S. Neelima
Papers
1
Total Citations
16
H-Index
1
About
S. Neelima is a forward-thinking researcher at the intersection of artificial intelligence and advanced manufacturing, with a primary focus on predictive maintenance and intelligent process optimization. Her most influential work, "AI-enhanced predictive maintenance in hybrid roll-to-roll manufacturing integrating multi-sensor data and self-supervised learning" (2024), has already garnered 16 citations, signaling its timely impact on Industry 4.0. In this study, Neelima pioneered a novel framework that fuses multi-sensor data streams with self-supervised learning algorithms, enabling real-time anomaly detection and equipment failure prediction in complex roll-to-roll production lines. This contribution is particularly significant for reducing downtime and improving yield in high-throughput manufacturing environments. Her approach stands out for its ability to learn from unlabeled data, making it scalable and cost-effective for industrial applications. Neelima’s work bridges the gap between cutting-edge AI and practical manufacturing challenges, offering a blueprint for smarter, more resilient production systems. As a rising voice in her field, she continues to explore how autonomous learning can transform traditional processes, positioning her as a key innovator in the drive toward fully intelligent factories.
Research Focus
Key Achievements
Top Papers
- 1