## 1 Introduction
[19] to optimize the stereolithographic process factors in order to increase the accuracy of the geometrical component. This analysis considered the following parameters: layer thickness, hatch overcure, hatch spacing, border overcure, fill spacing and fill cure depth. [PERSON] and [PERSON] [20] presented a parameter estimation approach to process planning for stereolithography to demonstrate significant surface finish improvements. [PERSON] [21] created a model based on geometrical analysis to describe the roughness of the surfaces of parts printed using the SLA process. The model was based on triangular shapes, called the stairstep effect, which depend on parameters like layer thickness, position on the platform and part orientation. [PERSON] and [PERSON] [9] proposed a neural network model with a genetic algorithm and simulated annealing to optimize stereolithographic (SLA) parameters to achieve minimum shrinkage of H-shaped parts. Three input parameters were selected: layer thickness, hatch overcure and hatch spacing. The results showed that the layer thickness and hatch overcure had a negative effect, and hatch spacing positively affected the total dimensional inaccuracy of the SLA parts. Moreover, researchers have been motivated in recent decades to improve the dimensional accuracy of 3D-printed objects by optimizing the process parameters. [PERSON] et al. [22] evaluated the influence of printing parameters like print orientation, part positioning on a build platform and the postcuring process on the dimensional accuracy of SLA-printed rectangular objects. One-way ANOVA was used for data evaluation, and it was found that the printing orientation and position affect parts' dimensional accuracy. [PERSON] et al. [23] assessed the impact of print layer thickness on the clinical acceptability of 3D-printed SLA orthodontic models. The results showed that a thin layer thickness gave better accuracy. [PERSON] et al. [24] applied response surface methodology to model stereolithographic process parameters with dimensional accuracy and found that the layer thickness was the most significant factor. In Khodaii and [PERSON] [25], the influences of surface angle, hatch space and postcuring time on surface roughness in the SLA process were studied using the printed parts under various experimental parameters. The results demonstrated that as the surface angle increased from 0 to 90 degrees, the surface irregularity rose dramatically. In contrast, postcuring time had a negligible and insignificant impact on surface roughness. [PERSON] et al. [7] studied the surface roughness of the side walls of the parts manufactured using projection micro-stereolithography. They proposed a physics-based analytical model as a function of the exposure time and the layer thickness to predict the surface roughness of the manufactured parts. The layer thickness significantly influenced the light-induced surface roughness compared with the exposure time. [PERSON] et al. [26] examined the dimensional accuracy and degree of polymerization of a transparent photopolymer resin object produced using SLA at different postpolymerization times and temperatures using ANOVA. Lower temperatures improve tissue surface accuracy; according to the study, the polymerizing temperature had a greater effect on dimensional accuracy than the polymerizing time. Using the Taguchi method, the manufacturing parameters of the stereolithographic apparatus were adjusted by [PERSON] [27] to assure the accuracy of the 3D-printed objects. Layer thickness, orientation and exposure duration were selected as the printing factors, and the ANOVA results showed that exposure duration significantly affected accuracy. [PERSON] et al. [28] examined the experimental data on the dimensional correctness of cured resin SLA 3D-printed objects. In this research, the authors set out to use an experimental design to show how layer thickness, exposure time and x-orientation interact as process characteristics that contribute to dimensional accuracy errors.