Digital Infrastructure Development Driving the Intelligent Transformation of Manufacturing: Technological Application Scenarios and Policy Optimization Strategies

Liyu Ge; Keke Ning; Mengyi  Zheng

doi:10.62177/apemr.v2i5.796

Authors

Liyu Ge Guangdong University of Finance & Economics
Keke Ning Guangdong University of Finance & Economics
Mengyi Zheng Guangdong University of Finance & Economics

DOI:

https://doi.org/10.62177/apemr.v2i5.796

Keywords:

Digital Infrastructure, Intelligent Manufacturing, Technological Scenarios, Policy Strategy, Logical Framework, Socio-Technical Systems, Ecosystem

Abstract

The analysis begins by deconstructing the conceptual architecture of digital infrastructure, articulating how its core components—ubiquitous connectivity, pervasive sensing, distributed computation, and integrative platforms—logically necessitate the emergence of key manufacturing capabilities such as real-time perception, data-driven cognition, adaptive response, and systemic integration. These capabilities are then logically synthesized into three representative technological application scenarios: holistic visibility and optimization, predictive intervention and autonomous quality assurance, mass customization through flexible reconfiguration. The paper further deduces the inherent socio-technical challenges that arise from this infrastructural transformation, including economic barriers, structural complexities, and skill obsolescence. Finally, through logical extension, the paper proposes a holistic set of policy optimization strategies designed not to subsidize technology adoption per se, but to cultivate a fertile ecosystem that addresses these inherent challenges, fosters innovation, and ensures the equitable and sustainable evolution of the manufacturing sector.

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References

Zhou, K., Liu, T., & Zhou, L. (2015). Industry 4.0: Towards future industrial opportunities and challenges. In 2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) (pp. 2147-2152). IEEE. DOI: https://doi.org/10.1109/FSKD.2015.7382284

Xu, L. D., Xu, E. L., & Li, L. (2018). Industry 4.0: state of the art and future trends. International Journal of Production Research, 56(8), 2941-2962. DOI: https://doi.org/10.1080/00207543.2018.1444806

Kagermann, H., Wahlster, W., & Helbig, J. (2013). Recommendations for implementing the strategic initiative INDUSTRIE 4.0: Final report of the Industrie 4.0 Working Group. Forschungsunion. https://www.din.de/resource/blob/76902/e8cac883f42bf28536e7e8165993f1fd/recommendations-for-implementing-industry-4-0-data.pdf

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. DOI: https://doi.org/10.1016/j.mfglet.2014.12.001

Liao, Y., Deschamps, F., Loures, E. D. F. R., & Ramos, L. F. P. (2017). Past, present and future of Industry 4.0-a systematic literature review and research agenda proposal. International Journal of Production Research, 55(12), 3609-3629. DOI: https://doi.org/10.1080/00207543.2017.1308576

Porter, M. E., & Heppelmann, J. E. (2015). How smart, connected products are transforming companies. Harvard Business Review, 93(10), 96-114.

Frank, A. G., Mendes, G. H., Ayala, N. F., & Ghezzi, A. (2019). Servitization and Industry 4.0 convergence in the digital transformation of product firms: A business model innovation perspective. Technological Forecasting and Social Change, 141, 341-351. DOI: https://doi.org/10.1016/j.techfore.2019.01.014