摘要
深度强化学习在智能制造领域具有广泛的应用前景。文章概述了相关文献的综述,总结了深度强化学习在智能制造领域的几个主要应用方向,如自动化控制、智能优化调度、故障预测与维修、品质控制与质量预测以及智能物流和供应链管理。在这些领域,深度强化学习利用深度学习网络和强化学习算法,能够实现更高效、更精准、更智能化的制造过程控制和管理。同时,探讨了深度强化学习在智能制造中面临的挑战和未来发展方向。这些研究对推动智能制造领域的发展,提高制造过程的效率和质量具有重要意义。
Deep reinforcement learning has broad application prospects in the field of intelligent manufacturing.Through a review of relevant literature,this paper summarizes several main application directions of deep reinforcement learning in the field of intelligent manufacturing:automatic control,intelligent optimal scheduling,fault prediction and maintenance,quality control and quality prediction,and intelligent logistics and supply chain management.Among these application directions,deep reinforcement learning can achieve more efficient,more accurate,and more intelligent manufacturing process control and management through deep learning networks and reinforcement learning algorithms.At the same time,the challenges and future development directions of deep reinforcement learning in intelligent manufacturing are also discussed.
作者
吕金旭
葛万成
LYU Jinxu;GE Wancheng(Tongji University,Shanghai 201800,China)
出处
《信息与电脑》
2023年第5期186-188,193,共4页
Information & Computer
关键词
人工智能
深度强化学习
智能控制
智能制造
artificial intelligence
deep reinforcement learning
intelligent control
intelligent manufacturing
