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Functionality of Digital Twin in Shopfloor Employees Training with AI and ML Technologies

In: Proceedings of the International Conference on Digital Transformation in Business: Navigating the New Frontiers Beyond Boundaries (DTBNNF 2024)

Author

Listed:
  • C.P. Chandra Mohini

    (VISTAS, Research Scholar, Department of Computer Science)

  • V. Raghavendran

    (VISTAS, Assistant Professor Department of Computer Science)

Abstract

The Digital Twin Technology is one of the fascinating innovations that shape the future. Digital Twin is an exact clone of a physical product, it replicates, not just the physical object but also its behavior and its entire life cycle. Digital Twin can be considered as a combined version of emerging technologies such as artificial intelligence (AI), Machine Learning (ML), Internet of Things (IoT), and Data Analytics. Digital twin technologies can be used as a training aid for shopfloor employees and their skill development. This research focuses on how to design and develop training programs to elevate employees’ skills for workforce development using digital twins of various machinery and equipment. Machine learning can be considered as a subset of Artificial Intelligence that allows computers to learn from data and experiences without special programming. Intelligent systems that are capable of handling difficult tasks can be developed using machine learning. Three primary categories of machine learning exist: reinforcement learning, unsupervised learning, and supervised learning.

Suggested Citation

  • C.P. Chandra Mohini & V. Raghavendran, 2024. "Functionality of Digital Twin in Shopfloor Employees Training with AI and ML Technologies," Advances in Economics, Business and Management Research, in: N. V. Suresh & P. S. Buvaneswari (ed.), Proceedings of the International Conference on Digital Transformation in Business: Navigating the New Frontiers Beyond Boundaries (DTBNNF 2024), pages 465-477, Springer.
    • Handle: RePEc:spr:advbcp:978-94-6463-433-4_35
    DOI: 10.2991/978-94-6463-433-4_35
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