As systems in smart manufacturing become increasingly complex, producing an abundance of data, the potential for production failures becomes increasingly more likely. There arises the need to minimize or eradicate production failures, one of which is by means of anomaly detection. However, with the deployment of anomaly detection systems, there are many aspects to be considered. In this paper, an overview of the components, benefits, challenges, methods, and open problems of anomaly detection in smart manufacturing and robotic finishing systems are discussed.
WorkBenchMark: A LEGO-Based Assembly Benchmark with an Assembly-by-Disassembly Baseline for the Smart Manufacturing League
Chair of Machine Learning and Reasoning (i6), RWTH Aachen University（亚琛工业大学机器学习与推理教席（i6））；MASCOR Institute, FH Aachen University of Applied Science（亚琛应用技术大学MASCOR研究所）
Coordinated motion control of a wire arc additive manufacturing robotic system for multi-directional building parts
Faculty of Electrical Engineering, Federal University of South and Southeast of Pará（电气工程学院，南和东南巴西北部联邦大学）；Department of Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute（电气、计算机和系统工程系，伦塞拉尔理工大学）；Department of Electrical Engineering, COPPE, Federal University of Rio de Janeiro（电气工程系，COPPE，里约热内卢联邦大学）
On Fulfilling the Exigent Need for Automating and Modernizing Logistics Infrastructure in India: Enabling AI-based Integration, Digitalization, and Smart Automation of Industrial Parks and Robotic Warehouses
Artificial Intelligence-Driven Customized Manufacturing Factory: Key Technologies, Applications, and Challenges
South China University of Technology（华南理工大学）；Zhongkai University of Agriculture and Engineering（仲恺农业工程学院）；Macau University of Science and Technology（澳门科技大学）；The University of Iowa（爱荷华大学）；Loughborough University（拉夫堡大学）
Stage-Aware and Roughness-Constrained Diffusion Policy for Multi-Stage Robotic Polishing
State Key Laboratory of Intelligent Manufacturing Equipment and Technology, Huazhong University of Science and Technology（华中科技大学智能制造装备与技术国家重点实验室）；Shanghai Spaceflight Precision Machinery Institute（上海航天精密机械研究所）
Digital Twin Synchronization: Bridging the Sim-RL Agent to a Real-Time Robotic Additive Manufacturing Control
Department of Mechanical Engineering, University of Louisiana at Lafayette（路易斯安那大学拉斐特分校机械工程系）；Computer Science & Information Systems Department, Bradley University（布雷纳德大学计算机科学与信息系统系）
