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Shoe manufacturing involves melting rubber and pouring it into preheated molds to form soles. Maintaining optimal temperatures is critical—underheating causes incomplete filling, leading to defects, while overheating results in overburn and wasted material. An AI and IoT-based solution can optimize this process by using temperature sensors and real-time data analytics. IoT sensors continuously monitor the molten rubber and mold temperatures, sending data to an AI system that dynamically adjusts heating parameters. AI models analyze historical patterns to predict and prevent defects, ensuring precise temperature control. This automation reduces raw material wastage, minimizes electricity consumption, and enhances product quality. Additionally, predictive maintenance alerts prevent overheating-related equipment failures, improving efficiency and sustainability in shoe manufacturing.
