Journal of Intelligent Manufacturing

Papers
(The H4-Index of Journal of Intelligent Manufacturing is 39. 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 2021-09-01 to 2025-09-01.)
ArticleCitations
From framework to industrial implementation: the digital twin in process planning225
Switch ON/OFF learning of one-dimensional convolutional neural network and one-dimensional generative adversarial network for fault detection185
Machine learning-based non-destructive method for identifying defect causes in OLED displays to enhance productivity168
Data-driven product configuration improvement and product line restructuring with text mining and multitask learning163
CENet: improve counting performance of X-ray surface mounted chip counter via scale favor and cell extraction163
Optimization of buffer design for mixed-model sequential production line based on simulation and reinforcement learning136
A normal weld recognition method for time-of-flight diffraction detection based on generative adversarial network120
Blockchain-based intelligent equipment assessment in manufacturing industry115
Variability-enhanced knowledge-based engineering (VEN) for reconfigurable molds100
A predictive modelling strategy for warpage and shrinkage defects in plastic injection molding using fuzzy logic and pattern search optimization92
Digital twin for product versus project lifecycles’ development in manufacturing and construction industries84
Random convolution layer: an auxiliary method to improve fault diagnosis performance75
Reverse engineering for programmable logic controller structure estimation via white box networks75
Digital Twin and web services for robotic deburring in intelligent manufacturing74
The multisensor information fusion-based deep learning model for equipment health monitor integrating subject matter expert knowledge71
Imbalanced fault diagnosis based on semi-supervised ensemble learning69
Warpage detection in 3D printing of polymer parts: a deep learning approach68
A machining feature recognition approach based on hierarchical neural network for multi-feature point cloud models68
A digital twin-assisted deep transfer learning method towards intelligent thermal error modeling of electric spindles66
Surface reconstruction of glass bottles using neural implicit representations for manufacturing system65
Motion stage precision prediction for photonic integrated circuit assembly60
A dynamic surface roughness prediction system based on machine learning for the 3D-printed carbon-fiber-reinforced-polymer (CFRP) turning59
Context-sensitive lexicon for imbalanced text sentiment classification using bidirectional LSTM59
Machining tool identification utilizing temporal 3D point clouds59
Remaining useful lifetime prediction for milling blades using a fused data prediction model (FDPM)50
Stability modeling for chatter avoidance in self-aware machining: an application of physics-guided machine learning50
Nash equilibrium as a tool for the Car Sequencing Problem 4.049
Intelligent hierarchical compensation method for industrial robot positioning error based on compound branch neural network automatic creation48
Fourth-party logistics network design with service time constraint under stochastic demand45
Explainable neural network for time series-based condition monitoring in sheet metal shearing45
A chip inspection system based on a multiscale subarea attention network44
Combining human guidance and structured task execution during physical human–robot collaboration44
Machining accuracy prediction and adaptive compensation method of CNC machine tool under absence of machining process sensing44
Design patterns of deep reinforcement learning models for job shop scheduling problems43
Stable pushing in narrow passage environment using a modified hybrid A* algorithm43
Analysis of the performance of LSTM-DNN models with the consideration of signal complexity in milling processes41
Machine-learning based process monitoring for automated composites manufacturing40
Real-time monitoring of molten zinc splatter using machine learning-based computer vision40
Real-time detection of blade surface defects based on the improved RT-DETR39
Enhancing robustness to novel visual defects through StyleGAN latent space navigation: a manufacturing use case39
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