A Functional Model Printing Approach Optimized for Cost-Efficiency Using FDM Technology ^†

Abstract

The study focuses on optimizing the Fused Deposition Modeling (FDM) process by implementing a cost-efficient support structure strategy. The main objective is to develop a systematic approach for analyzing structural and technological parameters considering print time, material consumption, and surface quality. The study focus is on manually designed support structures as an alternative to automatic generation, allowing for precise control over print settings. The methodology includes comparative analysis of various support strategies using a Prusa MK3S+ printer under standardized conditions. Statistical and visual evaluations confirm that the designed support structures reduce print time by up to 59 min while maintaining comparable material use and superior surface finish. The findings offer a practical framework for optimizing 3D printing processes, reducing waste, and enhancing efficiency in prototyping and small-batch production.

1. Introduction

Fused Deposition Modeling (FDM) is among the most widely used additive manufacturing technologies in both domestic and industrial 3D printing due to its affordability, material variety, and rapid prototyping capabilities. Despite these advantages, a key challenge in the FDM process is the necessity of support structures when printing complex geometries with overhanging features [1,2,3,4].

Modern slicing software—commonly referred to as “slicers”—facilitates automatic generation of support structures based on model orientation and predefined parameters. While these tools simplify the process for end users, they frequently lead to excessive material usage, prolonged print times, and visible surface marks following support removal. Conversely, manually designed support structures offer finer control and optimization potential but require additional time, design experience, and technical knowledge [5,6,7,8].

Today, a wide range of software tools across various categories are available to aid in design automation. These tools can be effectively utilized for designing custom support structures [9,10,11,12].

2. Materials and Methods

This study introduces a hybrid approach for optimizing support structures in FDM by integrating manually designed geometries with selectively customized slicing parameters. Unlike conventional methods that rely solely on automatic support generation, the proposed method allows for targeted improvements in material usage, surface quality, and print time. The presented method shows the application of dual-component support design and parameter isolation during slicing, providing a replicable framework for efficiency-driven prototyping [13,14,15,16].

The present study aims to analyze the performance of manually designed versus automatically generated support structures in the FDM process. Real-world models are used to compare print time, material consumption, and post-processing surface quality following support removal.

2.1. Analysis Parameters

All models were printed using a Prusa MK3S+ 3D printer (Prusa Research, Prague, Czech Republic) (Figure 1) under identical printing conditions in terms of temperature and speed, with a controlled ambient temperature of 20 °C (±1 °C). The filament used was PLA—one of the most commonly applied materials for prototyping. Print preparation and analysis were conducted using PrusaSlicer version 2.9.1. Three evaluation criteria were defined: (1) filament consumption (g), (2) total print time (min), and (3) post-processing surface quality. Surface quality was assessed visually by identifying sagging, layer disruptions, and residual marks from support removal [17,18,19,20,21,22].

2.2. Methodology

The first stage of the study compared the parameters “printing time” and “material usage” across various automatically generated support strategies. Many slicers now offer a “Paint” function that allows users to manually indicate where support should be generated, offering some level of optimization.

3. Results

Table 1. Results with values obtained from the information panel of the slicing software.

Type of Support	Used Filament (g)	Printing Time (min)
Paint Grid	2.55	30
Paint Snug	2.31	29
Paint Organic	2.65	31
Build Plate Only Grid	2.79	31
Build Plate Only Snug	2.51	29
Build Plate Only Organic	2.85	33
Everywhere Grid	2.86	32
Everywhere Snug	2.51	29
Everywhere Organic	2.81	33
Designed Support	2.27	27

presents the results of the study, with the values obtained from the information panel of the slicing software UltiMaker Cura 5.10.

As shown in Figure 2, the Designed Support approach demonstrated superior performance in both material efficiency and print time.

In the analysis of the remaining control parameters, the two models with the best values in terms of material usage and printing time were considered, namely Paint Snug and Designed Support.

Three models using the Paint Snug support type were printed, focusing on the regions indicated in Figure 3 for evaluation. In the first model, sagging was observed in the specified areas, along with noticeable material shrinkage. Based on these findings, the position of the support structures was adjusted for the subsequent prints. The second model (Figure 4) showed improved results, although problematic zones were still present. In the third model (Figure 5), both the placement and the number of supports were optimized, resulting in significant improvements in the targeted areas.

Based on the previous studies, a support structure was designed to follow the contour of the main part (Figure 6).

In this approach, the two components—the part and the designed support—are exported as separate files and then imported together into the slicing software (Figure 6). The main advantage of this method over automatically generated supports is the ability to fine-tune specific parameters that contribute to reduced print time and material usage, namely Bottom Solid Layers, Perimeters, and Top Solid Layers. Figure 7 and Figure 8 illustrate the print settings used for both the support structure and the main part.

Analysis of the first model printed with the Designed Support approach (Figure 9) showed that the previously identified crucial areas performed well; however, material shrinkage was detected in a new region.

A comparative analysis between models 1.3 and 2.1, following the removal of the support structures, revealed an additional problematic area in the model with Designed Support (Figure 10), indicating the need for adjustments in the support print settings. In the remaining regions of the part, the results were satisfactory, with no noticeable deformation in the model’s geometry.

To maintain minimal material usage and printing time, the support structure must be divided into two separate components, allowing for additional adjustments in the print settings. To eliminate the shrinkage observed in the initial analysis, the design of the support structure in the affected area needs to be modified. Figure 11 shows the updated settings for Bottom Solid Layers and Top Solid Layers applied specifically to the separate support component.

The results of the changes were analyzed and compared with Model 2.1, revealing an improvement in the examined sections (Figure 12).

An extended comparison across a full build plate containing 48 identical models revealed that the Designed Support method reduced total print time by 59 min with comparable material consumption—highlighting the method’s scalability and production efficiency (Figure 13).

4. Discussion

The comparative results suggest that manual design of support structures offers significant advantages over automatic generation, especially in production scenarios requiring optimized material usage and reduced post-processing. The ability to define support geometry externally allows for better alignment with the part’s topology, minimizing stress concentrations and improving overall print integrity. Additionally, the reduced printing time observed in the Designed Support configuration (by up to 18% compared to Paint Grid) demonstrates its potential for scaling up production without sacrificing quality. While this approach requires additional design time and expertise, the trade-off is justified by the efficiency gains observed.

5. Conclusions

The use of manually designed support structures significantly improves cost-efficiency in FDM printing by reducing both material usage and print time. The best-performing configuration—Designed Support—achieved a material usage of 2.27 g and a print time of 27 min, outperforming all automatically generated strategies tested, such as the Paint Organic and Build Plate Only Organic, which used up to 2.85 g and required up to 33 min. Surface quality assessments showed fewer defects and reduced post-processing needs. Notably, when applied to a batch of 48 identical parts, the Designed Support method led to a total print time reduction of 59 min, confirming its scalability for production-level scenarios. By allowing for selective adjustment of parameters like Bottom Solid Layers and Perimeters, this approach enables targeted refinements in problematic areas. Overall, the results validate the effectiveness of manual support design as a reliable strategy for improving productivity and part quality in FDM printing.