3D Printing Orientation Optimization Based on Non-dominated Sorting Genetic Algorithm

Authors

Dai Ning, College of Mechanical & Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;
Lisong Ou, College of Mechanical & Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;
Renkai Huang, College of Mechanical & Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;
Liu Hao, College of Mechanical & Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;

Abstract

Abstract: Part orientation is one of the key technologies in 3D Printing,which has important influence on the surface precision, machining time and machining cost of the part. This problem is a research hot point of how to balance the surface precision and machining time. The improved Non-dominated Sorting Genetic algorithm was proposed to solve the problem of part orientation optimization. The mathematical model of part surface accuracy and machining time were constructed. The chromosome model of part orientation and the adaptive crowding distance were established. The genetic operators of select, crossover and mutation were used to get a set of iterative solution. The experiments show that this method can effectively solve the problem of optimum part orientation.

Recommended Citation

Ning, Dai; Ou, Lisong; Huang, Renkai; and Hao, Liu (2020) "3D Printing Orientation Optimization Based on Non-dominated Sorting Genetic Algorithm," Journal of System Simulation: Vol. 27: Iss. 10, Article 21.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol27/iss10/21

First Page

2365

Revised Date

2015-07-24

DOI Link

https://doi.org/

Last Page

2373

CLC

TP391.72

Recommended Citation

Dai Ning, Ou Lisong, Huang Renkai, Liu Hao. 3D Printing Orientation Optimization Based on Non-dominated Sorting Genetic Algorithm[J]. Journal of System Simulation, 2015, 27(10): 2365-2373.