Computers in Industry

(The TQCC of Computers in Industry is 59. The table below lists those papers that are above that threshold based on CrossRef citation counts. The publications cover those that have been published in the past four years, i.e., from 2019-03-01 to 2023-03-01.)
Blockchain technology in agri-food value chain management: A synthesis of applications, challenges and future research directions284
Review of digital twin applications in manufacturing281
Generative adversarial networks for data augmentation in machine fault diagnosis224
A novel convolutional neural network based fault recognition method via image fusion of multi-vibration-signals199
Assessing Industry 4.0 readiness in manufacturing: Evidence for the European Union192
Building a digital twin for additive manufacturing through the exploitation of blockchain: A case analysis of the aircraft industry182
Bearing performance degradation assessment using long short-term memory recurrent network179
Intelligent fault diagnosis of rotating machinery based on one-dimensional convolutional neural network153
RETRACTED: An integrated neutrosophic ANP and VIKOR method for achieving sustainable supplier selection: A case study in importing field143
Sensing, smart and sustainable technologies for Agri-Food 4.0133
Intelligent fault diagnosis method of planetary gearboxes based on convolution neural network and discrete wavelet transform127
Deep neural networks with transfer learning in millet crop images125
Big data for agri-food 4.0: Application to sustainability management for by-products supply chain120
Oil and Gas 4.0 era: A systematic review and outlook117
Industry 4.0: Emerging themes and future research avenues using a text mining approach115
A multimodal and hybrid deep neural network model for Remaining Useful Life estimation114
Deep convolutional neural network based planet bearing fault classification111
Combining translation-invariant wavelet frames and convolutional neural network for intelligent tool wear state identification109
Deep heterogeneous GRU model for predictive analytics in smart manufacturing: Application to tool wear prediction104
Automated bearing fault diagnosis scheme using 2D representation of wavelet packet transform and deep convolutional neural network103
The degree of readiness for the implementation of Industry 4.094
Compound Fault Diagnosis of Gearboxes via Multi-label Convolutional Neural Network and Wavelet Transform90
Understanding CRM adoption stages: empirical analysis building on the TOE framework89
Digital transformation of manufacturing through cloud services and resource virtualization89
Ensemble deep learning-based fault diagnosis of rotor bearing systems80
Classification of cyber-physical production systems applications: Proposition of an analysis framework75
RETRACTED: Evaluation of the green supply chain management practices: A novel neutrosophic approach74
An end-to-end Internet of Things solution for Reverse Supply Chain Management in Industry 4.073
A comparison of fog and cloud computing cyber-physical interfaces for Industry 4.0 real-time embedded machine learning engineering applications71
Design and development of BIM models to support operations and maintenance69
A novel deep stacking least squares support vector machine for rolling bearing fault diagnosis67
A data-driven simulation to support remanufacturing operations66
Deep learning-based tensile strength prediction in fused deposition modeling65
Industrial robot control and operator training using virtual reality interfaces65
Ontology for safety risk identification in metro construction64
Smart technologies and corporate sustainability: The mediation effect of corporate sustainability strategy62
An enhanced convolutional neural network with enlarged receptive fields for fault diagnosis of planetary gearboxes59