| nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
| 1 |
A data-driven time-sequence feature-based composite network of time-distributed CNN-LSTM for detecting pore defects in laser penetration welding
|
Yan, Shenghong
|
|
|
36 |
5 |
p. 3509-3526
|
artikel
|
| 2 |
A Generative AI approach to improve in-situ vision tool wear monitoring with scarce data
|
Garcia-Perez, Alberto
|
|
|
36 |
5 |
p. 3165-3183
|
artikel
|
| 3 |
A multimodal fusion method for soldering quality online inspection
|
Xie, Jian
|
|
|
36 |
5 |
p. 3271-3284
|
artikel
|
| 4 |
An assembly process planning pipeline for industrial electronic equipment based on knowledge graph with bidirectional extracted knowledge from historical process documents
|
Xiao, Youzi
|
|
|
36 |
5 |
p. 3647-3667
|
artikel
|
| 5 |
An automatic inspection system for the detection of tire surface defects and their severity classification through a two-stage multimodal deep learning approach
|
Mignot, Thomas
|
|
|
36 |
5 |
p. 3427-3445
|
artikel
|
| 6 |
A novel method based on deep learning algorithms for material deformation rate detection
|
Özdem, Selim
|
|
|
36 |
5 |
p. 3249-3270
|
artikel
|
| 7 |
A reference framework for the digital twin smart factory based on cloud-fog-edge computing collaboration
|
Li, Zhiyuan
|
|
|
36 |
5 |
p. 3625-3645
|
artikel
|
| 8 |
Continual learning for surface defect segmentation by subnetwork creation and selection
|
Dekhovich, Aleksandr
|
|
|
36 |
5 |
p. 3051-3065
|
artikel
|
| 9 |
Correction: Detecting and classifying hidden defects in additively manufactured parts using deep learning and X-ray computed tomography
|
Bimrose, Miles V.
|
|
|
36 |
5 |
p. 3481
|
artikel
|
| 10 |
Defining a feature-level digital twin process model by extracting machining features from MBD models for intelligent process planning
|
Li, Jingjing
|
|
|
36 |
5 |
p. 3227-3248
|
artikel
|
| 11 |
Detecting and classifying hidden defects in additively manufactured parts using deep learning and X-ray computed tomography
|
Bimrose, Miles V.
|
|
|
36 |
5 |
p. 3465-3479
|
artikel
|
| 12 |
Development of a cascaded multitask physics-informed neural network (CM-PINN) to construct the muti-physical field model of rubber bushing press fitting
|
Chen, Yiru
|
|
|
36 |
5 |
p. 3607-3624
|
artikel
|
| 13 |
Digital twin and predictive quality solution for insulated glass line
|
Aydin, Gülcan
|
|
|
36 |
5 |
p. 3543-3567
|
artikel
|
| 14 |
Enhancing robustness to novel visual defects through StyleGAN latent space navigation: a manufacturing use case
|
Theodoropoulos, Spyros
|
|
|
36 |
5 |
p. 3527-3541
|
artikel
|
| 15 |
Explainable artificial intelligence and multi-stage transfer learning for injection molding quality prediction
|
Lin, Chung-Yin
|
|
|
36 |
5 |
p. 3587-3606
|
artikel
|
| 16 |
Flexible and robust detection for assembly automation with YOLOv5: a case study on HMLV manufacturing line
|
Simeth, Alexej
|
|
|
36 |
5 |
p. 3447-3463
|
artikel
|
| 17 |
Global receptive field graph attention network for unsupervised domain adaptation fault diagnosis in variable operating conditions
|
Cai, Meiling
|
|
|
36 |
5 |
p. 3285-3312
|
artikel
|
| 18 |
Leveraging computer vision towards high-efficiency autonomous industrial facilities
|
Yousif, Ibrahim
|
|
|
36 |
5 |
p. 2983-3008
|
artikel
|
| 19 |
Lightweight convolutional neural network for fast visual perception of storage location status in stereo warehouse
|
Zhang, Liangrui
|
|
|
36 |
5 |
p. 3143-3163
|
artikel
|
| 20 |
Modeling supply chain resilience drivers in the context of COVID-19 in manufacturing industries: leveraging the advantages of approximate fuzzy DEMATEL
|
Sarker, Md. Rayhan
|
|
|
36 |
5 |
p. 2939-2958
|
artikel
|
| 21 |
MSOA: A modular service-oriented architecture to integrate mobile manipulators as cyber-physical systems
|
Ghodsian, Nooshin
|
|
|
36 |
5 |
p. 3207-3226
|
artikel
|
| 22 |
Multi-agent cooperative swarm learning for dynamic layout optimisation of reconfigurable robotic assembly cells based on digital twin
|
Wang, Likun
|
|
|
36 |
5 |
p. 2959-2982
|
artikel
|
| 23 |
Multi-modal background-aware for defect semantic segmentation with limited data
|
Shan, Dexing
|
|
|
36 |
5 |
p. 3313-3325
|
artikel
|
| 24 |
Quantile regression-enriched event modeling framework for dropout analysis in high-temperature superconductor manufacturing
|
Li, Mai
|
|
|
36 |
5 |
p. 3009-3030
|
artikel
|
| 25 |
Real-time monitoring of molten zinc splatter using machine learning-based computer vision
|
O’Donovan, Callum
|
|
|
36 |
5 |
p. 3399-3425
|
artikel
|
| 26 |
Remaining useful life prediction based on parallel multi-scale feature fusion network
|
Yin, Yuyan
|
|
|
36 |
5 |
p. 3111-3127
|
artikel
|
| 27 |
Robust image-based cross-sectional grain boundary detection and characterization using machine learning
|
Satterlee, Nicholas
|
|
|
36 |
5 |
p. 3067-3095
|
artikel
|
| 28 |
Selecting subsets of source data for transfer learning with applications in metal additive manufacturing
|
Tang, Yifan
|
|
|
36 |
5 |
p. 3185-3206
|
artikel
|
| 29 |
Sparse deep encoded features with enhanced sinogramic red deer optimization for fault inspection in wafer maps
|
Altantawy, Doaa A.
|
|
|
36 |
5 |
p. 3359-3397
|
artikel
|
| 30 |
Three-dimensional fabric smoothness evaluation using point cloud data for enhanced quality control
|
Yuan, Zhijie
|
|
|
36 |
5 |
p. 3327-3343
|
artikel
|
| 31 |
Towards autonomous learning and optimisation in textile production: data-driven simulation approach for optimiser validation
|
Kins, Ruben
|
|
|
36 |
5 |
p. 3483-3508
|
artikel
|
| 32 |
Unknown-class recognition adversarial network for open set domain adaptation fault diagnosis of rotating machinery
|
Wu, Ke
|
|
|
36 |
5 |
p. 3031-3049
|
artikel
|
| 33 |
Use of machine learning models in condition monitoring of abrasive belt in robotic arm grinding process
|
Surindra, Mochamad Denny
|
|
|
36 |
5 |
p. 3345-3358
|
artikel
|
| 34 |
Variability-enhanced knowledge-based engineering (VEN) for reconfigurable molds
|
Qaiser, Zeeshan
|
|
|
36 |
5 |
p. 3097-3109
|
artikel
|
| 35 |
Warpage detection in 3D printing of polymer parts: a deep learning approach
|
Bhandarkar, Vivek V.
|
|
|
36 |
5 |
p. 3129-3141
|
artikel
|
| 36 |
Workplace performance measurement: digitalization of work observation and analysis
|
Nesterak, Janusz
|
|
|
36 |
5 |
p. 3569-3585
|
artikel
|
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