## 5 Conclusions  
This research aimed to investigate the impact of two practical print settings--orientation and infill density--on the mechanical performance of resin-printed parts. Based on the experimental results, several key takeaways emerged:  
* The angle at which a part is printed matters: Printing parts at a 75\({}^{\circ}\) tilt turned out to be the most effective, allowing them to stretch and deform the most before breaking. This orientation outperformed the standard flat (0\({}^{\circ}\)) setup by almost 20%. * Support settings play a behind-the-scenes role: Around the 60\({}^{\circ}\) mark, the slicing software started applying different automatic support settings, which had a noticeable impact on the results. This suggests that not only the angle but also how the software interprets it is important. * Filling the part completely is not always better: Infill densities between 60% and 90% provided just as much, if not better, deformation performance than completely solid parts. * Interestingly, lower infill levels also made the parts less brittle, breaking more slowly and predictably, rather than snapping abruptly. Figure 9: Displacement of the sections before fracture. * Someone can save time and material without sacrificing strength: Lighter parts with less infill take less time and use less resin to print, yet still hold up impressively well under load--an ideal balance for many real-world applications. * The DIC system proved to be a powerful tool: Using the GOM ARAMIS system allowed us to track exactly how and where the parts deformed, giving us detailed insight without physically touching or altering them. In short, with just a few thoughtful adjustments to print orientation and internal structure, it is possible to make resin-printed parts that are stronger, more flexible, and more resource-efficient. These findings can help makers, engineers, and designers get more out of their resin printers--whether they are creating prototypes or real, working parts. Although this study provides valuable insights into how print orientation and infill density impact the strength and flexibility of resin-printed parts, several limitations are worth noting. The authors worked with only one type of resin, printer, and slicing software, which means the results may not be applicable to other setups or materials. The mechanical testing focused on a modified bending test, so we did not explore how these parts behave under other loads, such as tension or repeated stress over time. Environmental factors--such as heat, moisture, or UV exposure--were also not included, even though they could affect how these parts perform in real-world conditions. Lastly, while we used advanced tools like the GOM ARAMIS system to measure deformation, we did not use simulation or predictive models to extend our findings beyond the tested cases. Looking ahead, there are several exciting directions that this research could take. For example, integrating artificial intelligence or machine learning [75; 76; 77] could help predict part performance based on different print settings or material types, saving time and resources during the design phase. Tools like fuzzy logic [78; 79] can also help navigate the trade-offs between print speed, material usage, and mechanical strength, especially in cases where inputs and priorities are not always clear-cut. On a broader level, future studies could investigate how these print strategies impact the environmental footprint of resin printing by examining factors such as energy consumption, waste generation, and recyclability. By combining smart technology with sustainability goals [80; 81; 82; 83; 84; 85; 86], someone can move closer to making resin-based 3D printing not just more reliable, but also more responsible. Future research could also build on current findings by exploring how intelligent design and production frameworks--such as those outlined by [PERSON] [87], [PERSON] et al.