[HTML][HTML] Research and application of machine learning for additive manufacturing
Additive manufacturing (AM) is poised to bring a revolution due to its unique production
paradigm. It offers the prospect of mass customization, flexible production, on-demand and …
paradigm. It offers the prospect of mass customization, flexible production, on-demand and …
Machine learning and deep learning based predictive quality in manufacturing: a systematic review
With the ongoing digitization of the manufacturing industry and the ability to bring together
data from manufacturing processes and quality measurements, there is enormous potential …
data from manufacturing processes and quality measurements, there is enormous potential …
Machine Learning for industrial applications: A comprehensive literature review
M Bertolini, D Mezzogori, M Neroni… - Expert Systems with …, 2021 - Elsevier
Abstract Machine Learning (ML) is a branch of artificial intelligence that studies algorithms
able to learn autonomously, directly from the input data. Over the last decade, ML …
able to learn autonomously, directly from the input data. Over the last decade, ML …
Metallurgy, mechanistic models and machine learning in metal printing
Additive manufacturing enables the printing of metallic parts, such as customized implants
for patients, durable single-crystal parts for use in harsh environments, and the printing of …
for patients, durable single-crystal parts for use in harsh environments, and the printing of …
[HTML][HTML] Big data, machine learning, and digital twin assisted additive manufacturing: A review
Additive manufacturing (AM) has undergone significant development over the past decades,
resulting in vast amounts of data that carry valuable information. Numerous research studies …
resulting in vast amounts of data that carry valuable information. Numerous research studies …
Machine learning for metal additive manufacturing: Towards a physics-informed data-driven paradigm
Abstract Machine learning (ML) has shown to be an effective alternative to physical models
for quality prediction and process optimization of metal additive manufacturing (AM) …
for quality prediction and process optimization of metal additive manufacturing (AM) …
Machine learning in additive manufacturing: a review
In this review article, the latest applications of machine learning (ML) in the additive
manufacturing (AM) field are reviewed. These applications, such as parameter optimization …
manufacturing (AM) field are reviewed. These applications, such as parameter optimization …
Dynamic prediction of jet grouted column diameter in soft soil using Bi-LSTM deep learning
The bidirectional long short-term memory (Bi-LSTM) network is an innovative computation
paradigm that learns bidirectional long-term dependencies between time steps and …
paradigm that learns bidirectional long-term dependencies between time steps and …
Big data analytics for smart factories of the future
Continued advancement of sensors has led to an ever-increasing amount of data of various
physical nature to be acquired from production lines. As rich information relevant to the …
physical nature to be acquired from production lines. As rich information relevant to the …
A spatial-temporal layer-wise relevance propagation method for improving interpretability and prediction accuracy of LSTM building energy prediction
G Li, F Li, C Xu, X Fang - Energy and Buildings, 2022 - Elsevier
At present, data-driven methods have achieved satisfactory results in building energy
consumption prediction, especially deep learning models such as long short-term memory …
consumption prediction, especially deep learning models such as long short-term memory …