Remelting is used in the production of superalloy ingots. In these processes, stabilization of the solidification front is crucial in the prevention of segregation defects. However, models that account for solidification dynamics often are distributed-parameter multi-physics models that are not used in process control due to their complexity. This paper outlines model reduction for a remelting process based on a multi-physics finite volume model. A reduced-order model is constructed from a state-space realization where only transport phenomena are included. Balancing-free square-root singular perturbation approximation is used to construct a minimal reduced system, and then modal residualization is performed to remove modes that lie outside of the bandwidth of the actuators. The obtained reduced-order model was used to design an LQG controller. Simulation results verify that using the proposed reduced-order model for estimation and control can result in more accurate solidification control, when compared to a simplified model that accounts only for thermal processes.

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