Journal of Intelligent Manufacturing

Papers
(The H4-Index of Journal of Intelligent Manufacturing is 38. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-09-01 to 2024-09-01.)
ArticleCitations
Remaining useful life estimation via transformer encoder enhanced by a gated convolutional unit135
Artificial intelligence systems for tool condition monitoring in machining: analysis and critical review124
Synthetic data augmentation for surface defect detection and classification using deep learning113
Machine learning and deep learning based predictive quality in manufacturing: a systematic review110
Modelling and prediction of surface roughness in wire arc additive manufacturing using machine learning105
A review of motion planning algorithms for intelligent robots93
Machine learning integrated design for additive manufacturing93
A steel surface defect inspection approach towards smart industrial monitoring91
Automated surface defect detection framework using machine vision and convolutional neural networks86
Applications of artificial intelligence in engineering and manufacturing: a systematic review86
Quality 4.0: a review of big data challenges in manufacturing86
Field-synchronized Digital Twin framework for production scheduling with uncertainty85
Designing and developing smart production planning and control systems in the industry 4.0 era: a methodology and case study76
Digitalization priorities of quality control processes for SMEs: a conceptual study in perspective of Industry 4.0 adoption73
From knowledge-based to big data analytic model: a novel IoT and machine learning based decision support system for predictive maintenance in Industry 4.071
Human-centred design in industry 4.0: case study review and opportunities for future research66
Machine learning techniques in additive manufacturing: a state of the art review on design, processes and production control64
Machine-learning for automatic prediction of flatness deviation considering the wear of the face mill teeth60
Enhancing wisdom manufacturing as industrial metaverse for industry and society 5.057
Machine learning with domain knowledge for predictive quality monitoring in resistance spot welding55
Tool wear condition monitoring based on a two-layer angle kernel extreme learning machine using sound sensor for milling process52
A systematic review of data-driven approaches to fault diagnosis and early warning51
An adaptive fault detection and root-cause analysis scheme for complex industrial processes using moving window KPCA and information geometric causal inference51
A digital twin emulator of a modular production system using a data-driven hybrid modeling and simulation approach50
Human factors in cobot era: a review of modern production systems features48
A novel transfer learning fault diagnosis method based on Manifold Embedded Distribution Alignment with a little labeled data47
Artificial intelligence application in fault diagnostics of rotating industrial machines: a state-of-the-art review46
Automated inspection in robotic additive manufacturing using deep learning for layer deformation detection44
Machine learning in continuous casting of steel: a state-of-the-art survey44
Improving the accuracy of machine-learning models with data from machine test repetitions44
On-line prediction of ultrasonic elliptical vibration cutting surface roughness of tungsten heavy alloy based on deep learning41
Machine learning-based optimization of process parameters in selective laser melting for biomedical applications41
Editorial: intelligent manufacturing systems towards industry 4.0 era41
A systematic literature review on recent trends of machine learning applications in additive manufacturing40
A novel approach of tool condition monitoring in sustainable machining of Ni alloy with transfer learning models40
An approach for tool wear prediction using customized DenseNet and GRU integrated model based on multi-sensor feature fusion40
An effective approach for the dual-resource flexible job shop scheduling problem considering loading and unloading40
Synthetic image data augmentation for fibre layup inspection processes: Techniques to enhance the data set39
Surface roughness stabilization method based on digital twin-driven machining parameters self-adaption adjustment: a case study in five-axis machining38
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