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.
Authors
- Assiya Boltaboyeva (ORCID: https://orcid.org/0000-0002-7279-9910)
- Баглан Иманбек (ORCID: https://orcid.org/0000-0001-7249-380X)
- Nurdaulet Tasmurzayev (ORCID: https://orcid.org/0000-0003-3039-6715)
- Мадина Мансурова (ORCID: https://orcid.org/0000-0002-9680-2758)
- Bibars Amangeldy (ORCID: https://orcid.org/0000-0002-4089-6337)
- Nurgul Karymssakova
Institutions
- Al-Farabi Kazakh National University (KZ)
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