When AI meets additive manufacturing: Challenges and emerging opportunities for human-centered products development
Nowadays, additive manufacturing (AM) has been increasingly leveraged to produce human-
centered products, such as orthoses and prostheses as well as therapeutic helmets, finger …
centered products, such as orthoses and prostheses as well as therapeutic helmets, finger …
Monitoring on a shoestring: Low cost solutions for digital manufacturing
Digital transformation can provide a competitive edge for many manufacturers, however
many smaller companies may not have the capabilities needed to embrace this opportunity …
many smaller companies may not have the capabilities needed to embrace this opportunity …
A survey on vertical federated learning: From a layered perspective
Vertical federated learning (VFL) is a promising category of federated learning for the
scenario where data is vertically partitioned and distributed among parties. VFL enriches the …
scenario where data is vertically partitioned and distributed among parties. VFL enriches the …
Compound knowledge graph-enabled AI assistant for accelerated materials discovery
Materials scientists are facing increasingly challenging multi-objective performance
requirements to meet the needs of modern systems such as lighter-weight and more fuel …
requirements to meet the needs of modern systems such as lighter-weight and more fuel …
A systematic overview of data federation systems
Data federation addresses the problem of uniformly accessing multiple, possibly
heterogeneous data sources, by mapping them into a unified schema, such as an RDF …
heterogeneous data sources, by mapping them into a unified schema, such as an RDF …
A synergic approach of deep learning towards digital additive manufacturing: A review
Deep learning and additive manufacturing have progressed together in the previous couple
of decades. Despite being one of the most promising technologies, they have several flaws …
of decades. Despite being one of the most promising technologies, they have several flaws …
[HTML][HTML] Federated learning enables privacy-preserving and data-efficient dimension prediction and part qualification across additive manufacturing factories
A crucial part of quality control in additive manufacturing (AM) is the decision to accept or
reject parts based on their dimensional accuracy. Machine learning (ML) models can learn …
reject parts based on their dimensional accuracy. Machine learning (ML) models can learn …
A Systematic Review of Additive Manufacturing Solutions Using Machine Learning, Internet of Things, Big Data, Digital Twins and Blockchain Technologies: A …
New manufacturing expertise, along with user expectations for gradually modified products
and facilities, is creating changes in manufacturing scale and distribution. Standardization is …
and facilities, is creating changes in manufacturing scale and distribution. Standardization is …
Illustrating an Effective Workflow for Accelerated Materials Discovery
M Mulukutla, AN Person, S Voigt, L Kuettner… - Integrating Materials and …, 2024 - Springer
Algorithmic materials discovery is a multidisciplinary domain that integrates insights from
specialists in alloy design, synthesis, characterization, experimental methodologies …
specialists in alloy design, synthesis, characterization, experimental methodologies …
An approach for data pipeline with distributed query engine for industrial applications
AG Chowdhury, M Illian, L Wisniewski… - 2020 25th IEEE …, 2020 - ieeexplore.ieee.org
The data driven services in industrial automation systems are transforming the world of
automation industry by optimizing industrial processes and providing Value Added Services …
automation industry by optimizing industrial processes and providing Value Added Services …