Author:Dr. Kavita Sharma,Mr. Aditya Singh
Abstract: The advancement of Computer Aided Manufacturing (CAM) has significantly improved production efficiency and quality. However, machine downtime and unexpected failures remain major challenges affecting operational productivity. This paper investigates predictive maintenance strategies empowered by big data analytics to enhance the reliability and availability of CAM systems. It explores various data acquisition techniques, analytical models, and implementation frameworks that enable early fault detection and condition-based maintenance. Two comprehensive tables summarize key big data sources and compare predictive maintenance techniques. The study also addresses challenges such as data management, model accuracy, and integration complexities. Finally, the paper provides insights into future directions in leveraging big data analytics for smarter maintenance solutions in CAM environments.
KEYWORDS
Predictive maintenance, Big data analytics, Computer aided manufacturing, Condition monitoring, Fault diagnosis, Data-driven maintenance
Full Issue
| View or download the full issue | PDF 20-25 |