ECONOMIC EFFICIENCY OF WIDESPREAD USE OF ARTIFICIAL INTELLIGENCE IN INDUSTRIAL ENTERPRISES IN THE CONTEXT OF THE UZBEK ECONOMY
DOI:
https://doi.org/10.55640/Keywords:
artificial intelligence, Industry 4.0, predictive maintenance, OEE, ROI, TCO, supply chain, Uzbek industry, energy efficiency, digital transformation.Abstract
This article analyzes the economic efficiency of implementing artificial intelligence (AI) technologies in Uzbekistan’s industrial sectors. The main applications considered include process optimization, predictive maintenance, quality control, supply chain management, energy management, and occupational safety. Key performance indicators such as ROI, NPV, TCO, OEE, and TFP are proposed to assess efficiency. In addition, a practical “roadmap” and regulatory-organizational recommendations tailored to Uzbekistan’s conditions are provided. Investment-return factors are systematically explained through calculations and scenario examples.
References
1.Cobb, C. W., Douglas, P. H. (1928). A Theory of Production. American Economic Review, 18(1), 139–165.
2.Solow, R. M. (1957). Technical Change and the Aggregate Production Function. The Review of Economics and Statistics, 39(3), 312–320.
3.Jorgenson, D. W., Griliches, Z. (1967). The Explanation of Productivity Change. The Review of Economic Studies, 34(3), 249–283.
4.Kagermann, H., Wahlster, W., Helbig, J. (2013). Recommendations for Implementing the Strategic Initiative INDUSTRIE 4.0. acatech.
5.Liao, Y., Deschamps, F., Loures, E. R., Ramos, L. F. P. (2017). Past, present and future of Industry 4.0: A systematic literature review and research agenda. International Journal of Production Research, 55(12), 3609–3629.
6.Carvalho, T. P., Soares, F. A. A. M. N., Vita, R., et al. (2019). A systematic literature review of machine learning methods applied to predictive maintenance. Computers & Industrial Engineering, 137, 106024.
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