Deepesh Upadrashta
Papers
1
Total Citations
5
H-Index
1
About
Deepesh Upadrashta is a researcher specializing in predictive maintenance, condition monitoring, and industrial automation, with a focus on integrating advanced sensing and data analytics into manufacturing processes. His work centers on developing real-time monitoring frameworks that enable early fault detection and proactive maintenance, reducing downtime and operational costs in smart factories. His most-cited paper, "Condition Monitoring for Predictive Maintenance of Machines and Processes in ARTC Model Factory" (2021, 5 citations), exemplifies his contribution to practical, industry-aligned solutions by demonstrating a systematic approach to monitoring machine health and process variability within a model factory environment. This work highlights his ability to bridge theoretical research with applied engineering, offering scalable methodologies for Industry 4.0 implementations. Upadrashta’s research impacts both academic understanding and industrial practice, providing a foundation for more resilient and efficient manufacturing systems. His achievements include advancing the use of sensor fusion and machine learning for predictive analytics, positioning him as a key contributor to the evolving field of intelligent maintenance and process optimization.
Research Focus
Key Achievements
Top Papers
- 1