Zhanli Li
ABSTRACT
The print 1orientation of the model of 3D printing determines the direction of additive manufacturing process and has a direct influence on the model accuracy and printing efficiency. Based on this problem, this article taken volumes error caused by stair-step-effect, the number of suspension added, the print time of model as optimal objectives and establish an optimization model of which the solution algorithm is designed by using both genetic algorithm and simulated annealing algorithm. After much testing, this designed algorithm has been proved significantly efficient in obtaining optimal solutions and is able to be applied to 3D printing system. The method introduced in this article is more superior in comparison with traditional method.
- S. H. Masood, W. Rattanawong, and P. lovenitti. 2000. Part Build Orientations Based on Volumetric Error in Fused Deposition Modelling. International Journal of Advanced Manufacturing Technology, London, 16, 162--168, February.Google Scholar
- J. Hong, D. L. Wu, D. C. Li, and B. H. Lu. Multi-Objective Optimization of the Part Building Orientation in Stereolithography. Journal of Xian Jiao tong University, Xi'an, vol. 33, no. 5, pp. 506--509, May 2001.Google Scholar
- W. G. Zhang, and Z. L. Li. Multi-objective optimization model for fabrication orientation. Journal of Chang'an University (Natural Science Edition), Xi'an, vol. 23, no. 5, pp. 104--106, September 2003.Google Scholar
- Z. H. Zhang, A. J. Li, J. Y. Yang, G. D. Hao, and H. Wang. Optimization Method to Fabrication Orientation of Parts in Rapid Prototyping Based on Genetic Algorithm. Journal of Donghua University (Natural Science), Shanghai, vol. 36, no. 4, pp. 376--380, August 2010.Google Scholar
- T. Dong, W. Y. Zhang, and C. H. Wang. New Optimizing Procedures of Part-building Orientation for Rapid Prototyping Manufacturing. Computer Engineering and Applications. Beijing, vol. 39, no. 1, pp. 45--48, January 2003.Google Scholar
- J. B. Zhao, L. Y. He, W. J. Liu, and H. Y. Bian. Optimization of Part-Building Orientation for Rapid Prototyping Manufacturing. Journal of Computer-aided Design & Computer Graphics, Beijing, vol. 18, no. 3, pp. 456--463, March 2006.Google Scholar
- W. Cheng, J. Y. H. Fuh, A.Y.C. Nee, Y. S. Wong, H. T. Loh, and T. Miyazawa. Multi-objective optimization of part-building orientation in stereolithography. Rapid Prototyping Journal, vol. 1, no. 4, pp. 12--23, April 1995.Google ScholarCross Ref
- P. T. Lan, S. Y. Chou, L. L. Chen, and D. Gemmill. Determining fabrication orientations for rapid prototyping with Stereolithography apparatus. Computer-Aided Design, vol. 29, no. 1, pp. 53--62, January 1997.Google ScholarCross Ref
- Y. Li, and J. Zhang. Multi-criteria GA-based Pareto Optimization of Building Direction for Rapid Prototyping. International Journal of Advanced Manufacturing Technology, Springer, Berlin, vol. 69, no. 5--8, pp. 1819--1831, November 2013.Google Scholar
- K. D. Chu, A. Lamaze, and K. Murphy. 3D printed rapid disaster response{C}. IEEE International Symposium on Technologies for Homeland Security, IEEE, 2014:91180B.Google Scholar
Index Terms
- Printing Orientation Optimization of 3D Model
Recommendations
Cost-effective printing of 3D objects with self-supporting property
The fused deposition modeling (FDM) printer is a simple, affordable and widely used device in the 3D printing society. However, the high price of printing materials is one of major restrictive factors for its further application. Based on the self-...
Parallel 3D printing based on skeletal remeshing
SIGGRAPH '16: ACM SIGGRAPH 2016 PostersAlthough 3D printing is becoming more popular, but there are two major problem. The first is the slowness of the process because of requirement of processing information of an extra axis comparing to tradition 2D printers. The second is the printable ...
Genetic Simulated Annealing Algorithm Used for PID Parameters Optimization
AICI '09: Proceedings of the 2009 International Conference on Artificial Intelligence and Computational Intelligence - Volume 01A type of genetic simulated annealing algorithms (GSAAs) is presented, which is used to optimize the parameters of proportional-integral-derivative (PID) controllers. This approach combines the merits of genetic algorithms (GAs) and simulated annealing ...
Comments