A Hybrid Fuzzy-PSO Framework for Multi-Objective Optimization of Stereolithography Process Parameters.

ABSTRACT: Additive manufacturing is driving a significant change in industry, extending beyond prototyping to the inclusion of printed parts in final designs. Stereolithography (SLA) is a polymerization technique valued for producing highly detailed parts with smooth surface finishes. This study presents a hybrid intelligent framework for modeling and optimizing the SLA 3D printer process's parameters for Acrylonitrile Butadiene Styrene (ABS) photopolymer parts. The nonlinear relationships between the process's parameters (Orientation, Lifting Speed, Lifting Distance, Exposure Time) and multiple performance characteristics (ultimate tensile strength, yield strength, modulus of elasticity, Shore D hardness, and surface roughness), which represent complex relationships, were investigated. A Taguchi de

SUBMITTER: Al-Khafaji MMH 

PROVIDER: S-EPMC12654128 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature