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  • 한국과학기술정보연구원(KISTI) 서울분원 대회의실(별관 3층)
  • 2024년 07월 03일(수) 13:30
 

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Analyzing Technological Trends of Smart Factory using Topic Modeling

Asian Journal of Innovation and Policy / Asian Journal of Innovation and Policy, (P)2287-1608; (E)2287-1616
2021, v.10 no.3, pp.380-403
https://doi.org/10.7545/ajip.2021.10.3.380
Adnan Hussain (Gyeongsang National University)
김철현 (인덕대학교)
Ganchimeg Battsengel (Gyeongsang National University)
전정환 (경상국립대학교)
  • 다운로드 수
  • 조회수

Abstract

Recently, smart factories have gained significant importance since the development of the fourth industrial revolution and the rise of global industrial competition. Therefore, the industries' survival to meet the global market trends requires accurate technological planning. Although, different works are available to investigate forecasting technologies and their influence on the smart factory. However, little significant work is available yet on the analysis of technological trends concerning the smart factory, which is the core focus herein. This work was performed to analyze the technological trends of the smart factory, followed by a detailed investigation of recent research hotspots/frontiers in the field. A well-known topic modeling technique, namely Latent Dirichlet Allocation (LDA), was employed for this study described above. The technological trends were further strengthened with the in-depth analysis of a smart factory-based case study. The findings produced the technological trends which possess significant potential in determining the technological strategies. Moreover, the results of this work may be helpful for researchers and enterprises in forecasting and planning future technological evolution.

keywords
Smart factory, Topic modeling, Latent Dirichlet Allocation(LDA), Patent analysis, Technological trends, Industry 4.0

참고문헌

1.

Alcácer, V., & Cruz-Machado, V. (2019). Scanning the Industry 4.0: A Literature Review on Technologies for Manufacturing Systems. Engineering Science and Technology, an International Journal, 22(3), 899–919. https://doi.org/10.1016/ j.jestch.2019.01.006

2.

Alghamdi, R., & Alfalqi, K. (2015). A Survey of Topic Modeling in Text Mining. International Journal of Advanced Computer Science and Applications, 6(1), 147–153. https://doi.org/10.14569/ijacsa.2015.060121

3.

Anantharaman, A., Jadiya, A., Siri, C. T. S., Adikar Bharath, N. V. S., & Mohan, B. (2019). Performance evaluation of topic modeling algorithms for text classification. Proceedings of the International Conference on Trends in Electronics and Informatics, ICOEI 2019, 2019-April(Icoei), 704–708. https://doi.org/10.1109 /icoei.2019.8862599

4.

Blei, D., Carin, L., & Dunson, D. (2010). Probabilistic topic models. IEEE Signal Processing Magazine, 27(6), 55–65. https://doi.org/10.1109/MSP.2010.938079

5.

Blei, D. M., & Lafferty, J. D. (2006). Dynamic topic models. ACM International Conference Proceeding Series, 148, 113–120. https://doi.org/10.1145/1143844. 1143859

6.

Campbell, J. C., Hindle, A., & Stroulia, E. (2015). Latent Dirichlet Allocation: Extracting Topics from Software Engineering Data. The Art and Science of Analyzing Software Data, 3, 139–159. https://doi.org/10.1016/B978-0-12-411519-4.00006-9

7.

Chen, B., Wan, J., Shu, L., Li, P., Mukherjee, M., & Yin, B. (2017). Smart Factory of Industry 4.0: Key Technologies, Application Case, and Challenges. IEEE Access, 6, 6505–6519. https://doi.org/10.1109/ACCESS.2017.2783682

8.

Chen, X., Zou, D., Cheng, G., & Xie, H. (2020). Detecting latent topics and trends in educational technologies over four decades using structural topic modeling: A retrospective of all volumes of Computers & Education. Computers and Education, 151(September 2019), 103855. https://doi.org/10.1016/j.compedu.2020.103855

9.

Cheng, J., Chen, W., Tao, F., & Lin, C. L. (2018). Industrial IoT in 5G environment towards smart manufacturing. Journal of Industrial Information Integration, 10. https://doi.org/10.1016/j.jii.2018.04.001

10.

Erzurumlu, S. S., & Pachamanova, D. (2020). Topic modeling and technology forecasting for assessing the commercial viability of healthcare innovations. Technological Forecasting and Social Change, 156(March), 120041. https:// doi.org/10.1016/j.techfore.2020.120041

11.

Hameed, B., Durr, F., & Rothermel, K. (2011). RFID based complex event processing in a smart real-time factory. Expert Discussion: Distributed Systems in Smart Spaces.

12.

Jeon, J., & Suh, Y. (2017). Analyzing the Major Issues of the 4th Industrial Revolution. Asian Journal of Innovation & Policy, 6(3), 262–273. http://web.b.ebscohost.com/ ehost/detail/detail?vid=0&sid=32c5d468d8124fd68fb3b929e0e273ab%40sessiomgr102&bdata=JnNpdGU9ZWhvc3QtbGl2ZSZzY29wZT1zaXRl#AN=129379372&db=bsu

13.

Kang, H. S., Lee, J. Y., Choi, S., Kim, H., Park, J. H., Son, J. Y., Kim, B. H., & Noh, S. Do. (2016). Smart manufacturing: Past research, present findings, and future directions. International Journal of Precision Engineering and Manufacturing - Green Technology, 3(1), 111–128. https://doi.org/10.1007/s40684-016-0015-5

14.

Lasi, H., Fettke, P., Kemper, H. G., Feld, T., & Hoffmann, M. (2014). Industry 4.0. Business and Information Systems Engineering, 6(4), 239–242. https://doi.org/ 10.1007/s12599-014-0334-4

15.

Lee, H., Seo, H., & Geum, Y. (2018). Uncovering the topic landscape of product-service system research: From sustainability to value creation. Sustainability (Switzerland), 10(4). https://doi.org/10.3390/su10040911

16.

Lee, J., Bagheri, B., & Kao, H. A. (2015). A Cyber-Physical Systems architecture for Industry 4.0-based manufacturing systems. Manufacturing Letters, 3, 18–23. https://doi.org/10.1016/j.mfglet.2014.12.001

17.

Lee, M. H., Yun, J. H. J., Pyka, A., Won, D. K., Kodama, F., Schiuma, G., Park, H. S., Jeon, J., Park, K. B., Jung, K. H., Yan, M. R., Lee, S. Y., & Zhao, X. (2018). How to respond to the Fourth Industrial Revolution, or the second information technology revolution? Dynamic new combinations between technology, market, and society through open innovation. Journal of Open Innovation: Technology, Market, and Complexity, 4(3). https://doi.org/10.3390/joitmc4030021

18.

Lehmhus, D., Aumund-Kopp, C., Petzoldt, F., Godlinski, D., Haberkorn, A., Zöllmer, V., & Busse, M. (2016). Customized Smartness: A Survey on Links between Additive Manufacturing and Sensor Integration. Procedia Technology, 26, 284–301. https://doi.org/10.1016/j.protcy.2016.08.038

19.

Lucke, D., Constantinescu, C., & Westkämper, E. (2008). Smart Factory - A Step towards the Next Generation of Manufacturing. Manufacturing Systems and Technologies for the New Frontier, Sfb 627, 115–118. https://doi.org/10.1007/978-1-84800-267-8_23

20.

Mittal, S., Khan, M. A., Romero, D., & Wuest, T. (2019). Smart manufacturing: Characteristics, technologies and enabling factors. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 233(5). https://doi.org/10.1177/0954405417736547

21.

Mohamed, N., Al-Jaroodi, J., & Lazarova-Molnar, S. (2019). Industry 4.0: Opportunities for enhancing energy efficiency in smart factories. SysCon 2019 - 13th Annual IEEE International Systems Conference, Proceedings. https://doi. org/10.1109/SYSCON.2019.8836751

22.

Pagnon, W. (2017). The 4th Industrial Revolution – A Smart Factory Implementation Guide. International Journal of Advanced Robotics and Automation, 2(2), 1–5. https://doi.org/10.15226/2473-3032/2/2/00123

23.

Phuyal, S., Bista, D., & Bista, R. (2020). Challenges, Opportunities and Future Directions of Smart Manufacturing: A State of Art Review. Sustainable Futures, 2(March), 100023. https://doi.org/10.1016/j.sftr.2020.100023

24.

Porter, K. (2018). Analyzing the DarkNetMarkets subreddit for evolutions of tools and trends using LDA topic modeling. Proceedings of the Digital Forensic Research Conference, DFRWS 2018 USA, 26, S87–S97. https://doi.org/10.1016/j.diin. 2018.04.023

25.

Radziwon, A., Bilberg, A., Bogers, M., & Madsen, E. S. (2014). The smart factory: Exploring adaptive and flexible manufacturing solutions. Procedia Engineering, 69, 1184–1190. https://doi.org/10.1016/j.proeng.2014.03.108

26.

Resman, M., Turk, M., & Herakovic, N. (2020). Methodology for planning smart factory. Procedia CIRP, 97, 401–406. https://doi.org/10.1016/j.procir.2020.05.258

27.

Shi, Z., Xie, Y., Xue, W., Chen, Y., Fu, L., & Xu, X. (2020). Smart factory in Industry 4.0. Systems Research and Behavioral Science, 37(4), 607–617. https://doi.org/ 10.1002/sres.2704

28.

Tao, F., & Zhang, M. (2017). Digital Twin Shop-Floor: A New Shop-Floor Paradigm Towards Smart Manufacturing. IEEE Access, 5, 20418–20427. https://doi.org/ 10.1109/ACCESS.2017.2756069

29.

Thoben, K. D., Wiesner, S. A., & Wuest, T. (2017). “Industrie 4.0” and smart manufacturing-a review of research issues and application examples. International Journal of Automation Technology, 11(1), 4–16. https://doi.org/10.20965/ijat. 2017.p0004

30.

Wiktorsson, M., Noh, S. Do, Bellgran, M., & Hanson, L. (2018). Smart Factories: South Korean and Swedish examples on manufacturing settings. Procedia Manufacturing, 25, 471–478. https://doi.org/10.1016/j.promfg.2018.06.128

31.

Yang, H. L., Chang, T. W., & Choi, Y. (2018). Exploring the research trend of smart factory with topic modeling. Sustainability (Switzerland), 10(8). https://doi. org/10.3390/su10082779

32.

Zhu, Q., Li, G., & Wu, W. (2018). Research on smart factory model of color TV industry based on Intelligent Manufacturing. Proceedings of 2018 IEEE 4th Information Technology and Mechatronics Engineering Conference, ITOEC 2018, Itoec, 1739–1742. https://doi.org/10.1109/ITOEC.2018.8740690

33.

Zuehlke, D. (2010). SmartFactory-Towards a factory-of-things. Annual Reviews in Control, 34(1), 129–138. https://doi.org/10.1016/j.arcontrol.2010.02.008

Asian Journal of Innovation and Policy