标题
Deep reinforcement learning in smart manufacturing: A review and prospects
作者
关键词
-
出版物
CIRP Journal of Manufacturing Science and Technology
Volume 40, Issue -, Pages 75-101
出版商
Elsevier BV
发表日期
2022-12-02
DOI
10.1016/j.cirpj.2022.11.003
参考文献
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注意:仅列出部分参考文献,下载原文获取全部文献信息。- Investigating the multi-objective optimization of quality and efficiency using deep reinforcement learning
- (2022) Zhenhui Wang et al. APPLIED INTELLIGENCE
- Modelling and condition-based control of a flexible and hybrid disassembly system with manual and autonomous workstations using reinforcement learning
- (2022) Marco Wurster et al. JOURNAL OF INTELLIGENT MANUFACTURING
- Energy management based on multi-agent deep reinforcement learning for a multi-energy industrial park
- (2022) Dafeng Zhu et al. APPLIED ENERGY
- Safe reinforcement learning for real-time automatic control in a smart energy-hub
- (2022) Dawei Qiu et al. APPLIED ENERGY
- A strategy transfer approach for intelligent human-robot collaborative assembly
- (2022) Qibing Lv et al. COMPUTERS & INDUSTRIAL ENGINEERING
- Reinforcement Learning in Manufacturing Control: Baselines, challenges and ways forward
- (2022) Vladimir Samsonov et al. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
- Using the proximal policy optimisation algorithm for solving the stochastic capacitated lot sizing problem
- (2022) Lotte van Hezewijk et al. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
- Deep reinforcement learning for dynamic scheduling of a flexible job shop
- (2022) Renke Liu et al. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
- A graph-based reinforcement learning-enabled approach for adaptive human-robot collaborative assembly operations
- (2022) Rong Zhang et al. JOURNAL OF MANUFACTURING SYSTEMS
- Toward human-centric smart manufacturing: A human-cyber-physical systems (HCPS) perspective
- (2022) Baicun Wang et al. JOURNAL OF MANUFACTURING SYSTEMS
- Research on a collaboration model of green closed-loop supply chains towards intelligent manufacturing
- (2022) Jin Qi et al. MULTIMEDIA TOOLS AND APPLICATIONS
- Motion control for laser machining via reinforcement learning
- (2022) Yunhui Xie et al. OPTICS EXPRESS
- Reinforcement learning for online optimization of job-shop scheduling in a smart manufacturing factory
- (2022) Tong Zhou et al. Advances in Mechanical Engineering
- Deep Reinforcement Learning for Dynamic Flexible Job Shop Scheduling with Random Job Arrival
- (2022) Jingru Chang et al. Processes
- Deep Reinforcement Learning for Robotic Control in High-Dexterity Assembly Tasks - A Reward Curriculum Approach
- (2022) Lars Leyendecker et al. International Journal of Semantic Computing
- Digital twin-enabled dynamic scheduling with preventive maintenance using a double-layer Q-learning algorithm
- (2022) Qi Yan et al. COMPUTERS & OPERATIONS RESEARCH
- Deep reinforcement learning applied to an assembly sequence planning problem with user preferences
- (2022) Miguel Neves et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- A multi-objective reinforcement learning approach for resequencing scheduling problems in automotive manufacturing systems
- (2022) Jinling Leng et al. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
- Instant flow distribution network optimization in liquid composite molding using deep reinforcement learning
- (2022) Martin Szarski et al. JOURNAL OF INTELLIGENT MANUFACTURING
- Graph neural network and multi-agent reinforcement learning for machine-process-system integrated control to optimize production yield
- (2022) Jing Huang et al. JOURNAL OF MANUFACTURING SYSTEMS
- Opportunistic maintenance scheduling with deep reinforcement learning
- (2022) Alexander Valet et al. JOURNAL OF MANUFACTURING SYSTEMS
- Average reward adjusted deep reinforcement learning for order release planning in manufacturing
- (2022) Manuel Schneckenreither et al. KNOWLEDGE-BASED SYSTEMS
- Logistics-involved service composition in a dynamic cloud manufacturing environment: A DDPG-based approach
- (2022) Yongkui Liu et al. ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
- AR-assisted digital twin-enabled robot collaborative manufacturing system with human-in-the-loop
- (2022) Chengxi Li et al. ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
- An integrated energy management system using double deep Q-learning and energy storage equipment to reduce energy cost in manufacturing under real-time pricing condition: A case study of scale-model factory
- (2022) Li Yi et al. CIRP Journal of Manufacturing Science and Technology
- MPR-RL: Multi-Prior Regularized Reinforcement Learning for Knowledge Transfer
- (2022) Quantao Yang et al. IEEE Robotics and Automation Letters
- Dynamic Robot Assignment for Flexible Serial Production Systems
- (2022) Kshitij Bhatta et al. IEEE Robotics and Automation Letters
- Multi-Agent Reinforcement Learning for Real-Time Dynamic Production Scheduling in a Robot Assembly Cell
- (2022) Dazzle Johnson et al. IEEE Robotics and Automation Letters
- Alternative multi-label imitation learning framework monitoring tool wear and bearing fault under different working conditions
- (2022) Zisheng Wang et al. ADVANCED ENGINEERING INFORMATICS
- Multi-agent reinforcement learning based on graph convolutional network for flexible job shop scheduling
- (2022) Xuan Jing et al. JOURNAL OF INTELLIGENT MANUFACTURING
- Dynamic scheduling of tasks in cloud manufacturing with multi-agent reinforcement learning
- (2022) Xiaohan Wang et al. JOURNAL OF MANUFACTURING SYSTEMS
- Hybrid feedback and reinforcement learning-based control of machine cycle time for a multi-stage production system
- (2022) Chen Li et al. JOURNAL OF MANUFACTURING SYSTEMS
- Digital twin and deep reinforcement learning enabled real-time scheduling for complex product flexible shop-floor
- (2022) Xiao Chang et al. PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE
- An electromyography signals-based human-robot collaboration system for human motion intention recognition and realization
- (2022) Tie Zhang et al. ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
- Solving job scheduling problems in a resource preemption environment with multi-agent reinforcement learning
- (2022) Xiaohan Wang et al. ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
- Probing an intelligent predictive maintenance approach with deep learning and augmented reality for machine tools in IoT-enabled manufacturing
- (2022) Changchun Liu et al. ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
- Dynamic scheduling for semiconductor manufacturing systems with uncertainties using convolutional neural networks and reinforcement learning
- (2022) Juan Liu et al. Complex & Intelligent Systems
- Reinforcement learning for industrial process control: A case study in flatness control in steel industry
- (2022) Jifei Deng et al. COMPUTERS IN INDUSTRY
- Distributed Real-Time Scheduling in Cloud Manufacturing by Deep Reinforcement Learning
- (2022) Lixiang Zhang et al. IEEE Transactions on Industrial Informatics
- Artificial-intelligence-based maintenance decision-making and optimization for multi-state component systems
- (2022) Van-Thai Nguyen et al. RELIABILITY ENGINEERING & SYSTEM SAFETY
- Multi-agent deep reinforcement learning based Predictive Maintenance on parallel machines
- (2022) Marcelo Luis Ruiz Rodríguez et al. ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
- Dynamic job shop scheduling based on deep reinforcement learning for multi-agent manufacturing systems
- (2022) Yi Zhang et al. ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
- An AR-assisted Deep Reinforcement Learning-based approach towards mutual-cognitive safe human-robot interaction
- (2022) Chengxi Li et al. ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
- Scheduling of decentralized robot services in cloud manufacturing with deep reinforcement learning
- (2022) Yongkui Liu et al. ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
- A fast decision-making method for process planning with dynamic machining resources via deep reinforcement learning
- (2021) Wenbo Wu et al. JOURNAL OF MANUFACTURING SYSTEMS
- Levering Task Modularity in Reinforcement Learning for Adaptable Industry 4.0 Automation
- (2021) Qiliang Chen et al. JOURNAL OF MECHANICAL DESIGN
- Algorithmic Approaches to Inventory Management Optimization
- (2021) Hector D. Perez et al. Processes
- Dynamic Job-shop Scheduling in Smart Manufacturing using Deep Reinforcement Learning
- (2021) Libing Wang et al. Computer Networks
- A robot arm digital twin utilising reinforcement learning
- (2021) Marius Matulis et al. COMPUTERS & GRAPHICS-UK
- Automation of load balancing for Gantt planning using reinforcement learning
- (2021) Jong Hun Woo et al. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
- KIcker: An Industrial Drive and Control Foosball System automated with Deep Reinforcement Learning
- (2021) Stefano De Blasi et al. JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
- Fault-Tolerant Control of Programmable Logic Controller-Based Production Systems With Deep Reinforcement Learning
- (2021) Jonas Zinn et al. JOURNAL OF MECHANICAL DESIGN
- A Reinforcement Learning Approach to View Planning for Automated Inspection Tasks
- (2021) Christian Landgraf et al. SENSORS
- Hierarchical Reinforcement Learning
- (2021) Shubham Pateria et al. ACM COMPUTING SURVEYS
- Intelligent fault recognition framework by using deep reinforcement learning with one dimension convolution and improved actor-critic algorithm
- (2021) Zisheng Wang et al. ADVANCED ENGINEERING INFORMATICS
- Deep reinforcement learning-based safe interaction for industrial human-robot collaboration using intrinsic reward function
- (2021) Quan Liu et al. ADVANCED ENGINEERING INFORMATICS
- Decentralized learning of energy optimal production policies using PLC-informed reinforcement learning
- (2021) Dorothea Schwung et al. COMPUTERS & CHEMICAL ENGINEERING
- Deep reinforcement learning in production systems: a systematic literature review
- (2021) Marcel Panzer et al. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
- Modular production control using deep reinforcement learning: proximal policy optimization
- (2021) Sebastian Mayer et al. JOURNAL OF INTELLIGENT MANUFACTURING
- Optimizing task scheduling in human-robot collaboration with deep multi-agent reinforcement learning
- (2021) Tian Yu et al. JOURNAL OF MANUFACTURING SYSTEMS
- A Novel Approach to the Job Shop Scheduling Problem Based on the Deep Q-Network in a Cooperative Multi-Access Edge Computing Ecosystem
- (2021) Junhyung Moon et al. SENSORS
- A full freedom pose measurement method for industrial robot based on reinforcement learning algorithm
- (2021) Xinghua Lu et al. SOFT COMPUTING
- Application of Machine Learning and Rule Scheduling in a Job-Shop Production Control System
- (2021) Y. Zhao et al. International Journal of Simulation Modelling
- A Review of Deep Reinforcement Learning for Smart Building Energy Management
- (2021) Liang Yu et al. IEEE Internet of Things Journal
- Successful Pass Schedule Design in Open-Die Forging Using Double Deep Q-Learning
- (2021) Niklas Reinisch et al. Processes
- Dynamic matching with deep reinforcement learning for a two-sided Manufacturing-as-a-Service (MaaS) marketplace
- (2021) Deepak Pahwa et al. Manufacturing Letters
- AI-enabled dynamic finish machining optimization for sustained surface integrity
- (2021) Julius Schoop et al. Manufacturing Letters
- Agent-based approach integrating deep reinforcement learning and hybrid genetic algorithm for dynamic scheduling for Industry 3.5 smart production
- (2021) Chen-Fu Chien et al. COMPUTERS & INDUSTRIAL ENGINEERING
- A flexible manufacturing assembly system with deep reinforcement learning
- (2021) Junzheng Li et al. CONTROL ENGINEERING PRACTICE
- Evolutionary job scheduling with optimized population by deep reinforcement learning
- (2021) Detian Zeng et al. ENGINEERING OPTIMIZATION
- Adaptive disassembly sequence planning for VR maintenance training via deep reinforcement learning
- (2021) Haoyang Mao et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- Simulation and deep reinforcement learning for adaptive dispatching in semiconductor manufacturing systems
- (2021) Ahmed H. Sakr et al. JOURNAL OF INTELLIGENT MANUFACTURING
- Towards Self-X cognitive manufacturing network: An industrial knowledge graph-based multi-agent reinforcement learning approach
- (2021) Pai Zheng et al. JOURNAL OF MANUFACTURING SYSTEMS
- A fuzzy hierarchical reinforcement learning based scheduling method for semiconductor wafer manufacturing systems
- (2021) Junliang Wang et al. JOURNAL OF MANUFACTURING SYSTEMS
- Machining sequence learning via inverse reinforcement learning
- (2021) Yasutomo Sugisawa et al. PRECISION ENGINEERING-JOURNAL OF THE INTERNATIONAL SOCIETIES FOR PRECISION ENGINEERING AND NANOTECHNOLOGY
- A reinforcement learning method for human-robot collaboration in assembly tasks
- (2021) Rong Zhang et al. ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
- Specifying and optimizing robotic motion for visual quality inspection
- (2021) Zvezdan Lončarević et al. ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
- Adaptive optimal control of stencil printing process using reinforcement learning
- (2021) Nourma Khader et al. ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
- A visual path-following learning approach for industrial robots using DRL
- (2021) Alan Maldonado-Ramirez et al. ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
- Reinforcement-Learning-Based Signal Integrity Optimization and Analysis of a Scalable 3-D X-Point Array Structure
- (2021) Kyungjune Son et al. IEEE Transactions on Components Packaging and Manufacturing Technology
- Deep reinforcement learning based mobile robot navigation: A review
- (2021) Kai Zhu et al. TSINGHUA SCIENCE AND TECHNOLOGY
- Thermal control of laser powder bed fusion using deep reinforcement learning
- (2021) Francis Ogoke et al. Additive Manufacturing
- An implementation of a reinforcement learning based algorithm for factory layout planning
- (2021) Matthias Klar et al. Manufacturing Letters
- Deep reinforcement learning based scheduling within production plan in semiconductor fabrication
- (2021) Young Hoon Lee et al. EXPERT SYSTEMS WITH APPLICATIONS
- Deep multi-agent reinforcement learning for multi-level preventive maintenance in manufacturing systems
- (2021) Jianyu Su et al. EXPERT SYSTEMS WITH APPLICATIONS
- A Cooperative Memetic Algorithm With Learning-Based Agent for Energy-Aware Distributed Hybrid Flow-Shop Scheduling
- (2021) Jing-Jing Wang et al. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
- Real-time data-driven dynamic scheduling for flexible job shop with insufficient transportation resources using hybrid deep Q network
- (2021) Yuxin Li et al. ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
- Scalable Scheduling of Semiconductor Packaging Facilities Using Deep Reinforcement Learning
- (2021) In-Beom Park et al. IEEE Transactions on Cybernetics
- Dynamic scheduling for flexible job shop with new job insertions by deep reinforcement learning
- (2020) Shu Luo APPLIED SOFT COMPUTING
- Task scheduling based on deep reinforcement learning in a cloud manufacturing environment
- (2020) Tingting Dong et al. CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
- Intelligent scheduling of discrete automated production line via deep reinforcement learning
- (2020) Daming Shi et al. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
- Deep reinforcement learning for selecting demand forecast models to empower Industry 3.5 and an empirical study for a semiconductor component distributor
- (2020) Chen-Fu Chien et al. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
- Cooperative multi-agent system for production control using reinforcement learning
- (2020) Marc-André Dittrich et al. CIRP ANNALS-MANUFACTURING TECHNOLOGY
- Real-time order dispatching for a fleet of autonomous mobile robots using multi-agent reinforcement learning
- (2020) Andreja Malus et al. CIRP ANNALS-MANUFACTURING TECHNOLOGY
- Self-repair of smart manufacturing systems by deep reinforcement learning
- (2020) Bogdan I. Epureanu et al. CIRP ANNALS-MANUFACTURING TECHNOLOGY
- A Review on Reinforcement Learning: Introduction and Applications in Industrial Process Control
- (2020) Rui Nian et al. COMPUTERS & CHEMICAL ENGINEERING
- Spatial arrangement using deep reinforcement learning to minimise rearrangement in ship block stockyards
- (2020) Byeongseop Kim et al. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
- Reinforcement learning-based collision-free path planner for redundant robot in narrow duct
- (2020) Xiaotong Hua et al. JOURNAL OF INTELLIGENT MANUFACTURING
- Petri-net-based dynamic scheduling of flexible manufacturing system via deep reinforcement learning with graph convolutional network
- (2020) Liang Hu et al. JOURNAL OF MANUFACTURING SYSTEMS
- Deep Reinforcement Learning-Based Optimal Decoupling Capacitor Design Method for Silicon Interposer-Based 2.5-D/3-D ICs
- (2020) Hyunwook Park et al. IEEE Transactions on Components Packaging and Manufacturing Technology
- Run-to-Run Control of Chemical Mechanical Polishing Process Based on Deep Reinforcement Learning
- (2020) Jianbo Yu et al. IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING
- Designing an adaptive production control system using reinforcement learning
- (2020) Andreas Kuhnle et al. JOURNAL OF INTELLIGENT MANUFACTURING
- Deep reinforcement learning for a color-batching resequencing problem
- (2020) Jinling Leng et al. JOURNAL OF MANUFACTURING SYSTEMS
- Reinforcement learning for facilitating human-robot-interaction in manufacturing
- (2020) Harley Oliff et al. JOURNAL OF MANUFACTURING SYSTEMS
- A digital twin to train deep reinforcement learning agent for smart manufacturing plants: Environment, interfaces and intelligence
- (2020) Kaishu Xia et al. JOURNAL OF MANUFACTURING SYSTEMS
- Utilization of a reinforcement learning algorithm for the accurate alignment of a robotic arm in a complete soft fabric shoe tongues automation process
- (2020) Yu-Ting Tsai et al. JOURNAL OF MANUFACTURING SYSTEMS
- Multi-agent deep reinforcement learning based demand response for discrete manufacturing systems energy management
- (2020) Renzhi Lu et al. APPLIED ENERGY
- Machine learning for clothing manufacture as a mean to respond quicker and better to the demands of clothing brands: a Greek case study
- (2020) Evridiki Papachristou et al. The International Journal of Advanced Manufacturing Technology
- Injection Mold Production Sustainable Scheduling Using Deep Reinforcement Learning
- (2020) Seunghoon Lee et al. Sustainability
- Variable Compliance Control for Robotic Peg-in-Hole Assembly: A Deep-Reinforcement-Learning Approach
- (2020) Cristian C. Beltran-Hernandez et al. Applied Sciences-Basel
- Smart Manufacturing and Intelligent Manufacturing: A Comparative Review
- (2020) Baicun Wang et al. Engineering
- A deep reinforcement learning based multi-criteria decision support system for optimizing textile chemical process
- (2020) Zhenglei He et al. COMPUTERS IN INDUSTRY
- Deep reinforcement learning based preventive maintenance policy for serial production lines
- (2020) Jing Huang et al. EXPERT SYSTEMS WITH APPLICATIONS
- A deep transfer‐learning‐based dynamic reinforcement learning for intelligent tightening system
- (2020) Wentao Luo et al. INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
- A loosely-coupled deep reinforcement learning approach for order acceptance decision of mass-individualized printed circuit board manufacturing in industry 4.0
- (2020) Jiewu Leng et al. JOURNAL OF CLEANER PRODUCTION
- A novel impedance control method of rubber unstacking robot dealing with unpredictable and time-variable adhesion force
- (2020) Le Liang et al. ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
- Smart Manufacturing Scheduling With Edge Computing Using Multiclass Deep Q Network
- (2019) Chun-Cheng Lin et al. IEEE Transactions on Industrial Informatics
- Modeling, planning, and scheduling of shop-floor assembly process with dynamic cyber-physical interactions: a case study for CPS-based smart industrial robot production
- (2019) Qingmeng Tan et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- A reinforcement learning decision model for online process parameters optimization from offline data in injection molding
- (2019) Fei Guo et al. APPLIED SOFT COMPUTING
- Model-free Adaptive Optimal Control of Episodic Fixed-horizon Manufacturing Processes Using Reinforcement Learning
- (2019) Johannes Dornheim et al. INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
- Trajectory smoothing method using reinforcement learning for computer numerical control machine tools
- (2019) Bingran Li et al. ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
- Reinforcement learning based on movement primitives for contact tasks
- (2019) Young-Loul Kim et al. ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
- Granular Prediction and Dynamic Scheduling Based on Adaptive Dynamic Programming for the Blast Furnace Gas System
- (2019) Jun Zhao et al. IEEE Transactions on Cybernetics
- An intelligent non-optimality self-recovery method based on reinforcement learning with small data in big data era
- (2018) Yan Qin et al. CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
- Facilitating Human-Robot Collaborative Tasks by Teaching-Learning-Collaboration From Human Demonstrations
- (2018) Weitian Wang et al. IEEE Transactions on Automation Science and Engineering
- Reinforcement learning based compensation methods for robot manipulators
- (2018) Yudha P. Pane et al. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
- Intelligent laser welding through representation, prediction, and control learning: An architecture with deep neural networks and reinforcement learning
- (2016) Johannes Günther et al. MECHATRONICS
- Mastering the game of Go with deep neural networks and tree search
- (2016) David Silver et al. NATURE
- Collaborative reinforcement learning for a two-robot job transfer flow-shop scheduling problem
- (2015) Kfir Arviv et al. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
- Natural actor–critic algorithms
- (2009) Shalabh Bhatnagar et al. AUTOMATICA
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