广东工业大学学报2025，Vol.42Issue(2)：59-69,11.
基于强化学习的注塑工艺参数自动调优方法及应用
Reinforcement Learning-based Automatic Tuning Method and Application of Injection Molding Process Parameters
摘要
Abstract
The optimization of injection molding process parameters is crucial in contemporary manufacturing,as it affects not only product quality but also production costs and efficiency.Traditional manual tuning methods rely on trial and error,leading to extended production cycles and increased costs.To address this,reinforcement learning(RL)technology is applied,for the first time,to the tuning of injection molding process parameters,proposing a novel automatic tuning algorithm based on RL for injection molding process parameters.The paper first models the injection molding process parameter tuning problem as a sequential decision-making problem and designs a customized Markov Decision Process model.Subsequently,a model-free RL method is proposed,implementing the automatic selection of injection molding process parameters based on the Q-learning algorithm.Compared with traditional methods,this algorithm can automatically explore and optimize process parameter configurations in dynamically changing production environments.Finally,the feasibility and effectiveness of the proposed method are experimentally validated,demonstrating significant application potential.关键词
注塑成型/强化学习/Q-learning/智能制造/知识自动化Key words
injection molding/reinforcement learning/Q-learning/intelligent manufacturing/knowledge automation分类
计算机与自动化引用本文复制引用
冯子豪,万会龙,林江豪,任志刚..基于强化学习的注塑工艺参数自动调优方法及应用[J].广东工业大学学报,2025,42(2):59-69,11.基金项目
国家自然科学基金资助项目(62073088) （62073088）
广东省基础与应用基础研究基金资助项目(2024A1515011768) （2024A1515011768）
