Optimizing 3D printing parameters for enhanced compression behavior in chiral-core PLA sandwich structures

Abstract

The goal of this research is to examine how certain 3D printing parameters affect the compression behavior of Polylactic Acid (PLA) sandwich beams with a chiral core topology. The parameters examined include printing speed, infill density, and build orientation. These sandwich beams are lightweight, high-strength structures used in the construction, automotive, and aerospace industries. Their enhanced performance can also benefit the energy sector, as well as sports and medical equipment. The findings of this work will provide a framework for advancing materials science and additive manufacturing, helping to improve 3D printing procedures to achieve better mechanical properties. This research employs the Taguchi approach for experimental design to investigate how build orientation, printing speed, and infill density influence the compression behavior of PLA sandwich beams with chiral core topology. The findings revealed that build orientation of 0°, print speed of 30 mm/s and infill density of 60% provided the most optimal and superior mechanical performance as compared to all other specimens. Build orientation had the greatest influence among all parameters, contributing between 36.0% and 50.5% to the mechanical characteristics. This result aligns with previous studies, which often identify build orientation as a key factor affecting the mechanical properties of 3D-printed structures. Infill density also played an important role, contributing between 16.5% and 26.0% to strength and stiffness. Print speed’s contribution varied more widely, ranging from 2.0% to 30.8%.

Keywords

3D printed sandwich beams chiral core compression tests print speed infill density build orientation Taguchi design of experiment

Introduction

In many engineering applications, parts must absorb a large amount of energy prior to breaking, especially when compressed, to guarantee that they can bear high loads and stresses without breaking structurally. This is difficult for materials that are known for their brittle characteristics rather than ductility, such as PLA. PLA samples are known for being brittle, but with the correct design and printing parameters, they can absorb a big amount of energy, making them suitable for applications that require high energy absorption. In this paper by,¹ the effects of different unit cell parameters on the mechanical properties of sandwich beams with chiral cores were studied. The Fused Deposition Modelling (FDM) technology was utilized to 3D print 27 unique specimens. The specimens were completely made with an improved type of PLA, which is PLA+. The parameters that were investigated were the diameter of the unit cell, the thickness, and the angle. Upon finishing the 3D printing of the samples, compression tests were carried out. The samples were placed in a way so that the compressive force was applied perpendicular to the face sheets of the beams, along their height. The mechanical properties such as Young’s modulus, Specific Energy Absorption (SEA), plateau stress, and densification stress were evaluated. Major findings showed that chiral unit cells with a diameter less than 15 mm exhibited outstanding Young’s modulus and energy absorption (EA). Additionally, Young’s modulus and SEA dropped with the reduction of the chiral core thickness and angle.

A study by Indreş et al.² investigates how sandwich beams with different core structures react under bending tests. The cores of the sandwich beams include chiral, honeycomb, and re-entrant auxetic honeycomb with 0° and 90° positions of the cells, and they were designed with the use of CATIA V5. Four samples with a relative density of 0.15 and another four with a relative density of 0.25 were created by using an FDM 3D printer. Moreover, the material used to print the specimens is PLA. Bending stiffness, energy absorption, and strength were the mechanical properties studied upon completing the bending tests. It was found that the honeycomb beam can undergo the maximum force and had the stiffest behavior out of all the specimens, however, with the rise of relative density, the honeycomb core got more brittle. The chiral beam was also very stiff but had a lower strength than the honeycomb core, making these two cores suitable choices for high stiffness applications. Additionally, the re-entrant auxetic honeycomb beams showed the ability to absorb the most energy out of all the specimens.

Najafi et al.³ looked at how different core topologies affect the performance of sandwich beams. Their aim was to investigate the bending properties when implementing auxetic cores in beams. The different core topologies in the sandwich beams were square node anti-tetra chiral, re-entrant auxetic, and arrowhead. All of these beams were 3D printed using an FDM printer and the material used was Acrylonitrile Butadiene Styrene (ABS). They also 3D printed sandwich beams with honeycomb cores and used them to compare them with the other beams. A total of 12 samples, 3 of each beam, were printed and tested under the three-point bending machine. Mechanical properties such as load bearing capacity, stiffness, flexural behavior, and energy absorption were investigated. Results showed that the beams with auxetic core exhibit great energy absorption, but do not perform as well as beams with honeycomb cores. However, the sandwich beams with auxetic core showed high load bearing capacity, and the arrowhead core had the highest.

Spahic et al.⁴ aim to find and investigate the factors that impact the bending properties of 3D printed sandwich beams with cellular cores. Four different cellular core patterns were chosen which include a hexagonal re-entrant honeycomb, a swastika pattern, a double-arrow shaped pattern and a hexachiral pattern. Each pattern in the sandwich beam was 3D printed 5 times, which resulted in a total of 20 beams. The 3D printing technique used for manufacturing the specimens was Fused Filament Fabrication (FFF), and the 3D printer used was Ultimaker 2. Additionally, the material used was co-Polyester (CPE). A three-point bending machine was then used to test the samples to study how their mechanical behavior changes. It was concluded that the skin stiffness of a sandwich beam with a cellular core is a crucial factor that affects its behavior. Moreover, they came to the conclusion that the transverse isotropy behavior must be taken into account in addition to auxeticity in order to maximize the shear stiffness of a cellular solid.

Sandwich beams with auxetic and non-auxetic cores were studied and their mechanical and vibrational properties were investigated through experimental tests and finite element simulations.⁵ A total of 12 specimens were printed of 3 patterns which are rectangular, hexagonal, and re-entrant honeycombs. Each pattern was printed 4 times with different densities. The material used for printing the samples was PLA with flax fibers and they were printed by using the additive manufacturing technology. Furthermore, tensile tests were conducted on the specimens to study how their density and topology affect their Young’s modulus and Poisson’s ratio. After the tensile tests, vibration tests were performed on the specimens. It was found that a low cell density across the specimen’s width results in low stiffness and good damping, while extensive cell density across the specimen’s width results in increased stiffness and reduced damping.

In another paper by Hamrouni et al.⁶ they investigate the static behavior of a sandwich beam with anti-trichiral core. Specimens were prepared by a RAISE3D Pro2 Plus 3D printer, and the filament used was PLA with flax fibers. Upon finishing the 3D printing of the samples, tensile tests were performed only on the anti-trichiral core of the sandwich beams, and then, three-point bending tests were carried out on the sandwich structures. The shear stiffness, bending stiffness, and modulus were the studied properties for the sandwich beams. The results of the study indicate that the Poisson’s ratio of the core is highly dependent on the unit cell size. Additionally, the core’s static behavior is impacted by the significant variation in Young’s modulus with radius, particularly at higher values. Greater bending stiffness, shear stiffness, and reduced stresses in the facing and core of the sandwich beam are all enhanced by a larger unit cell radius.

The impact of different core patterns in sandwich structures on the mechanical properties of the specimens were studied.⁷ The different core topologies were S-shape corrugated, out-of-plane honeycomb, and in-plane hexagonal honeycomb. The samples were 3D printed using an FDM 3D printer, and the material used was PLA. Tensile tests and three-point bending tests were then conducted on the samples. It was found that when sandwich structures were constructed with out-of-plane cell patterns instead of in-plane cell cores, the failures progressed more predictably in the tensile test and under the triaxial condition of loads generated in the three-point bending test. Moreover, sandwich constructions with in-plane hexagonal honeycomb cores require stiff faces in order to improve the core’s ability to limit the propagation of cracks in the beam’s cross-section by providing superior global absorption to bending loads.

Montazeri et al.⁸ study the bending behavior of auxetic and non-auxetic 3D printed sandwich beams. The 3D printed structures were re-entrant and cellular hexagonal honeycombs and they were printed using an FDM-based 3D printer. Two sets of samples were created, one out of PLA and the other out of thermoplastic polyurethane (TPU) and then their performance was compared. Additionally, the specimens were filled with polyurethane (PU) foam and their bending modulus and energy absorption were investigated. After the completion of the bending tests, it was found that by filling the PLA samples with PU foam the performance of the bending modulus and energy absorption drops. On the other hand, the TPU specimens’ performance was greatly enhanced. Also, because the re-entrant’s unit cell is larger than the hexagonal one, re-entrant honeycombs are more adequately reinforced with PU foam.

A paper by Essassi et al.⁹ investigates the quasi-static indentation behavior of 3D printed sandwich structures with auxetic core and its effects on the mechanical properties of the structures. Four distinct core layouts with varying numbers of cells were tested. The samples were 3D printed using the PLA filament reinforced with flax fibers. Quasi-static indentation tests were then carried out on the specimens. Finding the failure mechanisms that develop under indentation loading is the key goal of this study. Findings indicated that when the number of cells in the core increased, both the mechanical properties and the energy wasted improved. The fact that more cells lead to more stiffness serves as justification for this outcome. Moreover, the damage characteristic was found to be primarily dependent on the cell count.

In a study by Zahed et al.¹⁰ the effect of adding more supports on 3D printed sandwich beams under bending loading was investigated. The beams were structures of re-entrant honeycomb. The samples were printed using a 3D printer with FDM technology and the material used was TPU. The aim of this study was to see how the extra supports will affect the flexural behavior and the energy absorption of the specimens. The results show that under bending loading, honeycombs with concave curved supports perform significantly better than traditional re-entrant honeycombs in terms of flexural modulus. Moreover, when bending loading is applied to honeycomb structures, it is clear that the thickness of the additional support has the greatest impact on the bending modulus, SEA, and EA.

Mansour et al.¹¹ studied the dynamic and mechanical characteristics of 3D printed hierarchical honeycomb sandwich beams created from PLA, PLA reinforced with carbon fibers (PLA/CF), and PLA reinforced with nanodiamonds (PLA/uDiamond). Additionally, the honeycomb structures were created and designed of the zeroth, first, and second order. The 3D printer used in this work is Ultimaker 2⁺ that uses the fused filament fabrication (FFF) technology, also known as fused deposition modeling (FDM). The specimens went under compressive and bending tests. The outcomes indicate that adding nanodiamonds to the PLA improved the 3D-printed samples’ strength, hardness, and elastic modulus. Furthermore, when compared to the zeroth and first hierarchies, the second order of the PLA/uDiamond hierarchical sandwich beam showed higher strength, flexural, and elastic modulus. When compared to PLA nanocomposite filaments, the second order of the PLA/uDiamond honeycomb structure showed the largest gain in stiffness in terms of dynamic behavior.

In this work by Zoumaki et al.¹² the mechanical properties of starch-based 3D printed sandwich beams were investigated. The core of the beam is made of PLA and the skins are made of maize starch. For the 3D-printed core, three orders of hierarchical honeycombs were created which are zeroth, first, and second. The specimens went under a three-point bending test to study their mechanical behavior. Upon the completion of the tests, the findings revealed that using a second order hierarchy core enhanced the biodegradable sandwich structure’s bending strength, and starch-based skins enhanced the PLA-based honeycomb core’s strength and stiffness. Together with the results of the experiments, finite element analysis (FEA) was also used to evaluate the flexural behavior of the hierarchical honeycombs. Bending properties showed that a PLA honeycomb core combined with starch-based films is a good way to create biodegradable sandwich structures.

In a paper by Zhao et al.¹³ the energy absorption and flexural behavior of sandwich beams with star-triangular honeycomb core and the core by itself. The core is 3D printed using the stainless-steel material, and the front and back sheets are made from aluminium. By utilizing epoxy film, the core and aluminium panels were glued together to make up the sandwich beam. Three-point bending tests were carried out on the samples and the results show that the core only shows localized bending deformation in the loading zone, while the entire sandwich beam cells show shrinkage deformation and tensile deformation in the loading area, respectively, in their surrounding cells. Furthermore, it was found that the compression location and structural characteristics affect the sandwich beam’s deformation mode.

In a research paper by,¹⁴ the aim was to study how wood-based facings, both in terms of thickness and kind, affected the sandwich beams with auxetic core’s stiffness, strength, and capacity to absorb and distribute energy. The samples went under three-point bending tests and it was found that beams with plywood and high-density fibreboard (HDF) facings offer the best mechanical qualities. Although beams with plywood facings can equally effectively absorb energy, HDF beams demonstrated a greater capacity in this regard.¹⁵ aim to evaluate the crashworthiness characteristics and quasistatic performance of 3D-printed re-entrant diamond auxetic core and sandwich beams. The material used in this research is ABS. The outcomes are compared with those of standard re-entrant beams with identical unit cell sizes. In both in-plane and out-of-plane directions, the novel re-entrant diamond auxetic specimens outperformed energy absorption properties. As a core and sandwich, the new metamaterial has enhanced in-plane energy absorption by 88.33% and 29.24%, respectively, over the standard re-entrant beams,¹⁶ investigate the flexural behavior of a novel sandwich beam with graded auxetic honeycomb core. The samples are 3D printed utilizing the FDM technology and the material used is PLA. The findings show that the ideal cell angle gradation enhances the bending modulus to density ratio by 18.9%, while the lowering of the cell wall thickness to length ratio raises the flexural failure stress and specific absorbed energy by 35% and 45.8%, respectively,¹⁷ study the bending behavior of 3D printed sandwich beams with unidirectional core stiffeners. Samples of arched cell, corrugated, and trapezoid were 3D printed using thermomechanical pulp fibre-reinforced PLA. Upon the completion of the tests, it was found that out of the three sandwich beams, the trapezoid was the most superior in terms of bending properties.

Xu et al.¹⁸ investigated the clinical treatment of bone tissue scaffold using 3D printing process. Imaging was used to find the bone defect and 3D printing was used to fabricate the model. The study revealed the potential of creating micro/nano pores in the scaffold to support cell development and drug delivery etc.¹⁹ presented an improved, volume-conserving height-profile model for drop-on-demand 3D printing. This model provided multilayer 2D patterns via piecewise height-difference functions²⁰ investigated the development of bio-composites using marine waste. The study showed good potential of using sea urchin waste as bio-filler²¹ investigated the performance of sustainable PLA mixed Lawsonia inermis (LI) composites. The composite of PLA +15%LI provided the best compressive strength making it suitable for applications where PLA is being used²² also investigated the optimization of different printing parameters in combition with Artificial Bee Colony (ABC) algorithm for PLA/Wood composites. The ABC algorithm improved the prediction accuracy and the PLA/Wood composite was found to be a good option for applications²³ also investigated the performance of PLA/Henna composites. Results showed that 5% Henna composite provided the highest tensile strength. The study revealed henna as a good bio-filler material²⁴ also evaluated the performance of PLA/CF using statistical ANOVA and Neural Network approaches. The study found that infill density was the most influential parameter²⁵ also investigated the PLA/Wood composite performance. The study revealed that raster angle was the most influential parameter²⁶ examined the optimization of PLA/copper composite beams using VIKOR and GRA techniques. The study compared both models and found that stiffness and strength was better optimized by the GRA technique.

The literature review indicates that the specific combination of printing parameters and output responses considered in this study is rarely explored, making the chosen parameter–response set relatively unique. In addition, the use of desirability function analysis (DFA) to optimize these particular responses under this parameter combination is scarcely reported, further distinguishing the present work from existing studies (Tables 1 and 2).

Table 1.

Summary of literature review.

Reference no.	Source	Material used	3D Printing parameters	Major conclusions
1	(Kamarian et al., 2024)	PLA+	• Nozzle temperature: 215°C • Bed temperature: 60°C • Layer height: 0.15 mm • Printing speed: 50 mm/min	• Chiral unit cells with a diameter less than 15 mm exhibited outstanding Young’s modulus and energy absorption. • Young’s modulus and SEA dropped with the reduction of the chiral core thickness and angle.
2	(Indreş et al., 2021)	PLA	• Infill density: 100% • Build plate temperature: 60°C For cores with relative density of 0.15: • Printing temperature: 190°C • Layer height: 0.1 mm • Printing speed: 30 mm/s For cores with relative density of 0.25: • Printing temperature: 205°C • Layer height: 0.2 mm • Printing speed: 70 mm/s	• Honeycomb beam can undergo the maximum force and had the stiffest behavior. • Chiral beam had high stiffness but lower strength than honeycomb. • Re-entrant auxetic honeycomb beams showed the ability to absorb the most energy.
3	(Najafi et al., 2022)	ABS	• Layer height: 0.2 mm • Nozzle temperature: 243±5°C • Bed temperature: 85±5°C • Nozzle diameter: 0.4 mm • Infill percentage: 100% • Extrusion width: 0.51 mm	• Sandwich beams with auxetic core exhibit great energy absorption, but do not perform as well as beams with honeycomb cores. • Sandwich beams with auxetic core showed high load bearing capacity, and the arrowhead core had the highest.
4	(Spahic et al., 2021)	CPE	• Layer height: 0.2 mm • Nozzle temperature: 255°C • Plate temperature: 85°C • Printing speed: 60 mm/s • Nozzle diameter: 0.4 mm	• The skin stiffness of a sandwich beam with a cellular core is a crucial factor that affects its behavior. • The transverse isotropy behavior must be considered in addition to auxeticity in order to maximize the shear stiffness of a cellular solid.
5	(Hamrouni et al., 2023)	PLA with flax fibers	• Bed temperature: 60°C • Nozzle diameter: 0.4 mm • Travel speed: 60 mm/s • Layer thickness: 0.2 mm • Infill density: 100%	• Low cell density across the specimen’s width results in low stiffness and good damping, while extensive cell density across the specimen’s width results in increased stiffness and reduced damping.
6	(Hamrouni et al., 2023)	PLA with flax fibers	• Bed temperature: 55°C • Travel speed: 60 mm/s • Layer thickness: 0.2 mm • Infill density: 100%	• Poisson’s ratio of the core is highly dependent on the unit cell size. • The core’s static behavior is impacted by the significant variation in Young’s modulus with radius, particularly at higher values. • Greater bending stiffness, shear stiffness, and reduced stresses in the facing and core of the sandwich beam are all enhanced by a larger unit cell radius.
7	(Castro et al., 2022)	PLA	• Layer thickness: 0.2 mm • Print speed: 50 mm/s	• When sandwich structures were constructed with out-of-plane cell patterns instead of in-plane cell cores, the failures progressed more predictably in the tensile test and under the triaxial condition of loads generated in the three-point bending test. • Sandwich constructions with in-plane hexagonal honeycomb cores require stiff faces in order to improve the core’s ability to limit the propagation of cracks in the beam’s cross-section by providing superior global absorption to bending loads.
8	(Montazeri et al., 2023),	PLA & TPU	• Retraction speed: 85 mm/s for PLA & 30 mm/s for TPU • Layer height: 0.2 mm for PLA & 0.5 mm for TPU • Nozzle temperature: 190°C for PLA & 210°C for TPU	• Filling the PLA samples with PU foam the performance of the bending modulus and energy absorption drops. On the other hand, the TPU specimens’ performance was greatly enhanced. • Because the re-entrant’s unit cell is larger than the hexagonal one, re-entrant honeycombs are more adequately reinforced with PU foam.
9	(Essassi et al., 2021)	PLA with flax fibers	• Extrusion head temperature: 210°C • Building platform temperature: 55°C	• When the number of cells in the core increased, both the mechanical properties and the energy wasted improved. • The damage characteristic was found to be primarily dependent on the cell count.
10	(Zahed et al., 2023)	TPU	• Nozzle diameter: 0.4 mm • Layer height: 0.5 mm • Nozzle temperature: 215°C	• Under bending loading, honeycombs with concave curved supports perform significantly better than traditional re-entrant honeycombs in terms of flexural modulus. • When bending loading is applied to honeycomb structures, it is clear that the thickness of the additional support has the greatest impact on the bending modulus, SEA, and EA.
11	(Mansour et al., 2023)	PLA, PLA/CF, & PLA/uDiamond	• Nozzle diameter: 0.6 mm • Printing temperature: 200-240°C • Bed temperature: 55-90°C • Print speed 35 mm/s	• Adding nanodiamonds to the PLA improved the 3D-printed samples’ strength, hardness, and elastic modulus. • The second order of the PLA/uDiamond hierarchical sandwich beam showed higher strength, flexural, and elastic modulus. • The second order of the PLA/uDiamond honeycomb structure showed the largest gain in stiffness in terms of dynamic behavior.
12	(Zoumaki et al., 2022)	PLA for the core & maize starch for the skins of the sandwich beams	• Nozzle extrusion temperature: 220°C • Bed temperature: 60°C • Layer height: 0.2 mm • Printing speed: 40 mm/s	• Using a second order hierarchy core enhanced the biodegradable sandwich structure’s bending strength, and starch-based skins enhanced the PLA-based honeycomb core’s strength and stiffness. • Bending properties showed that a PLA honeycomb core combined with starch-based films is a good way to create biodegradable sandwich structures.
13	(Zhao et al., 2021)	Stainless steel and aluminium alloy	• Only geometric parameters were mentioned	• The core only shows localized bending deformation in the loading zone, while the entire sandwich beam cells show shrinkage deformation and tensile deformation in the loading area, respectively, in their surrounding cells. • The compression location and structural characteristics affect the sandwich beam’s deformation mode.
14	(Peliński & Smardzewski, 2020)	Plywood and high-density fibreboard (HDF)	• Only load speed and lab conditions are mentioned	• Beams with plywood and high-density fibreboard (HDF) facings offer the best mechanical qualities. • HDF beams demonstrated a greater capacity in absorbing energy.
15	(Chikkanna et al., 2023)	ABS	• Layer height: 3 mm • Infill density: 100% • Print speed: 40 mm/s • Nozzle diameter: 0.4 mm • Nozzle temperature: 205°C • Bed temperature: 70°C	• The novel re-entrant diamond auxetic specimens outperformed the standard re-entrant energy absorption properties. • As a core and sandwich, the new metamaterial has enhanced in-plane energy absorption by 88.33% and 29.24%, respectively, over the standard re-entrant beams.
16	(Zamani et al., 2022)	PLA	• Nozzle size: 0.4 mm • Layer height: 0.2 mm • Wall thickness: 0.3 mm • Printing temperature: 190°C • Printing speed: 50 mm/s	• The ideal cell angle gradation enhances the bending modulus to density ratio by 18.9%, while the lowering of the cell wall thickness to length ratio raises the flexural failure stress and specific absorbed energy by 35% and 45.8%, respectively.
17	(Zarna et al., 2023)	Thermomechanical pulp fibre-reinforced PLA	• Nozzle diameter: 0.6 mm • Infill density: 100% • Layer height: 0.15 mm • Extrusion speed: 50 mm/s • Extrusion temperature: 200°C • Bed temperature: 60°C	• It was found that out of the three sandwich beams, the trapezoid was the most superior in terms of bending properties.

Table 2.

Summary of current study.

Printing parameters	Output responses	Methodology	Major findings
• Build orientation: (0°, 45°, and 90°) • Print speed: (30 mm/s, 50 mm/s, and 70 mm/s) • Infill density: (60%, 80%, and 100%)	• Compressive modulus • Yield strength • Plateau stress • Resilience • Toughness	• Study adapted from Kamarian et al. (2024). • CREALITY CR-M4 used with set printing parameters. • Each parameter set was tested twice.	• The input parameters of sample 1 were found to be the most optimal. • Build orientation had the highest impact on mechanical properties, contributing 36.0% to 50.5%, which aligns with the literature.

Concluding remarks

Current research

Based on the available literature, the combination of the printing parameters and specific output responses listed below is both uncommon and rare.

Desirability function analysis (DFA) was used to examine the response data in order to determine the ideal conditions.

It is extremely uncommon to find this combination of printing parameters and DFA in the body of current research.

Methodology

In order to investigate and assess the results of the earlier studies in related fields, a thorough examination of the literature was conducted. Furthermore, it is worth noting that the sample design in this research was adapted from Kamarian et al. (2024), whose work provided the foundation of this research. Although their sample was used as an inspiration, the main aim of this study is to analyze the effects of build orientation, printing speed, and infill density on the mechanical properties of those structures subjected to compression tests.

Sample preparation and materials used

In this work, sandwich beams with chiral core topology were 3D printed using the FDM method. A CREALITY CR-M4 3D printer with various print speeds, infill densities, and printing orientations was used in this research. The printing temperature was set at 200°C, while the bed temperature was set at 65°C. A 0.4 mm nozzle diameter was used, and the layer height was adjusted to 0.2 mm. Autodesk Inventor was used to create the specimens, which were then saved in STL format. After that, the STL files were opened in Ultimaker software, where Ultimaker CURA was used to slice and convert the files to GCODE format. In order to improve the research’s accuracy and precision, two samples were printed for every pair of input parameters. The build orientations that were chosen were 0°, 45°, and 90°. The print speeds were 30 mm/s, 50 mm/s, and 70 mm/s, and the infill densities were 60%, 80%, and 100% (Figures 1 and 2).

Figure 1.

(a) Sandwich beam sample in autodesk inventor. (b) Chiral unit cell in autodesk inventor.

Figure 2.

(a) CREALITY CR-M4 3D Printer. (b) Labeled picture of the printer showing key components. (c) Specimen during 3D Printing process.

Design of experiment

Three primary parameters are the subject of this study, which are build orientation, printing speed, and infill density. 27 samples would be required for a full factorial design in order to examine the interaction of these factors. To improve accuracy, doubling each sample would result in a total of 54 samples. Instead, the Taguchi method was selected in order to minimize time while yet producing accurate findings. Without requiring as many experiments as a full factorial design would, the Taguchi method helps in the analysis of the most important interactions between these parameters. Table 3 shows the Taguchi design of experiment (DOE).

Table 3.

3D printing parameters.

3D Printing parameters	Value
Nozzle diameter	0.4 mm
Printing temperature	200°C
Bed temperature	65°C
Layer height	0.2 mm
Build orientation	0°, 45°, and 90°
Printing speed	30, 50, and 70 mm/s
Infill density	60, 80, and 100%

There were nine samples, each of them was printed twice, making a total of eighteen sandwich beams. However, the average results of the two identical specimens with the same parameters was taken. Compression tests were conducted on the specimens to evaluate their mechanical properties after they were 3D printed in accordance with the relevant parameters in the Taguchi design. Figure 3 displays the specimens that were 3D printed.

Figure 3.

3D Printed sandwich beams with chiral core topology before compression tests.

Experimental procedure

In this work, a Universal Testing Machine (UTM) is used to examine the compression behavior of 3D-printed sandwich beams with chiral core topology. Compression testing, data collection, and specimen preparation are all steps in the experimental process that assess the mechanical performance of the printed structures. To guarantee precise and consistent findings, a crosshead speed of 0.5 mm/min was used in compliance with the benchmarked procedures from Kamarian et al. (2024). Figure 4 shows the key elements of the UTM used in this study.

Figure 4.

Universal testing machine (UTM), highlighting its main components.

Compression testing setup

Before testing, every sample was positioned properly in the UTM to guarantee uniform loading conditions. As seen in Figure 5, (a) compressive force was applied along the height of the beams perpendicular to their face sheets. This setup ensures uniformity across all testing. In order to assess the samples’ deformation and failure properties, the compression test was conducted under quasi-static loading conditions.

Figure 5.

Sandwich beam under compression testing.

Data collection

After compression testing was finished, force-displacement data in TXT format, which contained important characteristics like load, elongation, displacement, stress, and strain, was extracted using the Laryee MaxText software. Microsoft Excel was then used to plot the stress-strain curves in order to examine the mechanical behavior.

Each of the nine unique parameter combinations was printed twice, resulting in 18 total specimens. The mechanical properties which are, the Compressive Modulus, Yield Strength, Plateau Stress, Resilience, and Toughness, were obtained based on the averaged results of the two identical specimens per parameter combination. Figure 6 shows the final specimens after testing (Table 4).

Figure 6.

Specimens after the compression test.

Table 4.

Taguchi design of experiment.

Sample No.	Build orientation (˚)	Printing speed (mm/s)	Infill density (%)
1	0	30	60
2	0	50	80
3	0	70	100
4	45	30	80
5	45	50	100
6	45	70	60
7	90	30	100
8	90	50	60
9	90	70	80

Results and discussion

Table 5 presents the results of compressive modulus, yield strength, plateau stress, resilience, and toughness for each sample. These values were obtained and calculated from the stress versus strain curves that were acquired from Laryee’s MaxText software.

Table 5.

Results of the compression tests.

Sample no.	Build orientation (˚)	Printing speed (mm/s)	Infill density (%)	Compressive modulus (MPa)	Yield strength (MPa)	Plateau stress (MPa)	Resilience (MPa)	Toughness (MPa)
1	0	30	60	2.113	5.17	4.125	4.756	8.642
2	0	50	80	1.713	5.350	3.936	7.183	11.120
3	0	70	100	1.988	5.100	3.345	5.384	9.964
4	45	30	80	1.579	4.630	4.186	5.570	9.757
5	45	50	100	1.915	4.550	3.828	1.321	5.149
6	45	70	60	1.470	4.810	3.876	7.858	11.734
7	90	30	100	1.716	3.850	3.048	4.227	7.275
8	90	50	60	2.055	5.080	3.911	4.881	8.792
9	90	70	80	1.722	3.040	1.536	2.456	3.992

Desirability function analysis

In this research, the optimal combination of input parameters was predicted and obtained through the application of desirability function analysis (DFA). Compressive modulus, yield strength, plateau stress, resilience, and toughness are the multiple response variables that were examined. The steps to getting the DFA are shown below.

Step 1: Desirability index

The desirability index (DI) for compressive modulus, yield strength, plateau stress, resilience, and toughness was calculated using equation (1) after the compression test data were tabulated. Using the “Larger the better” equation, the DI was calculated for this study based on the finding that each mechanical property performed better at higher values.

D_{i} = {0, {(\frac{\hat{y} - y_{\min}}{y_{\max} - y_{\min}})}^{r} 1, y_{\min} \leq (\frac{\hat{y} \leq y_{\min}}{\hat{y} \leq y_{\max} \hat{y} \geq y_{\min}}), r \geq 0

(1)

The corresponding values for the minimum and maximum in the output response are denoted by the variables $y_{\min}$ and $y_{\max}$ .

Table 6 displays the calculated DI for all the mechanical properties for each specimen. The next step would be to get the value for the composite desirability.

Step 2: Composite desirability and rank

D_{G} = \sqrt[w]{{D 1}^{W 1} * {D 2}^{W 2} \dots \dots \dots . * {D i}^{W i}}

(2)

Table 6.

Desirability index for all samples.

Sample no.	Compressive modulus (MPa)	Yield strength (MPa)	Plateau stress (MPa)	Resilience (MPa)	Toughness (MPa)
1	1.000	0.960	0.988	0.725	0.775
2	0.615	1.000	0.952	0.947	0.960
3	0.898	0.944	0.826	0.788	0.878
4	0.412	0.830	1.000	0.806	0.863
5	0.832	0.809	0.930	0.000	0.387
6	0.000	0.875	0.940	1.000	1.000
7	0.619	0.592	0.755	0.667	0.651
8	0.954	0.940	0.947	0.738	0.787
9	0.626	0.000	0.000	0.417	0.000

Equation (2) is used to calculate the composite desirability for each set of samples by combining the corresponding DI. The variables D_G, D_i, and W_i represent the individual desirability index, weightage, and composite desirability. All of the output responses were given the same weight in this research.

Table 7 shows the calculated composite desirability and rank for all samples after compression. Specimen number 1 got a rank of 1 which should mean that it gives the most optimal and ideal results. Specimen 1 had a build orientation of 0°, printing speed of 30 mm/s, and infill density of 60%.

Table 7.

Composite desirability and rank.

Sample No.	Composite desirability	Rank
1	0.882	1
2	0.881	2
3	0.865	4
4	0.750	5
5	0.000	7
6	0.000	7
7	0.655	6
8	0.868	3
9	0.000	7

Table 8 displays the initial output parameter results acquired experimentally. Terms A, B, and C stand for build orientation, printing speed, and infill density respectively. These terms have 3 levels each.

Step 3: Identify the combination of optimized parameter levels

Table 8.

Results to output parameters for sample No. 2.

Initial Output	Compressive modulus (MPa)	Yield strength (MPa)	Plateau stress (MPa)	Resilience (MPa)	Toughness (MPa)
A₁ B₁ C₁	2.113	5.17	4.125	4.756	8.642

The mean values were obtained by Taguchi analysis using the Minitab 19 Software, and the predicted mean values were obtained by using the “Predict Taguchi Results” feature (Table 9).

Table 9.

Mean and predicted mean values for all samples.

Sample No.	Composite desirability	Mean	Predicted mean
1	0.882	0.882	1.136
2	0.881	0.881	0.912
3	0.865	0.865	0.581
4	0.750	0.750	0.468
5	0.000	0.000	0.247
6	0.000	0.000	0.034
7	0.655	0.655	0.686
8	0.868	0.868	0.584
9	0.000	0.000	0.247

Sample 1 was predicted by the Minitab Software to yield the highest composite desirability index value, at 1.136. To verify that, the Taguchi design of experiment was analyzed on Minitab.

After analyzing the Taguchi (DOE) on Minitab, Table 10 was retrieved. Table 10 shows the means that will yield the best outcomes when all the input parameters are optimized. It can be seen that A₁B₁C₁, which corresponds to the first level of build orientation (0˚), the first level of print speed (30 mm/s), and the first level of infill density (60%), is the ideal parameter setting that produced the best outcomes in terms of the mechanical properties. This is because level 1 yielded the highest value of responses for all the parameters. This can also be verified by analyzing Figure 7 which is the main effects plot for means. This plot was also taken from Minitab when analyzing the Taguchi (DOE). It can be seen that level 1 is the highest point on the graph for all the parameters.

Table 10.

Response for means.

Level	Build orientation (A)	Printing speed (B)	Infill density (C)
1	0.8763	0.7630	0.5847
2	0.2493	0.5810	0.5420
3	0.5057	0.2873	0.5047
Delta	0.6270	0.4757	0.0800
Rank	1	2	3

Figure 7.

Main effects plot for means.

A₁B₁C₁ are the settings of specimen 1. That means it was the best-performing sample, and that indicates that its parameter combination provides the most balanced or optimal settings. This implies that further optimization is not required since an effective combination has already been identified and tested. Figure 8 shows the stress-strain curve for sample 1.

Figure 8.

Stress-strain curve for the most optimal specimen which is sample 1 with build orientation of 0°, printing speed of 30 mm/s, and infill density of 60%.

Sample 1 is presented in Figure 8 alongside its mechanical properties, which are the Compressive Modulus, Yield Strength, Plateau Stress, Resilience, and Toughness. The compressive modulus, which describes the specimen’s stiffness and resistance to deformation, is simply the slope of the curve in the elastic region. The yield strength is the point that separates the elastic region from the plastic region, and it can be found by using the 0.2% offset method. Following this, the plateau stress, which is the average stress maintained over the plateau region. This region represents progressive collapse of cells at relatively constant stress. The resilience of a material is its ability to absorb energy within the elastic region and fully recover. It can be determined by finding the area under the curve in the elastic region. And finally, the toughness, which is the total energy absorbed by the specimen before failure and it can be obtained from the entire area under the stress-strain curve.

Step 4: Analysis of Variance (ANOVA)

To find out which input parameter has the biggest impact on each of the five mechanical properties, analysis of variance (ANOVA) was used. By using the Minitab 19 Software, ANOVA was conducted, and the results are shown in the tables below (Tables 11–15).

Table 11.

ANOVA for compressive modulus.

Source	DF	Contribution	Adj SS	Adj MS	F-value	p-value
Build orientation	2	37.0%	0.1440	0.0720	1.38	0.321
Print speed	2	17.0%	0.0662	0.0331	0.30	0.768
Infill density	2	24.0%	0.0935	0.0468	0.60	0.626
Error	2	22.0%	0.0857	0.04285
Total	8	100.0%	0.38945

Table 12.

ANOVA for yield strength.

Source	DF	Contribution	Adj SS	Adj MS	F-value	p-value
Build orientation	2	50.5%	2.2289	1.1144	3.13	0.242
Print speed	2	16.1%	0.7089	0.3544	1.00	0.501
Infill density	2	17.2%	0.7584	0.3792	1.07	0.484
Error	2	16.2%	0.7117	0.3558
Total	8	100.0%	4.4078

Table 13.

ANOVA for plateau stress.

Source	DF	Contribution	Adj SS	Adj MS	F-value	p-value
Build orientation	2	40.5%	2.2482	1.1241	3.35	0.230
Print speed	2	30.8%	1.7094	0.8547	2.55	0.282
Infill density	2	16.5%	0.9174	0.4587	1.37	0.422
Error	2	12.1%	0.6703	0.3351
Total	8	100.0%	5.5454

Table 14.

ANOVA for resilience.

Source	DF	Contribution	Adj SS	Adj MS	F-value	p-value
Build orientation	2	36.0%	10.1633	5.0817	0.28	0.783
Print speed	2	9.0%	3.3878	1.6939	0.04	0.957
Infill density	2	26.0%	8.4944	4.2472	0.37	0.730
Error	2	29.0%	11.8160	5.9080
Total	8	100.0%	33.8775

Table 15.

ANOVA for toughness.

Source	DF	Contribution	Adj SS	Adj MS	F-value	p-value
Build orientation	2	47.5%	25.7250	12.8625	0.54	0.649
Print speed	2	2.0%	1.0841	0.5420	0.00	0.997
Infill density	2	20.0%	10.8404	5.4202	0.26	0.793
Error	2	30.5%	16.5537	8.2769
Total	8	100.0%	54.2032

According to the ANOVA computations, build orientation continuously makes the largest contribution to the mechanical properties across all tables, with contributions ranging from 36.0% to 50.5%. The infill density, which contributes 16.5% to 26.0%, comes next. Print speed also has an impact, ranging from 2.0% to 30.8%. With a range of 12.1% to 30.5%, error is the least significant contribution.

In literature, the effect of build orientation on the mechanical characteristics of 3D printed structures during the printing process has been thoroughly studied. Build orientation is known to have a major impact on the mechanical behavior of 3D printed parts, as many studies have shown. This is especially true for structures where the alignment of material layers affects the overall structural integrity and load-bearing capacity, such as sandwich beams and lattice structures. Orientation affects the inner material structure, and how layers are linked, also affecting stiffness, strength, and performance under compression. For example, it has been demonstrated through research on sandwich panels and lattice structures that build orientation is crucial in defining the mechanical properties such as strength and stiffness. According to several reports, the most important factor influencing compression behavior is build orientation. Other printing parameters, like the layer height and infill density, should also be considered because they also have a significant impact on the overall structural performance. This research finds that the compression behavior of sandwich beams with chiral core topology is highly affected by build orientation. This finding is consistent with previous research showing that build orientation has a significant impact on 3D printed structures’ mechanical performance.

Conclusions

This work aimed to determine the best and most optimal 3D printing parameters to analyze the compression behavior of 3D printed sandwich beams with chiral core topology. To do this, a thorough assessment of the literature was done. Finding out how different build orientations, printing speeds, and infill densities affected the mechanical properties of the specimens was the main goal. Using a Taguchi design of experiments, nine distinct parameter combinations were used, and from them, nine unique samples were 3D printed twice, resulting in a total of eighteen samples. However, the average results of each pair of the same specimen were taken. The CREALITY CR-M4 3D printer, which utilizes the fused deposition modeling (FDM) technology, was used to complete the 3D printing process. PLA was the material that was used to 3D print the specimens. Furthermore, by using the UTM, compression tests were performed on the samples, and the stress versus strain curves were then plotted on Excel after being extracted from the MaxText by Laryee program. Compressive Modulus, Yield Strength, Plateau Stress, Resilience, and Toughness, were among the mechanical characteristics of the samples that were determined using the stress versus strain curves that were done on Excel.

The findings showed that build orientation, which contributed between 36.0% and 50.5% across various mechanical parameters, had the biggest effect on compression performance. Infill density was the second biggest influencing parameter, contributing around 16.5% to 26.0%, and lastly, print speed, which varied between 2.0% and 30.8%. Because build orientation affects the internal layer arrangement and load distribution within the structure, the results validate that it has a significant impact on mechanical behavior, especially stiffness and strength. These results are consistent with previous research that highlights how build orientation affects the mechanical characteristics of 3D-printed structures.

Footnotes

ORCID iD

Salman Pervaiz

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

Data will be made available from the corresponding author upon request.*

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Sample No.	Build orientation (˚)	Printing speed (mm/s)	Infill density (%)
1	0	30	60
2	0	50	80
3	0	70	100
4	45	30	80
5	45	50	100
6	45	70	60
7	90	30	100
8	90	50	60
9	90	70	80

Sample No.	Build orientation (˚)	Printing speed (mm/s)	Infill density (%)
1	0	30	60
2	0	50	80
3	0	70	100
4	45	30	80
5	45	50	100
6	45	70	60
7	90	30	100
8	90	50	60
9	90	70	80

Sample No.	Build orientation (˚)	Printing speed (mm/s)	Infill density (%)
1	0	30	60
2	0	50	80
3	0	70	100
4	45	30	80
5	45	50	100
6	45	70	60
7	90	30	100
8	90	50	60
9	90	70	80