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While many industrial processes have been thoroughly exposed to machine learning models, the realm of powder metallurgy is still underexplored. This thesis aims to investigate the potential for a machine learning model to predict the characteristics of metal powders after a reduction annealing process using time series process data from the furnace. A supervised learning model was developed to pre
