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

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.

Key words: 3D printing, part orientation, genetic algorithm, multi-objective optimization

CLC Number:

TP391.72

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.

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