Data-driven order correlation pattern and storage location assignment in robotic mobile fulfillment and process automation system

KL Keung, CKM Lee, P Ji - Advanced Engineering Informatics, 2021 - Elsevier
With the rapid development and implementation of ICT, academics and industrial
practitioners are widely applying robotic process automation (RPA) to enhance their …

Investigation and Empirical Analysis of Transfer Learning for Industrial IoT Networks

P Yadav, V Rishiwal, M Yadav, A Alotaibi… - IEEE …, 2024 - ieeexplore.ieee.org
The Industrial Internet of Things Networks (IIoT-N) have revolutionized industrial systems by
connecting sensors, devices, and data analytics, creating complex, data-driven …

[HTML][HTML] Dataset for Weld Seam Analysis and Discontinuity Prediction in Laser Beam Welding Scenarios

D Walther, L Schmidt, K Schricker, C Junger… - Data in Brief, 2025 - Elsevier
Laser beam welding can produce narrow, high-quality welds in various industrial joining
processes. The thermal expansion and contraction of the metal during the weld results in the …

Federated learning for privacy-preserving collaboration in smart manufacturing

J Zhang, C Cooper, RX Gao - Global Conference on Sustainable …, 2022 - Springer
Manufacturers today are increasingly connected as part of a smart and connected
community. This transformation offers great potential to deepen their collaborations through …

Defect Recognition on Single Layer Bare Printed Circuit Boards for Quality Control and Visual Inspection: A Low-Sample-Size Deep Transfer Learning Approach

YD Austria, AC Fajardo - 2023 9th International Conference on …, 2023 - ieeexplore.ieee.org
Defect detection is a critical component in ensuring the highest quality of printed circuit
board manufacture. The work investigates the application of transfer learning to identify …

Designing computational intelligence and data-driven cyber-physical approach for robotic mobile fulfillment system

KL Keung - 2023 - theses.lib.polyu.edu.hk
With the rapid development and implementation of ICT, academics and industrial
practitioners are widely applying robotic solutions to enhance their business processes and …

Seawater Temperature Profile Reconstruction Based on Transfer Learning

Z Wang, Q Li, J Zhu, Q Li, Z Juan… - 2023 6th International …, 2023 - ieeexplore.ieee.org
Seawater temperature plays a key role in ocean thermal structure, water mass division, and
acoustic field distribution. To address the problem of constructing full-depth temperature …

Machine Learning-Driven Demand Prediction to Minimise Supply Chain Costs

SS Ahmed - 2023 - search.proquest.com
The application of artificial intelligence (AI), machine learning (ML), and data science
technologies has gained significant traction in recent years, particularly within the supply …

A Multi-Source Multi-Layer-Based Transfer Learning Approach for Forecasting Customer Demands of Newly Launched Products

A Supriyo Shafkat, RK Chakrabortty, DL Essam… - Ripon K. and Essam … - papers.ssrn.com
Forecasting the future demand for newly launched products has been challenging for supply
chain practitioners, often due to the lack of data. However, market surveys and extracting …

Augmented Transfer CNN For Fault Diagnosis Of Roller Bearing Under Frequent Working Condition Variation

W Qian, J Lu - 2021 Global Reliability and Prognostics and …, 2021 - ieeexplore.ieee.org
Intelligent fault diagnosis (IFD) has been widely investigated and achieved massive
successes in past years. Particularly, Transfer learning (TL)-based IFD has been a hot topic …