Improvement of Mechanical Properties of 3D Printed Polylactide Material Using Modified Nelder Mead Algorithm and Multi-Objective Optimization Approach

Abstract

Fused deposition modeling (FDM) is an advanced additive manufacturing technique that has become increasingly popular in a wide range of industrial applications. The technique offers several advantages over traditional manufacturing methods, including increased efficiency, reduced costs, and faster production times. One key factor affecting FDM product quality is the printing design parameters. By carefully selecting and optimizing these parameters, manufacturers can ensure that their FDM products have superior mechanical properties and meet the highest quality standards. This study aims to maximize the fracture strength and minimize the fracture strain of polylactide (PLA) material by applying a multi-objective optimization approach. Modified Nelder Mead Algorithm is utilized to determine the effects of various printing design parameters such as infill pattern, layer thickness, infill density, and printing speed on the fracture strength and fracture strain of the PLA material. Two different scenarios were defined to examine the effect of design parameters in solving the optimization problem. In the first scenario, the design parameters were allowed to take only specified level values, while in the second scenario, they were also allowed to take continuous values. Pareto set of solution was obtained by taking into account the situations where two objective functions are of different importance. The results show that the honeycomb pattern should be preferred when the fracture strength output is more critical, and the triangle pattern should be preferred when the fracture strain output is more important. It has been determined that when two design parameters are equally important, the appropriate design can be achieved by using an infill density of 99, a triangle infill pattern, a layer thickness of 0.1, and a printing speed of 45.