OOIR: Observatory of International Research

Papers

(The H4-Index of Journal of Manufacturing Systems is 72. 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.)

Article	Citations
Joint optimization of feature sequences and toolpath strategies in multi-feature workpiece machining for minimizing energy consumption and processing time	1570
On the feasibility of an integrated English wheel system	789
Application and trends of point cloud in intelligent welding: State of the art review	787
Digital twin based photogrammetry field-of-view evaluation and 3D layout optimisation for reconfigurable manufacturing systems	462
Collaborative optimization for multirobot manufacturing system reliability through integration of SysML simulation and maintenance knowledge graph	414
Optimal process planning for hybrid additive–subtractive manufacturing using recursive volume decomposition with decision criteria	373
Reconfigurable flexible assembly model and implementation for cross-category products	269
A multimodal hierarchical learning approach for virtual metrology in semiconductor manufacturing	249
Optimizing burn-in and predictive maintenance for enhanced reliability in manufacturing systems: A two-unit series system approach	237
Joint multi-objective dynamic scheduling of machine tools and vehicles in a workshop based on digital twin	219
Effective dispatching rules mining based on near-optimal schedules in intelligent job shop environment	203
A digital twin-based assembly model for multi-source variation fusion on vision transformer	195
Immersive and interactive cyber-physical system (I2CPS) and virtual reality interface for human involved robotic manufacturing	186
Machine learning based screw drive state detection for unfastening screw connections	182
A framework for designing a degradation-aware controller based on empirical estimation of the state–action cost and model predictive control	169
Using evolutionary artificial neural networks in monitoring binary and polytomous logistic profiles	167
Efficient ship pipeline routing with dual-strategy enhanced ant colony optimization: Active behavior adjustment and passive environmental adaptability	165
Deep reinforcement learning-based dynamic scheduling for resilient and sustainable manufacturing: A systematic review	164
Advancing human-robot collaboration: Predicting operator trajectories through AI and infrared imaging	164
State-of-the-art of selective laser melting process: A comprehensive review	158
Surface roughness prediction through GAN-synthesized power signal as a process signature	155
Data-model linkage prediction of tool remaining useful life based on deep feature fusion and Wiener process	155
Integrated Quality, Maintenance and Production model for multivariate processes: A Bayesian Approach	154
An interpretable convolutional neural network with multi-wavelet kernel fusion for intelligent fault diagnosis	148
A support-design framework for Cooperative Robots systems in labor-intensive manufacturing processes	146

Online quality inspection of resistance spot welding for automotive production lines	145
Review of manufacturing system design in the interplay of Industry 4.0 and Industry 5.0 (Part II): Design processes and enablers	144
A methodology for data-driven adjustment of variation propagation models in multistage manufacturing processes	142
Enabling predictive maintenance integrated production scheduling by operation-specific health prognostics with generative deep learning	135
Editorial Board	134
Implicit residual approximation for multi-sensor data fusion in surface geometry measurement	118
Production scheduling in Industry 4.0: Morphological analysis of the literature and future research agenda	118
Coarse-to-fine vision-based welding spot anomaly detection in production lines of body-in-white	116
SFRGNN-DA: An enhanced graph neural network with domain adaptation for feature recognition in structural parts machining	112
A contextual sensor system for non-intrusive machine status and energy monitoring	110
Rescheduling human-robot collaboration tasks under dynamic disassembly scenarios: An MLLM-KG collaboratively enabled approach	109
A new description model for enabling more general manufacturing systems representation in digital twin	107
A graph-based reinforcement learning-enabled approach for adaptive human-robot collaborative assembly operations	107
Model-based tool condition prognosis using power consumption and scarce surface roughness measurements	106
Establishing a reliable mechanism model of the digital twin machining system: An adaptive evaluation network approach	105
Flexible robotic cell scheduling with graph neural network based deep reinforcement learning	103
Integrated decision of production scheduling and condition-based maintenance planning for multi-unit systems with variable replacement thresholds	103
An online inference method for condition identification of workpieces with complex residual stress distributions	103
A skeleton-based assembly action recognition method with feature fusion for human-robot collaborative assembly	103
A general mathematic model framework for assembly process driven digital twin of assembly precision	102
Automated broad transfer learning for cross-domain fault diagnosis	100
Interpretable real-time monitoring of pipeline weld crack leakage based on wavelet multi-kernel network	99
Real-time decision-making for Digital Twin in additive manufacturing with Model Predictive Control using time-series deep neural networks	98
Tool wear identification and prediction method based on stack sparse self-coding network	95
Reinforcement and deep reinforcement learning-based solutions for machine maintenance planning, scheduling policies, and optimization	95
Detecting anomalies in time series data from a manufacturing system using recurrent neural networks	94
Challenges and opportunities on AR/VR technologies for manufacturing systems in the context of industry 4.0: A state of the art review	94
Adoption of machine learning technology for failure prediction in industrial maintenance: A systematic review	92
An Ontology-based Engineering system to support aircraft manufacturing system design	87
Heterogeneous hypergraph learning for analyzing surface defects in additive manufacturing process	84
Prognostic and health management through collaborative maintenance	81
Opportunistic maintenance optimization of continuous process manufacturing systems considering imperfect maintenance with epistemic uncertainty	81
A process strategy planning of additive-subtractive hybrid manufacturing based multi-dimensional manufacturability evaluation of geometry feature	80
Continuous-flow simulation of manufacturing systems with assembly/disassembly machines, multiple loops and general layout	79
Counterfactual-attention multi-agent reinforcement learning for joint condition-based maintenance and production scheduling	78
A verification-oriented and part-focused assembly monitoring system based on multi-layered digital twin	78
Secure sharing of big digital twin data for smart manufacturing based on blockchain	78
An intelligent monitoring system for robotic milling process based on transfer learning and digital twin	77
A novel integration framework for degradation-state prediction via transformer model with autonomous optimizing mechanism	77
Paired ensemble and group knowledge measurement for health evaluation of wind turbine gearbox under compound fault scenarios	77
An efficient critical path based method for permutation flow shop scheduling problem	77
Industrial big data-driven mechanical performance prediction for hot-rolling steel using lower upper bound estimation method	75
Towards the industry 5.0 frontier: Review and prospect of XR in product assembly	74
Enhancing metal additive manufacturing training with the advanced vision language model: A pathway to immersive augmented reality training for non-experts	74
Development of robotic bin picking platform with cluttered objects using human guidance and convolutional neural network (CNN)	73
Vibration energy-based indicators for multi-target condition monitoring in milling operations	73
Federated learning-based semantic segmentation for pixel-wise defect detection in additive manufacturing	72