A Review on Injection Molding: Conformal Cooling Channels, Modelling, Surrogate Models and Multi-Objective Optimization

Plastic injection molding is a fundamental manufacturing process utilized in diverse areas, producing approximately 30% of global plastic products. This review examines the optimization methodologies in injection molding, emphasizing the integration of advanced modeling, surrogate models, and multi-objective optimization techniques to enhance efficiency, quality, and sustainability. Key phases such as plasticizing, filling, packing, cooling, and ejection are analyzed, each presenting unique optimization challenges. The review highlights the significance of cooling, which constitutes 50-80% of the cycle time, and explores innovative strategies like conformal cooling channels (CCC) to improve uniformity and reduce defects. Various computational tools, including Moldex3D and Autodesk Moldflow, are discussed due to their role in process simulation and optimization. Additionally, optimization algorithms such as evolutionary algorithms, simulated annealing, and multi-objective optimization methods are explored. Integration of surrogate models like Kriging, response surface methodology, and artificial neural networks has shown promise in addressing computational cost challenges. Future directions emphasize the need for adaptive machine learning and artificial intelligence techniques to optimize molds in real time, offering more innovative and sustainable manufacturing solutions. This review is a comprehensive guide for researchers and practitioners, bridging theoretical advancements with practical implementation in injection molding optimization.