Harnessing Machine Learning for Data Transformation in Industry 5.0 Production Lines - Byadigere Doddathimmaiah, Varalakshmi; Gowdru Malleshappa, Lingaraju (Engineering, Technology & Applied Science Research, 2025)
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.