Machine Learning for industrial applications: A comprehensive literature review
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 …
Data-driven aerospace engineering: reframing the industry with machine learning
Data science, and machine learning in particular, is rapidly transforming the scientific and
industrial landscapes. The aerospace industry is poised to capitalize on big data and …
industrial landscapes. The aerospace industry is poised to capitalize on big data and …
A physics-informed machine learning approach for solving heat transfer equation in advanced manufacturing and engineering applications
N Zobeiry, KD Humfeld - Engineering Applications of Artificial Intelligence, 2021 - Elsevier
A physics-informed neural network is developed to solve conductive heat transfer partial
differential equation (PDE), along with convective heat transfer PDEs as boundary …
differential equation (PDE), along with convective heat transfer PDEs as boundary …
[HTML][HTML] Machine learning and mixed reality for smart aviation: Applications and challenges
Y Jiang, TH Tran, L Williams - Journal of Air Transport Management, 2023 - Elsevier
The aviation industry is a dynamic and ever-evolving sector. As technology advances and
becomes more sophisticated, the aviation industry must keep up with the changing trends …
becomes more sophisticated, the aviation industry must keep up with the changing trends …
Machine learning assisted characterisation and simulation of compressive damage in composite laminates
A data-rich framework is presented to consistently characterise the macroscopic strain-
softening response of laminated composites subjected to compressive loading. First, a …
softening response of laminated composites subjected to compressive loading. First, a …
[PDF][PDF] 数字孪生驱动的装配工艺设计现状及关键实现技术研究
郭飞燕， 刘检华， 邹方， 翟雨农， 王仲奇， 李少卓 - 机械工程学报, 2019 - researchgate.net
基于制造过程中的全数字量协调传递方式, 通过“虚实融合, 以虚控实” 的手段,
对数字孪生模型驱动的航空产品装配工艺优化-反馈-改进环机制进行了研究 …
对数字孪生模型驱动的航空产品装配工艺优化-反馈-改进环机制进行了研究 …
Development of aviation industry-oriented methodology for failure predictions of brittle bonded joints using probabilistic machine learning
The bonding assembly concept of cured aerospace composite parts is considered an
efficient approach from almost every perspective. It simplifies the design and provides great …
efficient approach from almost every perspective. It simplifies the design and provides great …
Implementation of a probabilistic machine learning strategy for failure predictions of adhesively bonded joints using cohesive zone modeling
Adhesive bonding as an assembly procedure in aviation products is very efficient from both
weight and recurring cost points of view. However, even with strict inspections, process …
weight and recurring cost points of view. However, even with strict inspections, process …
Readiness levels of Industry 4.0 technologies applied to aircraft manufacturing—a review, challenges and trends
GC Zutin, GF Barbosa, PC de Barros… - … International Journal of …, 2022 - Springer
The present paper provides an overview of the state-of-the-art research, outlining the
applications of the Industry 4.0 (I4. 0) technologies on the aircraft manufacturing sector and …
applications of the Industry 4.0 (I4. 0) technologies on the aircraft manufacturing sector and …
A review and framework for modeling methodologies to advance automated fiber placement
Accurate and reliable modeling techniques are required to properly understand and predict
manufacturing processes and the quality of the final product. The Automated Fiber …
manufacturing processes and the quality of the final product. The Automated Fiber …