Makarand Jadhav
Papers
1
Total Citations
16
H-Index
1
About
Dr. Makarand Jadhav is a leading researcher at the intersection of advanced manufacturing and artificial intelligence, with a primary focus on predictive maintenance and process optimization. His most notable contribution is the development of an AI-enhanced framework for hybrid roll-to-roll manufacturing, which integrates multi-sensor data with self-supervised learning to predict equipment failures before they occur. This work, published in 2024 and already garnering 16 citations, represents a significant leap forward in reducing downtime and improving yield in flexible electronics and printed device production. By enabling machines to learn from unlabeled operational data, Dr. Jadhav’s approach addresses a critical bottleneck in Industry 4.0: the scarcity of labeled fault data. His research not only advances the theoretical understanding of self-supervised learning in manufacturing contexts but also offers a practical, scalable solution for real-world production lines. Dr. Jadhav’s work is particularly impactful for students and engineers seeking to bridge the gap between cutting-edge AI and tangible industrial applications, demonstrating how intelligent systems can transform traditional manufacturing into a more resilient, data-driven ecosystem.
Research Focus
Key Achievements
Top Papers
- 1