DIRECTIONS FOR USING ARTIFICIAL INTELLIGENCE TO ENHANCE ECONOMIC EFFICIENCY OF MANUFACTURING PROCESSES
DOI:
https://doi.org/10.5281/zenodo.19644068Keywords:
artificial intelligence, manufacturing efficiency, Industry 4.0, predictive maintenance, economic optimisation, machine learning, smart productionAbstract
The rapid advancement of artificial intelligence (AI) technologies is fundamentally transforming manufacturing
industries worldwide. This paper systematically examines the principal directions in which AI is deployed to enhance
economic efficiency across production processes, covering predictive maintenance, intelligent quality control, supply
chain optimisation, energy management, and adaptive production planning. Drawing on a comprehensive literature review,
industry case studies, and quantitative performance data from Uzbek and international enterprises, we assess both
the economic benefits and the implementation challenges organisations encounter. Our findings indicate that AI-driven
systems reduce unplanned downtime by 25-45%, lower defect rates by up to 60%, and decrease energy consumption
by 15-30%. We further demonstrate that manufacturing firms in emerging economies-including Uzbekistan can achieve
competitive returns on AI investment within 18-36 months when adoption is supported by adequate digital infrastructure
and workforce upskilling. The paper concludes with a strategic framework for policymakers and industry leaders seeking
to maximise AI-enabled economic gains in the manufacturing sector
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