Prandip Baishya
Papers
1
Total Citations
16
H-Index
1
About
Prandip Baishya is a researcher at the forefront of industrial automation and smart manufacturing, with a primary focus on predictive maintenance systems within the Industry 4.0 paradigm. His most cited work, "Implementation of Predictive Maintenance Systems in Remotely Located Process Plants under Industry 4.0 Scenario" (2019), has garnered 16 citations, establishing a foundational framework for integrating advanced sensor networks and data analytics into geographically dispersed industrial operations. Baishya’s key contributions lie in bridging the gap between theoretical IoT architectures and practical deployment challenges, particularly for remote and resource-constrained environments. By addressing real-time monitoring, fault prediction, and cost-effective sensor integration, his research directly supports the transition toward autonomous, data-driven plant management. This work has been instrumental in demonstrating how predictive maintenance can reduce downtime and operational costs in sectors like oil and gas, chemicals, and utilities. Baishya’s achievements underscore a commitment to solving tangible industrial problems, making his research highly relevant for engineers and scholars working on scalable, resilient cyber-physical systems. His ongoing efforts continue to shape how industries leverage digital twins and machine learning for proactive equipment health management.
Research Focus
Key Achievements
Top Papers
- 1