Harnessing Machine Learning for Data Transformation in Industry 5.0 Production Lines
Received: 6 April 2025 | Revised: 26 April 2025 | Accepted: 4 May 2025 | Online: 30 June 2025
Corresponding author: Varalakshmi Byadigere Doddathimmaiah
Abstract
Industry 5.0 constitutes a significant revolution in the manufacturing sector, wherein advanced technologies and human-centric principles are combined to reshape processes. Machine learning (ML)-based interfaces are crucial for this transformation, offering opportunities for optimization and innovation. However, Industry 5.0 presents challenges such as data complexity and interoperability. To address these challenges, a holistic approach is proposed, combining ML techniques with intuitive interfaces to establish intelligent manufacturing environments. Predictive maintenance algorithms optimize equipment performance and minimize downtime, whereas intuitive interfaces facilitate seamless human-machine interaction. This system promises improved operational efficiency, enhanced quality, and cost reduction, paving the way for a transformative Industry 5.0 paradigm. Addressing these challenges requires careful attention to data quality, seamless integration with existing systems, and user-friendly interfaces in resource-constrained environments.
Keywords:
AC/DC current, acoustic emission, data analytics, Industry 5.0, machine learning-based interfaces, predictive analytics, spindle motorDownloads
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Copyright (c) 2025 Varalakshmi B D, Lingaraju G M
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