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SYSTEMS & CONTROL

Digi-flash pedagogy confronts new emerging technologies - Maturity level evaluation case study

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Article: 2186201 | Received 26 Oct 2022, Accepted 14 Feb 2023, Published online: 05 Mar 2023

References

  • Aheleroff, S., Huang, H., Xu, X., & Zhong, R. Y. (2022). Toward sustainability and resilience with industry 4.0 and industry 5.0. front. Manufacturing Technology, 26, 1–15. https://doi.org/10.3389/fmtec.2022.951643
  • Akter, S., Michael, K., Uddin, M. R., McCarthy, G., & Rahman, M. (2020). Transforming business using digital innovations: The application of AI, blockchain, cloud and data analytics. Annals of Operations Research, 1–33. http://dx.doi.org/10.1007/s10479-020-03620-w
  • Autiosalo, J., Ala-Laurinaho, R., Mattila, J., Valtonen, M., Peltoranta, V., & Tammi, K. (2021). Towards integrated digital twins for industrial products: Case study on an overhead crane. Applied Sciences, 11(2), 683. https://doi.org/10.3390/app11020683
  • Autiosalo, J., Vepsäläinen, J., Viitala, R., & Tammi, K. (2019). A feature-based framework for structuring industrial digital twins. IEEE Access, 8, 1193–1208. https://doi.org/10.1109/ACCESS.2019.2950507
  • Castro, F. L., Cox, L., & Fukumoto, G. (2017). Diffusion of an agricultural innovation: A case study involving dry litter technology in American Samoa. Pacific Agriculture and Natural Resources, 7(1), 1–12. https://hilo.hawaii.edu/panr/writing.php?id=301
  • Dedehayir, O., & Steinert, M. (2016). The hype cycle model: A review and future directions. Technological Forecasting and Social Change, 108, 28–41. https://doi.org/10.1016/j.techfore.2016.04.005
  • Fenn, J., & Raskino, M. (2008). Mastering the hype cycle: how to choose the right innovation at the right time. Harvard Business Press.
  • Fire, M., & Guestrin, C. (2019). Over-optimization of academic publishing metrics: Observing goodhart’s law in action. GigaScience, 8(6). giz053 https://doi.org/10.1093/gigascience/giz053
  • Gartner. (2022). Gartner hype cycle research methodology. Accessed 25 March 2022. https://www.gartner.com/en/research/methodologies/gartner-hype-cycle
  • GIM Institute. (2015). Rapid, iterative experimentation process – A ‘lean startup-style’ approach to innovation. Accessed 25 March 2022. https://www.giminstitute.org/lean-startup-style-innovation
  • Gkoumas, K., & Tsakalidis, A. (2019). A framework for the taxonomy and assessment of new and emerging transport technologies and trends. Transport, 34(4), 455–466. https://doi.org/10.3846/transport.2019.9318
  • Grunwald, A. (2009). Technology assessment: Concepts and methods. In Anthonie, M. (Ed.), Philosophy of technology and engineering sciences (pp. 1103–1146). North-Holland. https://www.sciencedirect.com/book/9780444516671/philosophy-of-technology-and-engineering-sciences#book-description
  • Guidolin, M., & Manfredi, P. (2023). Innovation diffusion processes: Concepts, models, and predictions. Annual Review of Statistics and Its Application, 10(1). https://doi.org/10.1146/annurev-statistics-040220-091526
  • Hein-Pensel, F., Winkler, H., Brückner, A., Wölke, M., Jabs, I., Mayan, I. J., Zinke-Wehlmann, C., Friedrich, J., & Zinke-Wehlmann, C. (2023). Maturity assessment for industry 5.0: A review of existing maturity models. Journal of Manufacturing Systems, 66, 200–210. https://doi.org/10.1016/j.jmsy.2022.12.009
  • Konstantinidis, F. K., Myrillas, N., Mouroutsos, S. G., Koulouriotis, D., & Gasteratos, A. (2022). Assessment of industry 4.0 for modern manufacturing ecosystem: A systematic survey of surveys. Machines, 10(9), 746. https://doi.org/10.3390/machines10090746
  • Kritzinger, W., Karner, M., Traar, G., Henjes, J., & Sihn, W. (2018). Digital twin in manufacturing: A categorical literature review and classification. IFAC-PapersOnLine, 51(11), 1016–1022. https://doi.org/10.1016/j.ifacol.2018.08.474
  • Leng, J., Ruan, G., Jiang, P., Xu, K., Liu, Q., Zhou, X., & Liu, C. (2020). Blockchain-empowered sustainable manufacturing and product lifecycle management in industry 4.0: A survey. Renewable and Sustainable Energy Reviews, 132, 110112. https://doi.org/10.1016/j.rser.2020.110112
  • Leng, J., Sha, W., Lin, Z., Jing, J., Liu, Q., & Chen, X. (2022). Blockchained smart contract pyramid-driven multi-agent autonomous process control for resilient individualised manufacturing towards industry 5.0. International Journal of Production Research, 1–20. https://doi.org/10.1080/00207543.2022.2089929
  • Leng, J., Wang, D., Shen, W., Li, X., Liu, Q., & Chen, X. (2021). Digital twins-based smart manufacturing system design in industry 4.0: A review. Journal of Manufacturing Systems, 60, 119–137. https://doi.org/10.1016/j.jmsy.2021.05.011
  • Liljaniemi, A., & Paavilainen, H. (2020). Using digital twin technology in engineering education – Course concept to explore benefits and barriers. Open Engineering, 10(1), 377–385. https://doi.org/10.1515/eng-2020-0040
  • Metropolia. (2021). Digi-flash project - Speeding up the use of industry 4.0 technologies in small and medium sized companies. Accessed 25 March 2022. https://digisalama.metropolia.fi
  • Nieto, M., López, F., & Cruz, F. (1998). Performance analysis of technology using the S curve model. Technovation, 18(6–7), 439–457. https://doi.org/10.1016/S0166-4972(98)00021-2
  • Revkin, S. K., Piazza, M., Izard, V., Cohen, L., & Dehaene, S. (2008). Does Subitizing Reflect Numerical Estimation? Psycho-logical Science, 19(6), 607–614. https://doi.org/10.1111/j.1467-9280.2008.02130.x
  • Ries, E. (2011). The lean startup: how today’s entrepreneurs use continuous innovation to create radically successful businesses. Crown Business.
  • Rogers, M. E. (2003). Diffusion of Innovations. Free Press.
  • Rotolo, D., Hicks, D., & Martin, B. (2015). What Is an Emerging Technology? Research Policy, 44(10), 1827–1843. https://doi.org/10.1016/j.respol.2015.06.006
  • Steinert, M., & Larry, L. (2010). Scrutinizing gartner’s hype cycle approach. Proceedings of PICMET
  • Woo, J., & Magee, C. L. (2022). Relationship between technological improvement and innovation diffusion: An empirical test. Technology Analysis & Strategic Management, 34(4), 390–405. https://doi.org/10.1080/09537325.2021.1901875