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This is a Quantitative Study study.

October 3, 2025Open Access

Real-Time Thermal State Estimation and Forecasting in Laser Powder Bed Fusion

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This framework utilizes Kalman filtering for thermal state forecasting in laser powder bed fusion, enhancing temperature management.

The framework enables effective predictive thermal control in laser powder bed fusion processes, improving part quality.
Validation showed reliable temperature estimation and forecasting across varying part geometries, including peak temperatures.
The method integrates a physics-informed reduced-order thermal model with Kalman filtering for real-time tracking.
Successful thermal management may lead to the implementation of closed-loop control in laser powder bed fusion.

Pareek et al. (2025) studied this question.

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