The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Industry 4.0: A Korea perspective
Abstract
Abstract The objectives of this paper are (1) to have a detailed, practical discussion of Industry 4.0, and (2) to suggest policy implications to transition toward Industry 4.0 in Korea. Companies should consider Industry 4.0 very seriously as they develop their future initiatives since traditional manufacturing business models do not fit with the emerging technologies of Industry 4.0. Some issues should be addressed with care: IT security, reliability and stability needed for critical machine-to-machine communication; a need to maintain the integrity of production processes, avoid IT snags, and protect industrial knowhow; and the lack of adequate skill-sets, general reluctance to change by stakeholders, and loss of many jobs to automatic processes and IT-controlled processes. To successfully transform Korean industry toward Industry 4.0, it is necessary to (1) refine and elaborate the strategies enacted by the central government to build economic and social systems that can flexibly respond to changes, (2) establish some kind of operational system to maximize the effectiveness of initiatives and policies, (3) develop concrete and workable action plans to transition toward economic and social systems that can accommodate innovative changes, and (4) establish infrastructure to lead all initiatives.
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Cites
Recent advances and trends in predictive manufacturing systems in big data environment
Lee, J., Lapira, E., Bagheri, B., & Kao, H.-A. (2013) · Manufacturing Letters · doi:10.1016/j.mfglet.2013.09.005 · Cited by 1,090
Cited by
Industry 4.0, digitization, and opportunities for sustainability
Ghobakhloo, M. (2020) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2019.119869 · Cited by 2,115
Horváth, D., & Szabó, R. Z. (2019) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2019.05.021 · Cited by 1,281
Lopes de Sousa Jabbour, A. B., Jabbour, C. J. C., Godinho Filho, M., & Roubaud, D. (2018) · Annals of Operations Research · doi:10.1007/s10479-018-2772-8 · Cited by 1,116
Understanding AI adoption in manufacturing and production firms using an integrated TAM-TOE model
Chatterjee, S., Rana, N. P., Dwivedi, Y. K., & Baabdullah, A. M. (2021) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2021.120880 · Cited by 825
Sima, V., Gheorghe, I. G., Subić, J., & Nancu, D. (2020) · Sustainability · doi:10.3390/su12104035 · Cited by 786
Metadata
- Authors
- Sung, T. K.
- Venue
- Technological Forecasting and Social Change
- Publisher
- Elsevier BV
- Published
- 2018-07
- Volume
- 132
- Pages
- 40-45
- ISSN
- 0040-1625 (ISSN-L)
- OpenAlex
- W2770323823
- Cited by
- 539
- References
- 1
- FWCI
- 49.78
- Type
- journal article
- Language
- en
- Open access
- closed
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