Author

C. R. Tripathy

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#edge computing Open access Sep 2026

IoT-based multi-sensor fusion predictive maintenance of 3D printers using an ensemble model framework

An optimised hybrid ensemble learning strategy integrating threshold-based detection, Isolation Forest, Random Forest, Support Vector Machine (SVM), and Logistic Regression (LR) classifiers is proposed to improve fault detection accuracy in IoT-enabled 3D printers.

Chitranjanjit Kaur, S. Chopra, C. R. Tripathy · Discover Computing · 0 citations

Open access Aug 2026

An Explainable IoT-Enabled Predictive Maintenance Framework Using Digital Twin and Multi-Sensor Machine Learning

A number of physically meaningful indicators, including thermal instability, vibration anomalies, smoke-related features, and aggregated risk scores, have a significant impact on maintenance predictions and hence provide better operational interpretability and maintenance transparency.

Chitranjanjit Kaur, S. Chopra, C. R. Tripathy · Automation · 0 citations