Theoretical foundations of computer science

Method for optimising the mass of plastic gearbox components in $3D$ printing using a genetic algorithm

T. Yu. Kim^ab, A. V. Pechkouskaya^a, Ya. I. Pechkouski<sup>a

a</sup> United Institute of Informatics Problems, National Academy of Sciences of Belarus, 6 Surganava Street, Minsk 220012, Belarus
^b Urgench branch of the Tashkent University of Information Technologies named after Muhammad Al-Khwarizmi, 110 Al-Khwarizmi Street, Urgench 220100, Uzbekistan

Abstract: This paper proposes the development of a fitness function for a genetic algorithm aimed at minimising the mass of gearbox components manufactured from polylactide using the FDM printing method. For gears optimised using genetic algorithms, the best results can be obtained in a solution space defined by constraints on contact strength, bending endurance, static shaft strength and fatigue strength. It is shown that evolutionary optimisation of the design of plastic parts manufactured using the FDM printing method makes it possible to reduce their mass without compromising strength and functionality. To improve the quality of optimisation, a technique for calculating the mass of gears is developed that surpasses the existing techniques in the accuracy of the results. It is expected that the obtained results will be used in the design and prototyping of robotic units that are demanding on the mass of parts. Computer modelling is herein performed in the Matlab environment.

Keywords: genetic algorithms; Matlab; gearbox; gear; optimisation; mass; evolutionary algorithms; 3D printing; FDM printing

UDC: 044.942, 519.876.5

Received: 30.08.2024
Revised: 04.10.2024
Accepted: 18.10.2024