Justyna Hebda-Sobkowicz
Papers
1
Total Citations
14
H-Index
1
About
Justyna Hebda-Sobkowicz is a leading researcher at the intersection of industrial data science and predictive maintenance, with a primary focus on enhancing the reliability and efficiency of heavy machinery through advanced analytics. Her most cited work, "Predictive Maintenance of Mining Machines Using Advanced Data Analysis System Based on the Cloud Technology" (2019, 14 citations), exemplifies her core contribution: integrating cloud-based data analysis with machine learning to preemptively identify equipment failures in mining operations. This research has practical significance for reducing downtime and operational costs in resource-intensive industries. Beyond this flagship paper, her broader portfolio explores condition monitoring, signal processing, and fault diagnosis, often leveraging real-world industrial datasets. Her work is notable for bridging the gap between theoretical algorithms and deployable, cloud-native solutions—a critical step toward Industry 4.0 in mining. While her citation count reflects a focused, emerging impact, the applied nature of her research has attracted attention from both academic peers and industry practitioners. For students and researchers in mechanical engineering, data science, or industrial IoT, Hebda-Sobkowicz’s work offers a clear model of how to translate complex data analysis into tangible maintenance strategies that save resources and improve safety.
Research Focus
Key Achievements
Top Papers
- 1