eXplainable artificial intelligence for automatic defect detection in additively manufactured parts using CT scan analysis
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Online first articles
Articles not assigned to an issue 238 articles
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Real-time monitoring and quality assurance for laser-based directed energy deposition: integrating co-axial imaging and self-supervised deep learning framework
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Semantic part segmentation of spatial features via geometric deep learning for automated control cabinet assembly
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Neural-network-based automatic trajectory adaptation for quality characteristics control in powder compaction
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Enterprise and service−level scheduling of robot production services in cloud manufacturing with deep reinforcement learning
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Study on anti-interference detection of machining surface defects under the influence of complex environment
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Supply chain modelling considering blockchain improvement and publicity with fairness concern
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Prediction of cutting force via machine learning: state of the art, challenges and potentials
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Acoustic emission reflection signal classification of PVDF-type AE sensor using convolutional neural network-transfer learning
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Deformation by design: data-driven approach to predict and modify deformation in thin Ti-6Al-4V sheets using laser peen forming
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Automatic model generation for material flow simulations of Third-Party Logistics
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Digital twin-based real-time energy optimization method for production line considering fault disturbances
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Ontology of 3D virtual modeling in digital twin: a review, analysis and thinking
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Cloud material handling systems: a cyber-physical system to enable dynamic resource allocation and digital interoperability
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A signal-to-image fault classification method based on multi-sensor data for robotic grinding monitoring
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Praxis: a framework for AI-driven human action recognition in assembly
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A digital twin-driven cutting force adaptive control approach for milling process
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Reinforcement learning for sustainability enhancement of production lines
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Research on flexible job shop scheduling problem with AGV using double DQN
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Designing an adaptive and deep learning based control framework for modular production systems
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Efficient quality variable prediction of industrial process via fuzzy neural network with lightweight structure
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Dual prototypical contrastive network: a novel self-supervised method for cross-domain few-shot fault diagnosis
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An intelligent prediction method of surface residual stresses based on multi-source heterogeneous data
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Machine vision-based recognition of elastic abrasive tool wear and its influence on machining performance
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Towards automated remote sizing and hot steel manufacturing with image registration and fusion
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An imbalanced data learning approach for tool wear monitoring based on data augmentation
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Critical analysis of the impact of artificial intelligence integration with cutting-edge technologies for production systems
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A survey on HoloLens AR in support of human-centric intelligent manufacturing
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Natural language processing (NLP) and association rules (AR)-based knowledge extraction for intelligent fault analysis: a case study in semiconductor industry
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The asset administration shell as enabler for predictive maintenance: a review
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Tool wear classification in precision machining using distance metrics and unsupervised machine learning
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Investigation on eXtreme Gradient Boosting for cutting force prediction in milling
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Wafer map defect recognition based on multi-scale feature fusion and attention spatial pyramid pooling
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3DWS: reliable segmentation on intelligent welding systems with 3D convolutions
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Enhanced modeling method of thermal behaviors in machine tool motorized spindles based on the mixture of thermal mechanism and machine learning
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Deep learning-based conductive particle inspection for TFT-LCDs inspired by parametric space envelope
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High accuracy roll forming springback prediction model of SVR based on SA-PSO optimization
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Q-learning-based multi-objective particle swarm optimization with local search within factories for energy-efficient distributed flow-shop scheduling problem
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DL-MSCNN: a general and lightweight framework for fault diagnosis with limited training samples
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