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ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
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INTEGRATION OF IOT TECHNOLOGIES INTO CNC MACHINING SYSTEMS: A CASE STUDY PERSPECTIVE FOR UZBEKISTAN'S MANUFACTURING SECTOR

Authors: Khalikulov Oybek Rustamjonovich; Kholkhujayev Jasurxo'ja Muxtor ugli;

INTEGRATION OF IOT TECHNOLOGIES INTO CNC MACHINING SYSTEMS: A CASE STUDY PERSPECTIVE FOR UZBEKISTAN'S MANUFACTURING SECTOR

Abstract

As Uzbekistan accelerates its transition towards an industrialized digital economy under the "Digital Uzbekistan 2030" strategy, modernizing existing manufacturing assets has become crucial. This paper analyzes the integration of Internet of Things (IoT) technologies into Computer Numerical Control (CNC) machining systems, focusing on local industrial contexts such as automotive and agricultural machinery production. While traditional CNC machines offer precision, they often lack connectivity. This study proposes a low-cost IoT architecture to monitor spindle load, vibration, and energy usage. Comparative analysis suggests that IoT integration can reduce unplanned downtime by 20-25% and optimize energy consumption by 12-15%. The findings provide a roadmap for Uzbek manufacturers to upgrade legacy equipment to Industry 4.0 standards cost-effectively.

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    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average