal of retailing, 72(1), 57-75. https://doi.org/10.1016/S0022-4359(96)90005-6
  3. S. S. Shin, Y. S. Jeong & Y. J. An. (2015). A Study of Analysis and Response and Plan for National and International Security Practices using Fin-Tech Technologies. Journal of Convergence Soceity for SMB, 5(3), 1-7.
  4. Y. S. Jeong. (2016). A Study of An Efficient Clustering Processing Scheme of Patient Disease Information for Cloud Computing Environment. Journal of Convergence Soceity for SMB, 6(1), 33-38. https://doi.org/10.22156/CS4SMB.2016.6.1.033
  5. D. Ilic, S. Karnouskos, P. Silva & S. Detzler. (2014). A system for enabling facility management to achieve deterministic energy behaviour in the smart grid era. International Conference on Smart Grids and Green IT systems (Smart- Green 2014).
  6. C. F. Lai, Y. X. Lai, L. T. Yang & H. C. Chao. (2012). Integration of IoT energy management system with appliance and activity recognition. 2012 IEEE International Conference on Green Computing and Communications (GreenCom), 66-71.
  7. D. Ilic, S. Karnouskos & M. Wilhelm. (2013). A comparative analysis of smart metering data aggregation performance. 2013 11th IEEE International Conference on Industrial Informatics (INDIN), 434-439.
  8. E. K. Kim & Y. M. Moon. (2016). The Fourth Industrial Revolution and Its Implications for Gyeonggi-Do. Gyeonggi Research Institute, 1-88.
  9. S. H. Choi. (2017). Current Status of POSCO Smart Factory and Artificial Intelligence Application. Transactions of the Korean Society of Automotive Engineers, 143-153. https://doi.org/10.7467/KSAE.2014.22.3.143
  10. Y. S. Jeong. (2010). An Efficiency Management Scheme using Big Data of Healthcare Patients using Puzzy AHP. Journal of Digital Convergence, 13(4), 227-234. https://doi.org/10.14400/JDC.2015.13.4.227
  11. Y. S. Jeong. (2016). Design of Prevention Model according to a Dysfunctional of Corporate Information. Journal of Convergence Soceity for SMB, 6(2), 11-17. https://doi.org/10.22156/CS4SMB.2016.6.2.011
  12. L. Raymond. (1985). Organizational Characteristics and MIS success in the Context of Small Business. MIS Quarterly, 37-52.
  13. K. H. Han & Y. S. Jeong. (2017). Efficient Authentication Establishment Scheme between IoT Device based on Pascal Triangle Theory. Journal of the Korea Convergence Society, 8(7), 15-21. https://doi.org/10.15207/JKCS.2017.8.7.015
  14. Y. S. Jeong & K. H. Han. (2018). An efficient access control techniques between different IoT devices in a cloud environment. Journal of the Korea Convergence Society, 8(7), 15-21. https://doi.org/10.15207/JKCS.2017.8.7.015
  15. Y. S. Jeong, Y. T. Kim & G. C. Park. (2019). Designing an Automated Production Information Platform for Small and Medium-sized Businesses. Journal of Convergence for Information Technology, 9(1), 116-122. https://doi.org/10.22156/CS4SMB.2019.9.1.116