The casting process manufactures products through complex comprehensive processes such as melting, molding, pouring, heat treatment, and surface treatment. Molding sand is regenerated and used. Regenerating equipment of molding sand is for that. This equipment is equipped with a scrubber, a sand cooler, a rotary reclaimer, etc., and is driven by a motor, and the fine dust generated at this time is treated through a dust collector. In the regenerating equipment of molding sand, process variables are current, voltage, pressure of the dust collector, and temperature/humidity of molding sand that can measure motor driving and dust collection. If the LOI (Loss on ignition) measurement value of the molding sand that is produced through the regenerating equipment is too high, the gas is mixed into the molten metal due to a large amount of gas generation, which affects the quality of the final product. Therefore, it is necessary to analyze the process variables of the equipment to reuse and manage sand. This study attempts to analyze the correlation between the LOI value of regenerating sand and process variable data of the regenerating equipment of molding sand using an AI algorithm.