OOIR: Observatory of International Research

Papers

(The H4-Index of Journal of Manufacturing Systems is 65. 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
Review of digital twin about concepts, technologies, and industrial applications	669
Industry 4.0 and Industry 5.0—Inception, conception and perception	657
Enabling technologies and tools for digital twin	572
Digital twins-based smart manufacturing system design in Industry 4.0: A review	278
Smart manufacturing process and system automation – A critical review of the standards and envisioned scenarios	253
Industry 5.0: Prospect and retrospect	218
Cyber-physical systems architectures for industrial internet of things applications in Industry 4.0: A literature review	208
A review on wire arc additive manufacturing: Monitoring, control and a framework of automated system	199
Digital twin modeling	195
Outlook on human-centric manufacturing towards Industry 5.0	177
Intelligent welding system technologies: State-of-the-art review and perspectives	172
Digital twin-based designing of the configuration, motion, control, and optimization model of a flow-type smart manufacturing system	169
Digital Twin Enhanced Dynamic Job-Shop Scheduling	152
Big data analytics for intelligent manufacturing systems: A review	145
Digital twin modeling method based on biomimicry for machining aerospace components	145
A literature survey of the robotic technologies during the COVID-19 pandemic	144
Industry 4.0 smart reconfigurable manufacturing machines	143
Unsupervised domain-share CNN for machine fault transfer diagnosis from steady speeds to time-varying speeds	143
Industry 5.0 and Society 5.0—Comparison, complementation and co-evolution	141
Artificial intelligence and internet of things in small and medium-sized enterprises: A survey	139
Automated defect inspection system for metal surfaces based on deep learning and data augmentation	134
A digital twin to train deep reinforcement learning agent for smart manufacturing plants: Environment, interfaces and intelligence	130
Digital twin-based smart assembly process design and application framework for complex products and its case study	124
Physics guided neural network for machining tool wear prediction	120
Past, present, and future barriers to digital transformation in manufacturing: A review	113

Smart augmented reality instructional system for mechanical assembly towards worker-centered intelligent manufacturing	111
Petri-net-based dynamic scheduling of flexible manufacturing system via deep reinforcement learning with graph convolutional network	109
Towards multi-model approaches to predictive maintenance: A systematic literature survey on diagnostics and prognostics	107
How to model and implement connections between physical and virtual models for digital twin application	95
Toward human-centric smart manufacturing: A human-cyber-physical systems (HCPS) perspective	94
A novel deep convolutional neural network-bootstrap integrated method for RUL prediction of rolling bearing	92
Application of sensing techniques and artificial intelligence-based methods to laser welding real-time monitoring: A critical review of recent literature	92
Toward in-situ flaw detection in laser powder bed fusion additive manufacturing through layerwise imagery and machine learning	92
Towards Self-X cognitive manufacturing network: An industrial knowledge graph-based multi-agent reinforcement learning approach	90
Systematic literature review on augmented reality in smart manufacturing: Collaboration between human and computational intelligence	90
MES-integrated digital twin frameworks	88
Digital twin and cloud-side-end collaboration for intelligent battery management system	88
State-of-the-art of selective laser melting process: A comprehensive review	87
Towards proactive human–robot collaboration: A foreseeable cognitive manufacturing paradigm	84
A digital-twin visualized architecture for Flexible Manufacturing System	81
A knowledge-based Digital Shadow for machining industry in a Digital Twin perspective	80
Additive manufacturing and the COVID-19 challenges: An in-depth study	80
Applications of virtual reality in maintenance during the industrial product lifecycle: A systematic review	79
A digital twin-enhanced system for engineering product family design and optimization	79
New Paradigm of Data-Driven Smart Customisation through Digital Twin	78
A digital twin-based big data virtual and real fusion learning reference framework supported by industrial internet towards smart manufacturing	77
Designing a closed-loop supply chain network for citrus fruits crates considering environmental and economic issues	77
Digital Twin-enabled Collaborative Data Management for Metal Additive Manufacturing Systems	77
Machine learning for metal additive manufacturing: Towards a physics-informed data-driven paradigm	76
Evaluating quality in human-robot interaction: A systematic search and classification of performance and human-centered factors, measures and metrics towards an industry 5.0	75
Data Construction Method for the Applications of Workshop Digital Twin System	75
Modeling and implementation of a digital twin of material flows based on physics simulation	75
Decentralized cloud manufacturing-as-a-service (CMaaS) platform architecture with configurable digital assets	74
A survey on decision-making based on system reliability in the context of Industry 4.0	74
Attitude data-based deep hybrid learning architecture for intelligent fault diagnosis of multi-joint industrial robots	73
Fault detection and diagnostic method of diesel engine by combining rule-based algorithm and BNs/BPNNs	73
Digital Twin-driven online anomaly detection for an automation system based on edge intelligence	71
Building a right digital twin with model engineering	70
A Digital Twin approach based on nonparametric Bayesian network for complex system health monitoring	68
Worker assistance systems in manufacturing: A review of the state of the art and future directions	67
Digital twin-driven service model and optimal allocation of manufacturing resources in shared manufacturing	67
A Review on Recent Advances in Vision-based Defect Recognition towards Industrial Intelligence	66
Automated manufacturing system discovery and digital twin generation	66
Challenges and opportunities on AR/VR technologies for manufacturing systems in the context of industry 4.0: A state of the art review	65
Deep learning-based adversarial multi-classifier optimization for cross-domain machinery fault diagnostics	65