Intelligent additive manufacturing and design: state of the art and future perspectives

Y Xiong, Y Tang, Q Zhou, Y Ma, DW Rosen - Additive Manufacturing, 2022 - Elsevier
In additive manufacturing (AM), intelligent technologies are proving to be a powerful tool for
facilitating economic, efficient, and effective decision-making within the product and service …

Smart additive manufacturing: Current artificial intelligence-enabled methods and future perspectives

YB Wang, P Zheng, T Peng, HY Yang, J Zou - Science China …, 2020 - Springer
Additive manufacturing (AM) has been increasingly used in production. Because of its rapid
growth, the efficiency and robustness of AM-based product development processes should …

Machine learning integrated design for additive manufacturing

J Jiang, Y Xiong, Z Zhang, DW Rosen - Journal of Intelligent …, 2022 - Springer
For improving manufacturing efficiency and minimizing costs, design for additive
manufacturing (AM) has been accordingly proposed. The existing design for AM methods …

Machine learning and knowledge graph based design rule construction for additive manufacturing

H Ko, P Witherell, Y Lu, S Kim, DW Rosen - Additive Manufacturing, 2021 - Elsevier
Additive Manufacturing (AM) is becoming data-intensive while increasingly generating
newly available data. The availability of AM data provides Design for AM (DfAM) with a …

Human-machine collaborative additive manufacturing

Y Xiong, Y Tang, S Kim, DW Rosen - Journal of Manufacturing Systems, 2023 - Elsevier
Recent advances in additive manufacturing have transformed the technology from a rapid
prototyping tool into a viable production option. Within such transition, the relationships …

Spare part segmentation for additive manufacturing–A framework

S Ghuge, V Dohale, M Akarte - Computers & Industrial Engineering, 2022 - Elsevier
Organizations strive to find new ways to manage the production of strategic spare parts with
unanticipated demand and high delivery time. Additive Manufacturing (AM) is a …

Investigation of deep learning for real-time melt pool classification in additive manufacturing

Z Yang, Y Lu, H Yeung… - 2019 IEEE 15th …, 2019 - ieeexplore.ieee.org
Consistent melt pool geometry is an indicator of a stable laser powder bed fusion (L-PBF)
additive manufacturing process. Melt pool size and shape reflect the impact of process …

[HTML][HTML] Implications of lattice structures on economics and productivity of metal powder bed fusion

I Flores, N Kretzschmar, AH Azman, S Chekurov… - Additive …, 2020 - Elsevier
The cost-effectiveness of metal powder bed fusion (PBF) systems in high-throughput
production are dominated by the high cost of metallic powder materials. Metal PBF …

Design for additive manufacturing: A comprehensive review of the tendencies and limitations of methodologies

LL Lopez Taborda, H Maury, J Pacheco - Rapid Prototyping Journal, 2021 - emerald.com
Purpose There are many investigations in design methodologies, but there are also
divergences and convergences as there are so many points of view. This study aims to …

Design and manufacturing implications of additive manufacturing

D Rosen, S Kim - 2021 - Springer
This article introduces the design and manufacturing implications of additive manufacturing
(AM) on part characteristics as well as on design opportunities and on manufacturing …