Tilani Gallege
Papers
1
Total Citations
11
H-Index
1
About
Tilani Gallege is a researcher focused on industrial automation, predictive maintenance, and machine learning applications in manufacturing. Her most-cited work, "A Predictive Maintenance Application for A Robot Cell using LSTM Model" (2022), demonstrates how deep learning can leverage industrial data to forecast equipment failures, reducing downtime and improving production efficiency. This paper has garnered 11 citations, reflecting its relevance to the growing field of smart manufacturing and Industry 4.0. Gallege’s research addresses the critical challenge of maintaining production capacity in increasingly digitalized factories, showing how data-driven models can ensure long-term operational viability. Her contributions are particularly valuable for engineers and researchers seeking to implement cost-effective, proactive maintenance strategies in robotic systems. By bridging the gap between theoretical machine learning and practical industrial applications, Gallege is helping to shape the future of autonomous, self-optimizing production environments.
Research Focus
Key Achievements
Top Papers
- 1A Predictive Maintenance Application for A Robot Cell using LSTM Model11 citations · 2022