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Real-Time Optimal Parameter Recommendation For Injection Molding Machines Using AI With Limited Dataset by feelinspectacular is a document available to read on EtoBox.

This paper presents a novel framework for optimizing parameters in plastic injection molding using a genetic algorithm combined with a CatBoost surrogate model, aiming to reduce cycle time and energy consumption while maintaining product quality. The approach demonstrated a 4.5% reduction in cycle time and satisfied 95% of industrial quality constraints, showcasing its effectiveness in real-time optimization. The framework integrates data acquisition, surrogate modeling, and multi-objective optimization, pr

Author

feelinspectacular

Language

EN