Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/76745
PIRA download icon_1.1View/Download Full Text
Title: Accelerating 3d printing process using an extended ant colony optimization algorithm
Authors: Fok, KY 
Cheng, CT 
Ganganath, N
Iu, HHC
Tse, CK 
Issue Date: 2018
Source: 2018 International Symposium on Circuits and Systems (ISCAS), Florence, Italy, 27-30 May 2018, p. 1-5
Abstract: Ant colony optimization (ACO) algorithms have been widely adopted in solving combinatorial problems, like the traveling salesman problem (TSP). Nevertheless, with a proper transformation to TSP, ACO is capable of solving undirected rural postman problems (URPP) as well. In fact, nozzle path planning problems in 3D printing can be represented as URPP. Therefore, in this work, ACO is utilized as a URPP solver to accelerate the printing process in fused deposition modeling applications. Furthermore, mechanisms which exploit unique properties in 3D models are proposed to further extend the ACO in the above optimization process. These mechanisms are capable of accelerating ACO by adaptively adjusting its number of iterations on-the-fly. Simulation results using real-life 3D models show that the proposed extensions can accelerate ACO without affecting the quality of its solutions significantly.
Keywords: Ant colony optimization
Additive manufacturing
3D printing
Undirected rural postman proble
Publisher: Institute of Electrical and Electronics Engineers
ISBN: 978-1-5386-4881-0 (electronic)
978-1-5386-4882-7 (print on demand(PoD))
EISSN: 2379-447X
DOI: 10.1109/ISCAS.2018.8351113
Rights: © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
The following publication Fok, K. Y., Cheng, C. T., Ganganath, N., Iu, H. H. C., & Chi, K. T. (2018, May). Accelerating 3D Printing Process Using an Extended Ant Colony Optimization Algorithm. In 2018 IEEE International Symposium on Circuits and Systems (ISCAS) (pp. 1-5). IEEE is available at https://dx.doi.org/10.1109/ISCAS.2018.8351113
Appears in Collections:Conference Paper

Files in This Item:
File Description SizeFormat 
Fok_Accelerating_3D_Printing.pdfPre-Published version1.36 MBAdobe PDFView/Open
Open Access Information
Status open access
File Version Final Accepted Manuscript
Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page views

140
Citations as of Jul 3, 2022

Downloads

207
Citations as of Jul 3, 2022

SCOPUSTM   
Citations

5
Citations as of Jul 7, 2022

WEB OF SCIENCETM
Citations

1
Last Week
0
Last month
Citations as of Jul 7, 2022

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.