Nurul Atiqah Dzulqarnain
Papers
1
Total Citations
5
H-Index
1
About
Nurul Atiqah Dzulqarnain is a researcher advancing the field of industrial automation and smart manufacturing, with a primary focus on condition monitoring and predictive maintenance. Her work addresses the critical challenge of minimizing downtime in production environments by developing data-driven frameworks that anticipate equipment failures before they occur. Her most cited paper, "Condition Monitoring for Predictive Maintenance of Machines and Processes in ARTC Model Factory" (2021), exemplifies this contribution by demonstrating a practical, integrated approach within a model factory setting, bridging the gap between theoretical algorithms and real-world industrial application. This research has garnered attention for its potential to optimize operational efficiency and reduce costs in manufacturing. While her citation count is still growing, her work is foundational in the context of Industry 4.0, where predictive analytics are key. Dzulqarnain’s research is particularly notable for its focus on the ARTC Model Factory, a testbed that validates her methods in a controlled yet realistic environment, making her findings directly relevant to engineers and researchers seeking to implement smart maintenance strategies in complex production systems.
Research Focus
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Top Papers
- 1