OOIR: Observatory of International Research

Papers

(The H4-Index of Journal of Intelligent Manufacturing is 37. 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 2020-03-01 to 2024-03-01.)

Article	Citations
Bearing fault diagnosis base on multi-scale CNN and LSTM model	219
RETRACTED ARTICLE: Visual sensor intelligent module based image transmission in industrial manufacturing for monitoring and manipulation problems	175
Prediction of laser cutting parameters for polymethylmethacrylate sheets using random vector functional link network integrated with equilibrium optimizer	108
A case study of conditional deep convolutional generative adversarial networks in machine fault diagnosis	103
Remaining useful life estimation via transformer encoder enhanced by a gated convolutional unit	97
Modelling and prediction of surface roughness in wire arc additive manufacturing using machine learning	81
Artificial intelligence systems for tool condition monitoring in machining: analysis and critical review	81
Synthetic data augmentation for surface defect detection and classification using deep learning	80
Machine learning integrated design for additive manufacturing	78
Multiple time-series convolutional neural network for fault detection and diagnosis and empirical study in semiconductor manufacturing	74
Field-synchronized Digital Twin framework for production scheduling with uncertainty	73
Designing an adaptive production control system using reinforcement learning	71
A steel surface defect inspection approach towards smart industrial monitoring	70
Machine learning and deep learning based predictive quality in manufacturing: a systematic review	69
Quality 4.0: a review of big data challenges in manufacturing	62
Estimation of tool wear and optimization of cutting parameters based on novel ANFIS-PSO method toward intelligent machining	61
Designing and developing smart production planning and control systems in the industry 4.0 era: a methodology and case study	59
A review of motion planning algorithms for intelligent robots	58
Digitalization priorities of quality control processes for SMEs: a conceptual study in perspective of Industry 4.0 adoption	56
Prediction of geometry deviations in additive manufactured parts: comparison of linear regression with machine learning algorithms	56
Machine-learning for automatic prediction of flatness deviation considering the wear of the face mill teeth	53
Tool wear condition monitoring based on a two-layer angle kernel extreme learning machine using sound sensor for milling process	49
Automated surface defect detection framework using machine vision and convolutional neural networks	48
Multitask learning for health condition identification and remaining useful life prediction: deep convolutional neural network approach	47
Human-centred design in industry 4.0: case study review and opportunities for future research	46

Applications of artificial intelligence in engineering and manufacturing: a systematic review	46
Milling force prediction model based on transfer learning and neural network	43
Module-based product family design: systematic literature review and meta-synthesis	43
A novel transfer learning fault diagnosis method based on Manifold Embedded Distribution Alignment with a little labeled data	43
An adaptive fault detection and root-cause analysis scheme for complex industrial processes using moving window KPCA and information geometric causal inference	42
Weld defect classification in radiographic images using unified deep neural network with multi-level features	42
A digital twin emulator of a modular production system using a data-driven hybrid modeling and simulation approach	41
Machine learning with domain knowledge for predictive quality monitoring in resistance spot welding	41
Control of deposition height in WAAM using visual inspection of previous and current layers	40
Machine learning techniques in additive manufacturing: a state of the art review on design, processes and production control	39
On-line prediction of ultrasonic elliptical vibration cutting surface roughness of tungsten heavy alloy based on deep learning	38
From knowledge-based to big data analytic model: a novel IoT and machine learning based decision support system for predictive maintenance in Industry 4.0	38
Improving the accuracy of machine-learning models with data from machine test repetitions	37