Analyzing the Application of Digital Twin Technology in Manufacturing Processes

Digital twins and machine learning, two contemporary information technology, have opened up new possibilities for the digital display, visualization, and monitoring of industrial processes. This research suggests utilizing machine learning, visualization, and monitoring approaches to analyze the use of digital twins in industrial process control. This novel method integrates real-time performance data and machine learning for monitoring, visualization, and prediction. In particular, trends and preferences are found and future situations are predicted by machine learning approaches. A variety of situations are created and assessed with the use of digital twins, and information is gathered to train machine learning algorithms on actual data.

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Publication Details

Published
2024-08-29
DOI
https://doi.org/10.1109/is61756.2024.10705254
Citations
1
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
0.35
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article

Analyzing the Application of Digital Twin Technology in Manufacturing Processes

Assiya Boltaboyeva, Баглан Иманбек, Nurdaulet Tasmurzayev, Мадина Мансурова et al.
1 citations
Digital Transformation in Industry
0.35
article

Analyzing the Application of Digital Twin Technology in Manufacturing Processes

Assiya Boltaboyeva, Баглан Иманбек, Nurdaulet Tasmurzayev, Мадина Мансурова, Bibars Amangeldy, Nurgul Karymssakova
article en
1 citations

Abstract

Digital twins and machine learning, two contemporary information technology, have opened up new possibilities for the digital display, visualization, and monitoring of industrial processes. This research suggests utilizing machine learning, visualization, and monitoring approaches to analyze the use of digital twins in industrial process control. This novel method integrates real-time performance data and machine learning for monitoring, visualization, and prediction. In particular, trends and preferences are found and future situations are predicted by machine learning approaches. A variety of situations are created and assessed with the use of digital twins, and information is gathered to train machine learning algorithms on actual data.

Al-Farabi Kazakh National University (KZ)
Industry, innovation and infrastructure
Openalex Percentile: Top 35%
Digital Transformation in Industry
0.35
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Analyzing the Application of Digital Twin Technology in Manufacturing Processes — Assiya Boltaboyeva, Баглан Иманбек, et al. · (2024) | TGRS Research Map | TGRS