[HTML][HTML] Big data, machine learning, and digital twin assisted additive manufacturing: A review

L **, X Zhai, K Wang, K Zhang, D Wu, A Nazir, J Jiang… - Materials & Design, 2024 - Elsevier
Additive manufacturing (AM) has undergone significant development over the past decades,
resulting in vast amounts of data that carry valuable information. Numerous research studies …

Applying machine learning to wire arc additive manufacturing: a systematic data-driven literature review

A Hamrani, A Agarwal, A Allouhi… - Journal of Intelligent …, 2024 - Springer
Due to its unique benefits over standard conventional “subtractive” manufacturing, additive
manufacturing is attracting growing interest in academic and industrial sectors. Here, special …

[HTML][HTML] Integration of renewable energy and sustainable development with strategic planning in the mining industry

M Pouresmaieli, M Ataei, AN Qarahasanlou… - Results in …, 2023 - Elsevier
With an increase in the world population, the global demand for minerals is rising,
increasing energy consumption. Due to the distance of mines from urban areas, the energy …

Contrastive learning-based semantic segmentation for In-situ stratified defect detection in additive manufacturing

K Wang - Journal of Manufacturing Systems, 2023 - Elsevier
Supervised semantic segmentation has been widely utilized for the quality assurance of the
additive manufacturing process. However, abnormal states (those with defects) happen …

Energy consumption intelligent modeling and prediction for additive manufacturing via multisource fusion and inter-layer consistency

K Wang, L Yu, J Xu, S Zhang, J Qin - Computers & Industrial Engineering, 2022 - Elsevier
A novel deep network termed 3DPECP-Net is proposed to address an important, interesting,
yet challenging problem in intelligent manufacturing: Accurately predicting energy …

Towards low-budget energy efficiency design in additive manufacturing based on variational scale-aware transformer

K Wang, J Xu, S Zhang, J Tan, J Qin - Journal of Cleaner Production, 2023 - Elsevier
In opposite to subtractive manufacturing methodologies, additive manufacturing (AM)
embraces plenty of sustainable advantages to decrease energy consumption and material …

Energy efficiency design for eco-friendly additive manufacturing based on multimodal attention fusion

K Wang, Y Song, H Sheng, J Xu, S Zhang… - Journal of Manufacturing …, 2022 - Elsevier
Additive manufacturing (AM) holds an imponderable scope to reduce energy consumption
(EC) and material waste in contrast to subtractive manufacturing methodologies. With the …

Deep pattern matching for energy consumption prediction of complex structures in ecological additive manufacturing

K Wang, Y Zhang, Y Song, J Xu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
We propose a novel and effective deep learning method, called deep pattern matching, for
predicting the energy consumption of complex structures, which helps designers to develop …

Multi-Modal CNN Features Fusion for Emotion Recognition: A Modified Xception Model

HM Shahzad, SM Bhatti, A Jaffar, M Rashid… - IEEE …, 2023 - ieeexplore.ieee.org
Facial expression recognition (FER) is advancing human-computer interaction, especially,
today, where facial masks are commonly worn due to the COVID-19 pandemic. Traditional …

Economically evaluating energy efficiency performance in fused filament fabrication using a multi-scale hierarchical transformer

K Wang, J Xu, S Zhang, J Tan - The International Journal of Advanced …, 2023 - Springer
In recent years, fused filament fabrication (FFF) has become the most popular additive
manufacturing (AM) process due to its low cost and relative simplicity, which incorporates a …