The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
A Particle Swarm Optimization Approach for Minimizing GD&T Error in Additive Manufactured Parts: PSO Based GD&T Minimization
Abstract
This paper presents a particle swarm optimization (PSO) approach to improve the geometrical accuracy of additive manufacturing (AM) parts by minimizing geometrical dimensioning and tolerancing (GD&T) error. Four AM process parameters viz. Bed temperature, nozzle temperature, Infill, layer thickness are taken as input while circularity and flatness error in ABS part are taken as response. A mathematical model is developed for circularity and flatness error individually using regression technique in terms of process parameters as design variables. For the optimum search of the AM process parameter values, minimization of circularity and flatness are formulated as multi-objective, multi-variable optimization problem which is optimized using particle swarm optimization (PSO) algorithm and hence improving the geometrical accuracy of the ABS part.
Related Content
|
Takaomi Kobayashi.
© 2025.
32 pages.
|
|
Karla L. Tovar Carrillo, Ayano Ibaraki, Takaomi Kobayashi.
© 2025.
28 pages.
|
|
Shoji Nagaoka, Maki Horikawa, Tomohiro Shirosaki.
© 2025.
34 pages.
|
|
Huixin Jiang, Hannah Snider, Xianhui Zhao, Saurabh Prakash Pethe, Shuvodeep De, Tolga Aytug, Soydan Ozcan, Kashif Nawaz, Kai Li.
© 2025.
24 pages.
|
|
Takaomi Kobayashi.
© 2025.
36 pages.
|
|
Takaomi Kobayashi, Debbie Dominic, Nurul Alia Syufina Abu Bakar, Siti Baidurah.
© 2025.
14 pages.
|
|
Truong Thi Cam Trang, Khoa Dang Nguyen.
© 2025.
34 pages.
|
|
|