materials

Article Optimization of the 3D Printing Parameters for Tensile Properties of Specimens Produced by Fused Filament Fabrication of 17-4PH Stainless Steel

Damir Godec 1,* , Santiago Cano 2 , Clemens Holzer 2 and Joamin Gonzalez-Gutierrez 2

1 Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb (UNIZAG FSB), 10000 Zagreb, Croatia 2 Polymer Processing, Montanuniversitaet Leoben, 8700 Leoben, Austria; [email protected] (S.C.); [email protected] (C.H.); [email protected] (J.G.-G.) * Correspondence: [email protected]; Tel.: +385-1-6168-192



Received: 21 January 2020; Accepted: 5 February 2020; Published: 8 February 2020


Abstract: Fused filament fabrication (FFF) combined with debinding and sintering could be an economical process for three-dimensional (3D) printing of metal parts. In this paper, compounding, filament making, and FFF processing of feedstock material with 55% vol. of 17-4PH stainless steel powder in a multicomponent binder system are presented. The experimental part of the paper encompasses central composite design for optimization of the most significant 3D printing parameters (extrusion temperature, flow rate multiplier, and layer thickness) to obtain maximum tensile strength of the 3D-printed specimens. Here, only green specimens were examined in order to be able to determine the optimal parameters for 3D printing. The results show that the factor with the biggest influence on the tensile properties was flow rate multiplier, followed by the layer thickness and finally the extrusion temperature. Maximizing all three parameters led to the highest tensile properties of the green parts.

Keywords: additive manufacturing; fused filament fabrication; stainless steel 17-4PH; green parts; tensile properties; central composite design; optimization

1. Introduction Additive manufacturing (AM) comprises a group of technologies used to build physical parts by adding material in a layer-by-layer fashion from a computer-aided design (CAD) file, as opposed to subtractive manufacturing methods, such as machining [1]. AM is the term standardized by ISO and ASTM [2]; however, other common names for AM include three-dimensional (3D) printing, layer-based manufacturing, solid freeform fabrication (SFF), and rapid prototyping (RP) [3,4]. Each of these terms highlights a distinct feature of these processes, for example, 3D printing is a common name used by the general public, whereas the term rapid prototyping derives from the initial use for which the AM technologies were developed. The terms layer-based additive manufacturing and solid freeform fabrication refer to the independence of the geometries that can be produced from the manufacturing process [4]. In this work, the standardized term AM is used. Over the last three decades, many AM technologies were developed for the production of polymeric, metallic, or ceramic parts. Examples of these techniques include vat photopolymerization (VPP), powder bed fusion (PBF), and material extrusion (MEAM). These three techniques were originally developed for the manufacturing of polymeric parts; however, over the years, they were adapted and used for direct and indirect production of metal and ceramic parts [5].

Materials 2020, 13, 774; doi:10.3390/ma13030774 www.mdpi.com/journal/materials Materials 2020, 13, 774 2 of 23

One of the most commonly used AM technologies for the production of metal parts is PBF. In PBF, a laser or electron beam selectively fuses metal powder or metal powder covered with a binding agent by scanning cross-sectional layers generated from a CAD file of the part on the surface of a powder bed. After one cross-section is scanned, the powder bed is lowered and a new layer of powder is added on top of the previous one; the process repeats until the part is finished [6]. One of the biggest disadvantages of PBF is that it relies on high-power lasers or high-energy electron beams, which can be very costly. In addition, the powder must be free-flowing and, therefore, it requires a specific powder distribution, which adds to the price of the material. Therefore, MEAM shows great promise as a cost-effective alternative since the shaping equipment is orders of magnitude cheaper than PBF [6], and powders with a great range of particle size distributions can be processed. In the most common type of MEAM, the building material is supplied in the form of spooled filaments and, therefore, is also known as fused filament fabrication (FFF). In most FFF machines, the filament is fed into a heating unit with a nozzle using counter-rotating rollers as a feeding system. The extrusion head is controlled to move in the XY plane, and, as it moves, material is extruded through the nozzle on a flat platform that moves in the Z-direction [5]. However, there are also MEAM systems, where the extrusion system is fixed and the printing platform moves in three axes [7], and systems where the printed head moves in three axes and the building platform is fixed [8]. FFF was first developed for polymeric materials; however, for the fabrication of metal or ceramic parts, a filament made of a polymeric blend filled with a large portion of metal or ceramic particles, known as feedstock, is used. After shaping the filament into what is referred to as the green parts, the binder system is removed from the part by thermal, catalytic, or solvent extraction and then sintered to obtain a final metal or ceramic part. This process was first introduced as FDMet (Fused Deposition of Metals) and FDC (Fused Deposition of Ceramics) in the 1990s [9,10]; however, since developing appropriate binder systems for metal or ceramic powder is not a trivial task and the FFF process was protected by patents [11–13], FFF for the production of metal or ceramic parts was neglected until recently. Currently, FFF machines are an open-source technology accessible to almost everyone due to their low price; therefore, the interest in producing metallic or ceramic parts via MEAM was rejuvenated and different companies are offering equipment and materials to produce metal and ceramic specimens indirectly after shaping, debinding, and sintering [14–18]. Moreover, several research groups are investigating different materials [19] such as 316 L steel [20–22], 17-4PH steel [23–25], Ti6Al4V [26], NdFeB [27], copper [28], zirconia [29], alumina [30–33], silicon nitride [34,35], lead zirconate titanate [36,37], fused silica [38], tricalcium phosphate [39], hard metals [40–42], cermets [41], and multi-material parts combining ceramics and metals [43]. Most materials that can be used in an FFF machine are melt-processable, i.e., they must flow when heated without applying large shear. Conventional FFF machines are basically ram extruders, with the ram being the printing material in the shape of a filament. Therefore, sufficient stiffness is required for the filament to push the material without buckling into the liquefier and through the nozzle. At the same time, the filament must be strong enough to avoid breaking due to cutting by the wheels [44]. In addition to these requirements, the filament should also be flexible enough so that it can be spooled, such that the filament can be easily stored in a compact place and fed in a more or less continuous fashion into the liquefier with very simple mechanisms [27]. Many unfilled or lightly filled thermoplastics fit all these mechanical requirements. However, when the polymers are filled with 45% vol. or more, as is the case with feedstocks, the filaments become very brittle and their melt viscosity increases substantially; therefore, the properties required for ram extrusion are not met with a single-component binder. The only way to achieve the appropriate mechanical properties is to use multicomponent polymeric binder systems. As previously mentioned, finding the right combination of polymers is not a simple task due to the contradictory requirements of FFF and, later on, during debinding. Possible binder compositions for sinterable FFF filaments were discussed previously [19,29]. Materials 2020, 13, 774 3 of 23

It was observed that the printing step is crucial in obtaining good mechanical properties of the metal specimens; therefore, it is necessary to find the optimal printing conditions, preferably in a systematic approach. Thus, in this paper, a feedstock formulation consisting of a proprietary binder system [45] and 17-4PH stainless-steel powder was used to shape specimens following a central composite design for optimization, and the tensile properties of the shaped parts were measured after FFF. Several studies are available where the tensile properties of polymeric parts produced by MEAM were investigated. For example, Bayraktar et al. [46], Alafaghani et al. [47], Chacon et al. [48], and Spoerk et al. [49] investigated PLA (Polylactic Acid) parts; Ahn et al. [50], Reddy et al. [51], and Álvarez et al. [52] investigated ABS parts; finally, Spoerk et al. [53] investigated filled polypropylene. However, information of the optimization of the printing conditions to improve the tensile properties of feedstocks to obtain high-quality sintered metallic parts shaped by FFF is not available in the open literature. Such information is crucial in order to extend the applicability of FFF to manufacture uniquely designed or complex load-bearing metallic components that can replace parts made by other manufacturing techniques.

2. Materials and Methods

2.1. Feedstock Filaments Feedstock consisted of a multicomponent binder system and filler particles. The binder system consisted of a mixture of a thermoplastic elastomer (Kraiburg TPE GmbH & Co. KG, Waldkraiburg, Germany) with a grafted polyolefin (Byk-Chemie GmbH, Wesel, Germany). The exact binder composition is confidential. The powder was 17-4PH, gas atomized by Sandvik Osprey Ltd., Neath, UK. The particle size data measured by laser diffraction and the chemical composition as given by the producer are shown in Table1. The particle size distribution is mentioned because it is a factor that greatly determines the FFF processability of the produced feedstocks [54].

Table 1. Particle size data of 17-4PH stainless-steel powder.

Particle Size Distribution D10 (µm) 4.2 D50 (µm) 12.3 D90 (µm) 28.2

Feedstock was prepared in a co-rotating twin-screw extruder (Leistritz ZSE 18 HP-48D, Leistritz Extrusionstechnik GmbH, Nuremberg, Germany). The resulting compound was granulated in a cutting mill (Retsch SM200, Retsch GmbH, Haan, Germany) after it cooled down on air-cooled conveyor belt (Reduction Engineering Scheer, Kent, OH, USA). The feedstock granulates were used to produce filaments in a single-screw extruder (FT-E20T-MP-IS, Dr. Collin GmbH, Ebersberg, Germany) coupled to a Teflon conveyor belt (GAL-25, GEPPERT-BAND GmbH, Jülich, Germany) and a self-developed haul off and winding unit. More details about the process are given elsewhere [24].

2.2. Material Extrusion AM Trials Material extrusion additive manufacturing trials were performed on an Original Prusa i3 MK3 fused filament fabrication machine (Prusa Research, Prague, Czech Republic). Nozzle diameter was 0.4 mm. The printing surface was a replaceable heated steel sheet. The printed parts were dog-bone specimens, as shown in the CAD image in Figure1. The software Cura 3D (Ultimaker BV, Utrecht, The Netherlands) was used to prepare the G-code for printing; the following parameters were kept constant: infill density of 100%, rectilinear fill patterns for all layers, fill (raster) angle of 45◦, speed of printing of 35 mm/s, extrusion width of first layer of 200%, infill overlap of 15%, and printing surface temperature of 100 ◦C. The building orientation is as shown in Figure1, with the broadest dimension against the build platform. Materials 2020, 13, x FOR PEER REVIEW 4 of 24

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Figure 1. Dog-boneFigure 1. Dog-bonespecimen specimen printed printed during during printi printingng trialstrials (all (all dimensions dimensions are in mm).are in mm). 2.3. Design of Experiment (DoE)—Central Composite Design The software Cura 3D (Ultimaker BV, Utrecht, The Netherlands) was used to prepare the G-code The extruder temperature, the flow rate multiplier, and the layer thickness were varied according for printing; tothe the following central composite parameters design for optimization were kept shown constant: in Table2 .infill Central density composite of design 100%, is a design rectilinear fill patterns for allof firstlayers, order fill (2k —where(raster) k isangle a number of 45°, of adjustable speed parameters)of printing extended of 35 withmm/s, additional extrusion trials in width the of first layer of 200%,center infill of the overlap design (mean of 15%, values and of parameters) printing and surface axis for eachtemperature parameter, inof order 100 to °C. be able The to building estimate parameters with models of second order. Central composite design consists of 2k trials on the orientation is peakas shown values of in the Figure observed 1, parameters,with the broadest 2k trials in axes dimension of each parameter, against and the trials build at the platform. center of the design (Figure2). 2.3. Design of Experiment (DoE)—Central Composite Design Table 2. Central composite design for optimization (19 trials; five repetitions in the center).

The extruder temperature, theFactor flow 1: Extrusionrate multFactoriplier, 2: Flowand Rate the layerFactor 3:thickness Layer were varied Trial Number according to the central composite designTemperature for (◦ C)optimizationMultiplier shown (◦C) inThickness Table (mm)2. Central composite design is a design of first 1order (2k—where 220 k is a number 120of adjustable parameters) 0.25 extended with 2 235 110 0.12 additional trials in the center3 of the design 220(mean values of 101parameters) and 0.15axis for each parameter, in order to be able to estimate4 parameters 250 with models of 101second order. Central 0.15 composite design 5 260 110 0.20 consists of 2k trials on the peak6 values of the 235 observed parameters, 110 2k trials in 0.28 axes of each parameter, 7 210 110 0.20 and trials at the center of the8 design (Figure 220 2). 120 0.15 9 250 101 0.25 Table 2. Central composite10 design for 235 optimization (19 trials; 95 five repetitions 0.20 in the center). 11 235 110 0.20 12 235 110 0.20 Factor 1: Factor 2: Factor 3: Trial 13 235 127 0.20 Extrusion14 Temperature 235 Flow Rate 110 Multiplier Layer 0.20 Thickness Number 15 235 110 0.20 16(°C) 250(°C) 120 0.25 (mm) 17 235 110 0.20 1 18220 250 120 120 0.15 0.25 2 19235 220 110 101 0.25 0.12 3 220 101 0.15 4 250 101 0.15 5 260 110 0.20 6 235 110 0.28 7 210 110 0.20 8 220 120 0.15 9 250 101 0.25 10 235 95 0.20 11 235 110 0.20 12 235 110 0.20 13 235 127 0.20 14 235 110 0.20 15 235 110 0.20 16 250 120 0.25 17 235 110 0.20 18 250 120 0.15

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19 220 101 0.25

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Figure 2. Figure 2. ModelModel of central of central composite composite design design with with three three factors factors [55]. [55]. The desired characteristic of each DoE is the independent estimation of the main factors and Thetheir desired interactions, characteristic which is a of function each ofDoE the rotatabilityis the independent of the design. estimation The rotatability of the of the main design factors is and their interactions,accomplished which by adding is a function trials so that of all the design rotatability trials (parameters of the design. values) areThe equally rotatability distant fromof the the design is accomplishedcenter of by the adding design (mean trials values so that of parameters).all design Intrials other (parameters words, a design values) is rotatable are ifequally it predicts distant the from values of the parameters with the same precision at all points equidistant from the coded origin of the the center of the design (mean values of parameters). In other words, a design is rotatable if it predicts design [56]. A design is rotatable if the following relationship exists [55]: the values of the parameters with the same precision at all points equidistant from the coded origin 4 of the design [56]. A design is rotatable if the followingα = √F relationship exists [55]: (1)

where α is the distance of a trial in the design axis𝛼= from√ the𝐹 center of the design (Figure2), and F is the (1) number of parameters. where α is theIn thedistance case of of central a trial composite in the design design withaxis threefrom adjustable the center parameters, of the designF is equal (Figure to 8 (22),3); and F is the numbertherefore, of parameters. the α value is 1.68. Therefore, design factors in coded form can be presented as 1.68, 1, 0, − − In the1, and case 1.68. of Total central numbers composite of trials indesign that case with have three to be adjustable 14 trials on designparameters, peaks and F atis axisequal and to 8 (23); therefore,trials the in α the value design is center,1.68. Therefore, where the design design has fact repetitionsors in coded for estimation form can of the be model presented error. as −1.68, −1, 0, 1, and 1.68. TotalThe determination numbers of of trials the limits in that of the case design have of experiment to be 14 trials (DoE) on was design previously peaks discussed and at in axis and Reference [40]. Five specimens per set of printing conditions were fabricated at a time. A total of trials in 95the parts design were center, produced where (Table the2). Afterdesign the ha optimals repetitions conditions for were estimation found, further of the specimens model wereerror. Thereprinted determination with the optimizedof the limits conditions of the to design prove the ofresults experiment of the DoE. (DoE) was previously discussed in Reference [40]. Five specimens per set of printing conditions were fabricated at a time. A total of 95 2.4. Tensile Testing parts were produced (Table 2). After the optimal conditions were found, further specimens were reprinted withTensile the testingoptimized of 3D-printed conditions specimens to prove was the performed results of on the a static DoE. material testing machine Shimadzu AGS-X 10 kN fitted with an extensometer (Shimadzu Corporation, Kyoto, Japan) (Figure3). Tensile strength (N/mm2), maximal tensile force (N), and tensile modulus (N/mm2) were used as 2.4. Tensile Testing characterization parameters for the mechanical tensile properties of specimens. Additionally, the mass Tensileof the testing test specimens of 3D-printed was measured specimens in order towas relate pe itrformed to the achieved on a mechanicalstatic material properties testing of the machine Shimadzutested AGS-X specimens. 10 kN Specimens fitted with were an tested extensometer with a deformation (Shimadzu speed of Corporation, 2 mm/min. The resultsKyoto, of Japan) tensile (Figure testing of 3D-printed specimens are presented in Table3. 3).

Materials 2020, 13, 774 6 of 23 Materials 2020, 13, x FOR PEER REVIEW 6 of 24

Figure 3.Figure Static 3. Staticmaterial material testing testing machine machine Shimad Shimadzuzu AGS-X AGS-X 10 kN10 kN with with tested tested specimen. specimen.

Table 3. Results of tensile testing of green parts (averages with standard deviations ( SD)). Tensile strength (N/mm2), maximal tensile force (N), and tensile modulus± (N/mm2) were used Tensile Strength Maximal Force Tensile Modulus Trial Number Mass (g) as characterization parametersSD for (N/mm the2) mechanical± SD (N)tensile± propertiesSD (N/ mmof 2specimens.) Additionally, the ± mass of the test specimens1 was 7.67 measured0.51 in order 109.12 to6.77 relate it 194.70to the 29.01achieved mechanical 6.57 properties ± ± ± of the tested specimens.2 Specimens 5.76 0.15 were tested 74.32 with1.88 a deformation 143.97 speed9.55 of 2 mm/min. 5.10 The results ± ± ± 3 4.40 0.20 56.54 2.30 114.75 9.78 4.80 of tensile testing of 3D-printed sp±ecimens are presented± in Table 3. ± 4 5.23 0.23 62.36 2.90 134.16 14.94 4.90 ± ± ± 5 6.78 0.37 90.63 5.19 170.62 29.26 5.70 ± ± ± 6 7.90 0.49 106.61 7.41 201.65 17.02 6.30 2.5. Scanning Electron Microscopy (SEM)± ± ± 7 6.13 0.22 82.17 3.95 185.30 22.08 5.70 ± ± ± 8 6.97 0.26 91.14 3.90 167.77 25.42 5.70 For green specimen structure± analysis on the ±fracture surface, ±the scanning electron microscope 9 5.89 0.33 74.93 4.12 166.99 30.59 5.70 ± ± ± Tescan Vega TS 105136 MM (Tescan 4.82 0.25S.r.o, Brno, 62.58Czech2.98 Republic) 136.08 was used17.87 (Figure 4). 5.10 ± ± ± 11 7.15 0.31 95.37 3.65 173.34 14.94 5.80 ± ± ± 12 7.03 0.33 93.60 5.25 180.41 17.55 5.80 ± ± ± 13 8.47 0.13 124.51 2.31 223.92 12.65 6.70 ± ± ± 14 6.82 0.23 94.14 3.48 188.30 17.11 5.80 ± ± ± 15 6.44 0.41 84.55 5.60 183.01 25.80 5.67 ± ± ± 16 8.32 0.48 116.80 6.95 230.50 21.69 6.70 ± ± ± 17 6.48 0.18 86.79 2.49 167.25 10.40 5.80 ± ± ± 18 7.73 0.24 101.81 2.74 187.32 16.04 5.80 ± ± ± 19 5.18 0.37 65.35 4.75 148.62 11.14 5.43 ± ± ±

2.5. Scanning Electron Microscopy (SEM) For green specimen structure analysis on the fracture surface, the scanning electron microscope Tescan Vega TS 5136 MM (Tescan S.r.o, Brno, Czech Republic) was used (Figure4). The microscope had a magnification range of 15 to one million, with a maximal nominal resolution of 3 nm. SEM images were obtained without surface treatment on the specimen cross-section at break.

Figure 4. Scanning electron microscope Tescan Vega TS 5136 MM.

The microscope had a magnification range of 15 to one million, with a maximal nominal resolution of 3 nm. SEM images were obtained without surface treatment on the specimen cross- section at break.

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Figure 3. Static material testing machine Shimadzu AGS-X 10 kN with tested specimen.

Tensile strength (N/mm2), maximal tensile force (N), and tensile modulus (N/mm2) were used as characterization parameters for the mechanical tensile properties of specimens. Additionally, the mass of the test specimens was measured in order to relate it to the achieved mechanical properties of the tested specimens. Specimens were tested with a deformation speed of 2 mm/min. The results of tensile testing of 3D-printed specimens are presented in Table 3.

2.5. Scanning Electron Microscopy (SEM)

MaterialsFor2020 green, 13, 774specimen structure analysis on the fracture surface, the scanning electron microscope7 of 23 Tescan Vega TS 5136 MM (Tescan S.r.o, Brno, Czech Republic) was used (Figure 4).

Materials 2020, 13, x FOR PEER REVIEW 7 of 24 Figure 4. Scanning electron microscope Tescan Vega TS 5136 MM. 3. Results and DiscussionFigure 4. Scanning electron microscope Tescan Vega TS 5136 MM. 3. ResultsThe microscope and Discussion had a magnification range of 15 to one million, with a maximal nominal 3.1. Fused Filament Fabrication of Specimens resolution of 3 nm. SEM images were obtained without surface treatment on the specimen cross- 3.1. Fused Filament Fabrication of Specimens sectionExamples at break. of printed specimens are shown in Figure 5. It can be seen that varying the printing parametersExamples changed of printed the appearance specimens of are the shown 3D-printed in Figure specimens.5. It can be seen that varying the printing parameters changed the appearance of the 3D-printed specimens.

(a) (c) (e)

(b) (d) (f)

FigureFigure 5.5. Top and side views of specimens printed at didifferentfferent conditionsconditions ofof thethe designdesign ofof experiment (DoE)(DoE) afterafter tensiletensile testing:testing: ((a)) trialtrial 77 (temperature(temperature 210210 ◦°C);C); (b)) trialtrial 55 (temperature(temperature 260260 ◦°C);C); ((cc)) trialtrial 1010 (flow(flow raterate multipliermultiplier 95%);95%); ((dd)) trialtrial 1313 (flow(flow raterate multipliermultiplier 127%);127%); ((ee)) trialtrial 22 (layer(layer thickness. 0.12 mm); ((ff)) trialtrial 66 (layer(layer thickness.thickness. 0.280.28 mm).mm).

ThereThere waswas aa visiblevisible changechange inin thethe appearanceappearance ofof thethe printedprinted specimensspecimens asas thethe temperaturetemperature waswas increasedincreased fromfrom 210210 toto 260260 ◦°C,C, withwith thethe specimensspecimens producedproduced atat higherhigher temperaturetemperature havinghaving aa slightlyslightly smoothersmoother surface on the top of the specimen (Figures (Figure5 a,b).5a,b). The The factor factor with with the the largestlargest eeffectffect inin thethe appearanceappearance ofof specimensspecimens waswas thethe flowflow raterate multipliermultiplier sincesince moremore materialmaterial waswas extrudedextruded resultingresulting inin moremore overlapoverlap betweenbetween thethe strandsstrands asas thethe multipliermultiplier increasedincreased fromfrom 95%95% toto 127%.127%. For example, having aa largerlarger flowflow multipliermultiplier led led to to a a better better adhesion adhesion to to the the perimeter perimeter layers layers (Figure (Figures5c,d). 5c,d). The The change change in the in the appearance of the parts with the different layer thickness values of the DoE is shown in Figures 5e,f, where specimens with a layer thickness of 0.12 and 0.28 mm are shown. Figure 6 shows microscopy images of the specimens produced in trial 13 (Figures 6–c—extrusion temperature 235 °C, flow rate multiplier 127%, and layer thickness 0.2 mm) with the best tensile properties (Table 3) and the filament (Figure 6d).

(a) (b)

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3. Results and Discussion

3.1. Fused Filament Fabrication of Specimens Examples of printed specimens are shown in Figure 5. It can be seen that varying the printing parameters changed the appearance of the 3D-printed specimens.

(a) (c) (e)

(b) (d) (f)

Figure 5. Top and side views of specimens printed at different conditions of the design of experiment (DoE) after tensile testing: (a) trial 7 (temperature 210 °C); (b) trial 5 (temperature 260 °C); (c) trial 10 (flow rate multiplier 95%); (d) trial 13 (flow rate multiplier 127%); (e) trial 2 (layer thickness. 0.12 mm); (f) trial 6 (layer thickness. 0.28 mm).

There was a visible change in the appearance of the printed specimens as the temperature was increased from 210 to 260 °C, with the specimens produced at higher temperature having a slightly smoother surface on the top of the specimen (Figures 5a,b). The factor with the largest effect in the

Materialsappearance2020, 13of, 774specimens was the flow rate multiplier since more material was extruded resulting8 of 23in more overlap between the strands as the multiplier increased from 95% to 127%. For example, having a larger flow multiplier led to a better adhesion to the perimeter layers (Figures 5c,d). The change in appearancethe appearance of the of partsthe parts with with the ditheff erentdifferent layer laye thicknessr thickness values values of the of DoEthe DoE is shown is shown in Figure in Figures5e,f, where5e,f, where specimens specimens with awith layer a layer thickness thickness of 0.12 of and0.12 0.28 and mm0.28 aremm shown. are shown. FigureFigure6 6 shows shows microscopy microscopy images images of of the the specimens specimens produced produced in in trial trial 13 13 (Figure (Figures6a–c—extrusion 6–c—extrusion temperaturetemperature 235235 ◦°C,C, flowflow raterate multipliermultiplier 127%,127%, and layer thicknessthickness 0.2 mm)mm) withwith thethe bestbest tensiletensile propertiesproperties (Table(Table3 )3) and and the the filament filament (Figure (Figure6d). 6d).

Materials 2020, 13, x FOR PEER REVIEW 8 of 24 (a) (b)

(c) (d)

FigureFigure 6.6. Morphology of three-dimensional (3D) printed parts investigatedinvestigated by scanningscanning electronelectron microscopy at different magnifications: (a) 39 ;(b) 300 ;(c) 2300 ;(d) 2400 . microscopy at different magnifications: (a) 39×;× (b) 300×;× (c) 2300×;× (d) 2400×.×

TheThe microscopymicroscopy images images of of the the printed printed specimens specimen shows show the the printed printed layers layers (Figure (Figure6a), which 6a), which were ofwere more of ormore less or constant less constant dimensions. dimensions. In each In of theeach layers of the and layers the filament,and the filament, the steel particles the steel were particles well distributedwere well distributed and joint together and joint by together the polymeric by the binderpolymeric (Figure binder6b–d). (Figures Some pores6b–d). due Some to thepores printing due to strategythe printing (i.e., strategy places where (i.e., places two perimeters where two joinedperimeters or where joined the or infill where started the infill and started jointed) and are jointed) visible inare Figure visible6 a,b,in Figures and they 6a,b, are and marked they are by marked dotted by lines. dotted This lines. alignment This alignment of pores of was pores observed was observed in CT (Computedin CT (Computed Tomography) Tomography) scans of specimensscans of specimens produced byproduced FFF with by other FFF highly with filledother filaments highly filled [21], andfilaments they can [21], lead and to they weaker can lead mechanical to weaker properties mechanical (see Sectionproperties 3.3 ).(see Section 3.3). FurtherFurther magnificationmagnification (Figure (Figures6c,d) 6c,d) revealed revealed that the that particles the particles were held were together held bytogether the polymeric by the binder.polymeric Such binder. network Such morphology network morphology is needed in orderis needed to be in able order to perform to be able the to steps perform of debinding the steps and of sinteringdebinding without and sintering destroying without the shaped destroying parts. the It is shap importanted parts. to mention It is important that the to particle mention distribution that the inparticle the printed distribution specimens in the did printed not change specimens from did that not of thechange filament from (Figure that of6 thec,d). filament (Figures 6c,d).

3.2. Tensile Properties of 3D-Printed Green Parts Table 3 presents results of tensile testing 3D-printed specimens. The results are average values of testing five specimens for each DoE trial with standard deviations.

Table 3. Results of tensile testing of green parts (averages with standard deviations (± SD)).

Trial Tensile Strength ± SD Maximal Force ± Tensile Modulus ± SD Mass (g) Number (N/mm2) SD (N) (N/mm2) 1 7.67 ± 0.51 109.12 ± 6.77 194.70 ± 29.01 6.57 2 5.76 ± 0.15 74.32 ± 1.88 143.97 ± 9.55 5.10 3 4.40 ± 0.20 56.54 ± 2.30 114.75 ± 9.78 4.80 4 5.23 ± 0.23 62.36 ± 2.90 134.16 ± 14.94 4.90 5 6.78 ± 0.37 90.63 ± 5.19 170.62 ± 29.26 5.70 6 7.90 ± 0.49 106.61 ± 7.41 201.65 ± 17.02 6.30 7 6.13 ± 0.22 82.17 ± 3.95 185.30 ± 22.08 5.70 8 6.97 ± 0.26 91.14 ± 3.90 167.77 ± 25.42 5.70 9 5.89 ± 0.33 74.93 ± 4.12 166.99 ± 30.59 5.70 10 4.82 ± 0.25 62.58 ± 2.98 136.08 ± 17.87 5.10 11 7.15 ± 0.31 95.37 ± 3.65 173.34 ± 14.94 5.80 12 7.03 ± 0.33 93.60 ± 5.25 180.41 ± 17.55 5.80 13 8.47 ± 0.13 124.51 ± 2.31 223.92 ± 12.65 6.70 14 6.82 ± 0.23 94.14 ± 3.48 188.30 ± 17.11 5.80 15 6.44 ± 0.41 84.55 ± 5.60 183.01 ± 25.80 5.67

Materials 2020, 13, 774 9 of 23 Materials 2020, 13, x FOR PEER REVIEW 9 of 24

3.2. Tensile Properties16 of 3D-Printed 8.32 ± 0.48 Green Parts 116.80 ± 6.95 230.50 ± 21.69 6.70 17 6.48 ± 0.18 86.79 ± 2.49 167.25 ± 10.40 5.80 Table3 presents18 results 7.73 of tensile± 0.24 testing 3D-printed 101.81 ± 2.74 specimens. 187.32 The results ± 16.04 are average 5.80 values of testing five specimens19 for each5.18 ± DoE0.37 trial with standard 65.35 ± 4.75 deviations. 148.62 ± 11.14 5.43 From Table3, two di fferent DoE trials can be pointed out: trial 3 with the lowest tensile properties,From and Table trial 133, withtwo different the highest DoE tensiletrials can properties. be pointed Figure out: 7trial shows 3 with a tensile the lowest strength–strain tensile properties, and trial 13 with the highest tensile properties. Figure 7 shows a tensile strength–strain (elongation) diagram for representative specimens from both trials: specimens 3_2 and 13_4. A very (elongation) diagram for representative specimens from both trials: specimens 3_2 and 13_4. A very big dibigfference difference can can be seen be seen in theirin their tensile tensile behavior, behavior, pointing out out the the importance importance of selecting of selecting the correct the correct printingprinting parameters. parameters.

FigureFigure 7. Tensile 7. Tensile strength–strain strength–strain diagram diagram for for strongeststrongest and and weakest weakest specimens: specimens: 3_2 3_2and and13_4. 13_4.

In orderIn order to observeto observe trends trends in in the the properties properties and their their correlation correlation with with adjustable adjustable printing printing parameters,parameters, trials trials 10 (second10 (second worst) worst) and and 16 16 (second (second best) can can also also be be observed observed and and compared compared to the to the best andbest theand worst the worst trials. trials. Central Central composite composite design design with with three three adjustableadjustable parameters parameters was was performed performed at five diatff fiveerent different levels oflevels adjustable of adjustable parameters. parameters In. coded In coded form, form, those those levels levels can can be be presentedpresented as as −1.68,1.68, 1, − − 0 (center−1, 0 of (center design), of 1,design), and 1.68 1, and asdescribed 1.68 as described in Section in Section2.4. Table 2.4.4 Tablepresents 4 presents a combination a combination of adjustable of adjustable parameters in coded form for selected trials (3, 10, 13, and 16). parameters in coded form for selected trials (3, 10, 13, and 16).

Table 4. Adjustable parameters and their values in coded form (trials 3, 10, 13, and 16). Table 4. Adjustable parameters and their values in coded form (trials 3, 10, 13, and 16). Factor 1: Factor 2: Factor 3: Trial Number Factor 1: Extrusion Factor 2: Flow Rate Trial Number Extrusion Temperature Flow Rate Multiplier LayerFactor Thickness 3: Layer Thickness Temperature Multiplier The worst trials (combinations of parameters in coded form) The worst trials (combinations of parameters in coded form) 3 −1 −1 −1 3 1 1 1 10 −0 −1.68− 0 − 10 0 1.68 0 The best trials (combinations of parameters− in coded form) 13 The best trials0 (combinations of parameters 1.68 in coded form) 0 1316 01 1 1.68 1 0 16 1 1 1 Even before further statistical analysis of the data shown in Tables 3 and 4, one can conclude Eventhat all before parameters further had statistical a significant analysis effect on of the the tensile data properties shown in (the Tables strongest3 and being4, one the can flow conclude rate that allmultiplier) parameters with hadsimilar a significant trends; increasing effect onall theof th tensilee parameters properties increased (the the strongest tensile properties. being the More flow rate detailed analysis is made in Section 3.3. multiplier) with similar trends; increasing all of the parameters increased the tensile properties. More detailed analysis is made in Section 3.3.

3.3. Statistical Analysis of Tensile Testing Results

For statistical analysis of the tensile testing results, the software Design Expert (Stat-Ease Inc., Minneapolis, MN, USA) was used. Central composite design, as a part of response surface methodology, is a statistical technique useful for developing, improving, and optimizing processes. In statistical analysis of the testing results, two tensile properties were examined (tensile strength and tensile Materials 2020, 13, 774 10 of 23 modulus). Analysis of variance (ANOVA) and response surface models were used in order to determine significance of adjustable printing parameters and their interactions on the observed tensile properties. Statistical analysis was also used to determine a mathematical function, which can be used for the prediction of future results for the observed tensile properties.

3.3.1. Statistical Analysis of Tensile Strength Results of ANOVA for tensile strength testing are shown in Table5. The mathematical model of the response surface (quadratic model) for tensile strength (TS) can be presented in the form of Equation (2), where all factors are in coded form as specified in Table5. The equation in terms of coded factors can be used to make predictions about the response for given levels of each factor. By default, the high levels of the factors are coded as +1 and the low levels are coded as 1. The coded equation is − useful for identifying the relative impact of the factors by comparing the factor coefficients.

TS = 6.807 + 0.298 A + 1.333 B + 0.467 C 0.013 AB 0.028 AC 0.027 BC 0.111 A2 0.275 B2 + 0.025 C2. (2) · · · − · − · − · − · − · ·

Table 5. ANOVA for tensile strength testing (quadratic model, DoF—degree of freedom).

Sum of Source DoF Mean Square F-Value p-Value Remark Squares Model 23.56 9 2.62 21.49 <0.0001 Significant A—Extrusion temperature 1.20 1 1.20 9.84 0.0120 Significant B—Flow rate multiplier 18.56 1 18.56 152.31 <0.0001 Significant C—Layer thickness 2.86 1 2.86 23.51 0.0009 Significant AB 0.0015 1 0.0015 0.0119 0.9154 AC 0.0064 1 0.0064 0.0524 0.8241 BC 0.0058 1 0.0058 0.0477 0.8320 A2 0.1682 1 0.1682 1.38 0.2701 B2 0.6866 1 0.6866 5.63 0.0417 Significant C2 0.0072 1 0.0072 0.0592 0.8132 Residual 1.10 9 0.1219 Lack of fit 0.6840 5 0.1368 1.33 0.4038 Not significant Pure Error 0.4127 4 0.1032 Corrected Total 24.66 18

From Table5, it can be concluded that all parameters (i.e., flow rate multiplier, layer thickness, and extrusion temperature) had a strong and significant impact on the tensile strength; increasing the value of these parameters resulted in an increased tensile strength. The flow rate multiplier increased the amount of material being pushed through the nozzle (i.e., the volumetric flow rate), resulting in heavier specimens (Table3), in which the deposited strands were better connected and overlapping; therefore, the amount of voids between strands was reduced. It was determined that voids are the main factor leading to reduced mechanical properties in FFF parts [57]; therefore, reducing voids is very important to improve the mechanical performance. This is especially visible in trials 1, 13, and 16, where this factor was set to higher values (120% and 127%) (Figure8). The results of the DoE are in agreement with studies performed with unfilled PLA and PLA filled with carbon nanotubes, in which the tensile strength increased upon increasing the volume flow rate [49,58]. The flow rate multiplier has a limitation on higher levels, because pushing excessive material through the extruder nozzle can result in nozzle clogging, which can lead to void creation in the fabricated specimens [59]; for this reason, it was limited to 127% in the DoE. Increasing the layer thickness also increased the tensile strength. This was also observed in unfilled PLA specimens, particularly when the raster angle was 45◦ and a flat printing orientation was used [60,61], similar to the conditions used in the present DoE. Increasing the layer thickness is equivalent to decreasing the number of layers and interlayer contacts. The interlayer contacts could be the weakest points of the printed specimens depending on the printing conditions, since there is an incomplete diffusion of polymer chains between adjacent strands, a reduced cross-section due to the introduction of voids, and fracture mechanic-type stress concentrations [43]. Therefore, decreasing the number of interfaces by increasing the layer thickness can increase the strength of the specimens [35]. Materials 2020, 13, 774 11 of 23

Materials 2020, 13, x FOR PEER REVIEW 11 of 24 Layer thickness is also limited due to the 3D printer design; most of the printers for material extrusion incan agreement achieve layer withthicknesses studies performed between with 0.1 and unfilled 0.3 mm PLA [60 ],and which PLA are filled within with the carbon limits ofnanotubes, the DoE used. in whichIt is important the tensile to strength mention increased that, if the upon building increasing orientation, the volume the raster flow rate angle, [49,58]. and the raster width are changed, the trend of the tensile strength, as a function of layer thickness, can be reversed, as reported previously for other materials [49,60,61 ].

(a) (b) (c)

FigureFigure 8. 8. TopTop view view of of specimens specimens from from trials trials with with highest highest values values of of flow flow rate rate multiplier: multiplier: (a ()a trial) trial 1; 1;(b ()b ) trialtrial 13; 13; (c ()c )trial trial 16. 16.

TheThe flow results rate of multiplier the tensile has strength a limitation dependence on higher on the levels, extrusion because temperature pushing are excessive also in agreementmaterial throughwith the the results extruder obtained nozzle for can PLA result [49, 62in– 64nozzle], in whichclogging, an increasewhich can in extrusionlead to void temperature creation in led the to fabricatedhigher tensile specimens strengths. [59]; Thefor this increase reason, in tensileit was limited properties to 127% can be in explained the DoE. by the improved fluidity (decreasingIncreasing viscosity) the layer of thethickness material, also which increased decreases the flowtensile resistance strength. as This it passes was throughalso observed the nozzle. in unfilledWith lower PLA extrusionspecimens, temperature, particularly the when lack the of materialraster angle deposition was 45° results and a inflat bigger printing air gaps,orientation which wasreduce used the [60,61], cross-section similar ofto thethe specimens. conditions Thatused can in the be confirmed present DoE. with Increasing results of specimen the layer massthickness analysis is equivalent(Tables2 and to 3decreasing), where specimens the number printed of layers at higher and temperaturesinterlayer contacts. have higher The interlayer masses even contacts without could the beinteraction the weakest with points flow of rate the multiplier, printed specimens as the parameter depending with on the the strongest printing eff conditions,ect on specimen since massthere and is antensile incomplete properties. diffusion Extrusion of polymer at lower chains temperatures between adjacent also results strands, in a a reduced reduced bonding cross-section between due twoto thedi fferentintroduction layers that of leadsvoids, to lowerand tensilefracture properties. mechanic-type It has tostress be pointed concentrations out that, in this[43]. research, Therefore, only decreasingthe polymer the component number of (45% interfaces vol.) wasby increasing melted during the layer the FFF thickness process; can therefore, increase the the e ffstrengthect of extrusion of the specimenstemperature [35]. on Layer tensile thickness properties is wasalso notlimited as strong due to as the in case3D printer of FFF ofdesign; pure polymermost of the material printers [46 –for53 ]. 2 materialThe extrusion square can of theachieve flow layer rate thicknesses multiplier between (B ) also 0.1 has and a 0.3 significant mm [60], impactwhich are on within the tensile the limitsstrength of the of DoE specimens. used. It is However, important theto mention effect is that, much if the lower building compared orientation, to the the influence raster angle, of all andparameters the raster independently. width are changed, the trend of the tensile strength, as a function of layer thickness, can beThe reversed, influence as reported of the extrusion previously temperature, for other flowmaterials rate multiplier, [49,60,61]. and layer thickness on the tensile strengthThe ofresults fabricated of the parts tensile can bestrength presented dependence in the form ofon two-dimensional the extrusion temperature (2D) graphs (Figuresare also9– 11in). While presenting individual parameter, the other two are maintained at mean values. agreementMaterials 2020 with, 13, x FORthe PEERresults REVIEW obtained for PLA [49,62–64], in which an increase in extrusion12 of 24 temperature led to higher tensile strengths. The increase in tensile properties can be explained by the improved fluidity (decreasing viscosity) of the material, which decreases flow resistance as it passes through the nozzle. With lower extrusion temperature, the lack of material deposition results in bigger air gaps, which reduce the cross-section of the specimens. That can be confirmed with results of specimen mass analysis (Tables 2 and 3), where specimens printed at higher temperatures have higher masses even without the interaction with flow rate multiplier, as the parameter with the strongest effect on specimen mass and tensile properties. Extrusion at lower temperatures also results in a reduced bonding between two different layers that leads to lower tensile properties. It has to be pointed out that, in this research, only the polymer component (45% vol.) was melted during the FFF process; therefore, the effect of extrusion temperature on tensile properties was not as strong as in case of FFF of pure polymer material [46–53]. The square of the flow rate multiplier (B2) also has a significant impact on the tensile strength of specimens. However, the effect is much lower compared to the influence of all parameters independently. The influence of the extrusion temperature, flow rate multiplier, and layer thickness on the tensile strength of fabricated parts can be presented in the form of two-dimensional (2D) graphs Figure 9. Two-dimensional (2D) graph of the influence of extrusion temperature on tensile strength (FiguresFigure 9–11). 9. Two-dimensionalWhile presenting (2D) individual graph of parameter,the influence the of otherextrusion two temperature are maintained on tensile at mean strength values. (flow(flow raterate multipliermultiplier 110%,110%, layerlayer thicknessthickness 0.200.20 mm).mm).

Figure 10. The 2D graph of the influence of flow rate multiplier on tensile strength (extrusion temperature 235 °C, layer thickness 0.20 mm).

Figure 11. The 2D graph of the influence of layer thickness on tensile strength (extrusion temperature 235 °C, flow rate multiplier 110%).

MaterialsMaterials 20202020,, 1313,, xx FORFOR PEERPEER REVIEWREVIEW 1212 ofof 2424

MaterialsFigureFigure2020 ,9.9.13 Two-dimensionalTwo-dimensional, 774 (2D)(2D) graphgraph ofof thethe influenceinfluence ofof extrusionextrusion temperaturetemperature onon tensiletensile strengthstrength12 of 23 (flow(flow raterate multipliermultiplier 110%,110%, layerlayer thicknessthickness 0.200.20 mm).mm).

FigureFigure 10.10. TheTheThe 2D2D 2D graphgraph graph ofof of thethe influenceinfluence influence ofof flow flowflow rate rate multiplier multiplier on on tensile tensile strength strength (extrusion(extrusion temperaturetemperature 235 235 °C,◦°C,C, layer layer thickness thickness 0.20 0.20 mm). mm).

FigureFigure 11. 11. TheThe 2D2D graphgraph ofof thethe influenceinfluence influence ofof layerlayer thicknethickne thicknessssss onon tensiletensile strengthstrength (extrusion(extrusion temperature temperature 235235 °C,◦°C,C, flow flowflow rate rate multiplier multiplier 110%). 110%).

From Figures9–11, it can be concluded that increasing all three observed parameters individually led to an increase in tensile strength. Influence of the flow rate multiplier (Figure 10) was the most significant parameter here, as seen by the steeper slope of the curve. Figures 12–14 show the influence of two parameters on tensile strength simultaneously in the form of 3D graphs, while keeping the third parameter at the maximum value. From Figures 12–14, it can be concluded that the flow rate multiplier had the most significant effect on tensile strength. On Figures 12 and 14, a significant increase in tensile strength can be seen upon increasing the flow rate multiplier in interaction with the extrusion temperature and layer thickness. The interaction of the other two parameters had a slight influence (Figure 13) on tensile strength; thus, the plotted surface area appeared almost flat. Materials 2020, 13, x FOR PEER REVIEW 13 of 24 Materials 2020, 13, x FOR PEER REVIEW 13 of 24 From Figures 9–11, it can be concluded that increasing all three observed parameters From Figures 9–11, it can be concluded that increasingincreasing allall threethree observedobserved parametersparameters individually led to an increase in tensile strength. Influence of the flow rate multiplier (Figure 10) individuallywas the most led significant to an increase parameter in tensile here, asstrength. seen by Influence the steeper of slopethe flow of the rate curve. multiplier (Figure 10) was the most significant parameter here, as seenseen byby thethe steepersteeper slopeslope ofof thethe curve.curve. Figures 12–14 show the influence of two parameters on tensile strength simultaneously in the MaterialsformFigures of2020 3D ,graphs,13 12–14, 774 showwhile thekeeping influence the third of two parameter parameters at the on maximum tensile strength value. simultaneously 13in ofthe 23 formform ofof 3D3D graphs,graphs, whilewhile keepingkeeping thethe thirdthird parameterparameter atat thethe maximummaximum value.value.

Figure 12. The 3D graph of the simultaneous influence of extrusion temperature and flow rate Figure 12.12. TheThe 3D 3D graph graph of theof simultaneousthe simultaneous influence influenc of extrusione of extrusion temperature temperature and flow and rate multiplierflow rate multiplier on tensile strength (layer thickness 0.28 mm). multiplieron tensile strengthon tensile (layer strength thickness (layer 0.28 thickness mm). 0.28 mm).

Figure 13. The 3D graph of the simultaneous influence of extrusion temperature and layer thickness Figure 13. The 3D graph ofof thethe simultaneoussimultaneous influence influence of of extrusion extrusion temperature temperature and and layer layer thickness thickness on tensileon tensile strength strength (flow (flow rate rate multiplier multiplier 127%). 127%). on tensile strength (flow rate multiplier 127%).

Figure 14. The 3D graph of the simultaneous influence of flow rate multiplier and layer thickness on Figure 14. The 3D graph of the simultaneous influence of flow rate multiplier and layer thickness on Figuretensile strength14. The 3D (extrusion graph of temperature the simultaneous 260 C). influence of flow rate multiplier and layer thickness on tensile strength (extrusion temperature 260 ◦°C). tensile strength (extrusion temperature 260 °C). 3.3.2. Statistical Analysis of Tensile Modulus

Results of ANOVA for the tensile modulus testing of printed specimens are shown in Table6.

Materials 2020, 13, 774 14 of 23

Table 6. ANOVA for tensile modulus testing (quadratic model, DoF—degree of freedom).

Sum of Source DoF Mean Square F-Value p-Value Remark Squares Model 14,316.59 9 1590.73 10.11 0.0010 Significant A—Extrusion temperature 355.08 1 355.08 2.26 0.1674 B—Flow rate multiplier 9204.05 1 9204.05 58.47 <0.0001 Significant C—Layer thickness 4001.95 1 4001.95 25.42 0.0007 Significant AB 51.60 1 51.60 0.3278 0.5810 AC 28.91 1 28.91 0.1837 0.6783 BC 1.33 1 1.33 0.0085 0.9288 A2 11.75 1 11.75 0.0747 0.7908 B2 225.21 1 225.21 1.43 0.2622 C2 115.74 1 115.74 0.7352 0.4134 Residual 1416.72 9 157.41 Lack of fit 1143.52 5 228.70 3.35 0.1325 Not significant Pure Error 273.20 4 68.30 Corrected Total 15,733.31 18

The mathematical model of the quadratic response surface for tensile modulus (TM) can be presented in the form of Equation (3), where all factors are in coded form according to Table6.

TM = 179.18 + 5.12 A + 29.69 B + 17.47 C + 2.54 AB + 1.90 AC + 0.408 BC 0.931 A2 4.98 B2 3.12 C2. (3) · · · · · · − · − · − · Here, flow rate multiplier and layer thickness are significant parameters. Figures 15–17 show the individual effect of all three parameters on tensile modulus, while keeping the other two parameters at mean values. As presented in Figures 15–17, increasing both flow rate multiplier and layer thickness led to an increase in tensile modulus (Figure 18), with a stronger effect of the flow rate multiplier (Figure 16). As the tensile modulus describes material behavior in the elastic area and presents a measure of the stiffness of the specimens, it is expected that a specimen printed with higher flow rate multiplier and with larger layer thickness would result in higher density and, as a result, stiffer specimens. Extrusion Materials 2020temperature, 13, x FOR also PEER had REVIEW the same effect (Figure 15); however, in this case, it was not significant. 15 of 24

Figure 15.Figure The 15. 2DThe graph 2D graph of the of theinfluence influence of of extrusion extrusion temperaturetemperature on theon tensilethe tensile modulus modulus (flow rate (flow rate multiplier 110%, layer thickness 0.20 mm). multiplier 110%, layer thickness 0.20 mm).

Figure 16. The 2D graph of the influence of flow rate multiplier on the tensile modulus (extrusion temperature 235 °C, layer thickness 0.20 mm).

Figure 17. The 2D graph of the influence of layer thickness on the tensile modulus (flow rate multiplier 110%, extrusion temperature 235 °C).

Materials 20202020,, 1313,, xx FORFOR PEERPEER REVIEWREVIEW 1515 ofof 2424

MaterialsFigure2020 ,15.13 ,The 774 2D graph of the influence of extrusion temperature on the tensile modulus (flow rate15 of 23 multiplier 110%, layer thickness 0.20 mm).

Figure 16. TheThe 2D 2D graph graph of of the influence influence of flow flow rate multiplier on the tensile modulus (extrusion

temperaturetemperature 235 235 °C,◦°C,C, layerlayer thickness thickness 0.20 0.20 mm). mm).

Materials 2020, 13, x FOR PEER REVIEW 16 of 24

AsFigure presented 17. 17. TheThe 2Din 2D graphFigures graph of of the15–17, the influence influence increasing of of layer layer both thickness thickness flow onrate on the the multiplier tensile tensile modulus modulus and layer (flow (flow thickness rate rate multiplier multiplier led to an increase110%, in extrusion tensile modulus temperature (Figure 235235 ◦°C). 18),C). with a stronger effect of the flow rate multiplier (Figure 16).

FigureFigure 18. SimultaneousSimultaneous effect effect of of flow flow rate rate multiplier multiplier and and layer layer thickness on on the tensile modulus (extrusion(extrusion temperature 260 °C).◦C).

As the tensile modulus describes material behavior in the elastic area and presents a measure of the stiffness of the specimens, it is expected that a specimen printed with higher flow rate multiplier and with larger layer thickness would result in higher density and, as a result, stiffer specimens. Extrusion temperature also had the same effect (Figure 15); however, in this case, it was not significant.

3.4. Statistical Model for Optimization In order to set the FFF parameters for the production of specimens with optimal properties, the criteria for optimization have to be determined (Table 7). Here, complex optimization based on multiple simultaneous criteria was used. The limits of the expected tensile properties, shown in Table 7, were set according to the results obtained from the previous DoE analyzed in Section 3.3.

Table 7. Optimization criteria.

Parameter/Property Goal Lower Limit Upper Limit Importance A: Extrusion temperature Is in range 200 °C 260 °C 3 B: Flow rate multiplier Is in range 90% 130% 3 C: Layer thickness Is in range 0.1 mm 0.3 mm 3 Tensile strength Maximize 8 N/mm2 12 N/mm2 5 Maximum tensile force Maximize 100 N 160 N 5 Tensile modulus Maximize 200 N/mm2 270 N/mm2 5

The mathematical method for finding the optimum of the observed response surface was the desirability function. The desirability function ranges from 0 to 1, where 1 is the goal of the optimization. The numerical results of the complex optimization with the highest desirability function are shown in Table 8.

Table 8. Numerical results of optimization (highest desirability function).

Parameter/Property Goal Unit A: Extrusion temperature 260 °C B: Flow rate multiplier 130 % C: Layer thickness 0.3 mm Tensile strength 9.36 N/mm2 Maximum tensile force 144.31 N

Materials 2020, 13, 774 16 of 23

3.4. Statistical Model for Optimization In order to set the FFF parameters for the production of specimens with optimal properties, the criteria for optimization have to be determined (Table7). Here, complex optimization based on multiple simultaneous criteria was used. The limits of the expected tensile properties, shown in Table7, were set according to the results obtained from the previous DoE analyzed in Section 3.3.

Table 7. Optimization criteria.

Parameter/Property Goal Lower Limit Upper Limit Importance

A: Extrusion temperature Is in range 200 ◦C 260 ◦C 3 B: Flow rate multiplier Is in range 90% 130% 3 C: Layer thickness Is in range 0.1 mm 0.3 mm 3 Tensile strength Maximize 8 N/mm2 12 N/mm2 5 Maximum tensile force Maximize 100 N 160 N 5 Tensile modulus Maximize 200 N/mm2 270 N/mm2 5

The mathematical method for finding the optimum of the observed response surface was the desirability function. The desirability function ranges from 0 to 1, where 1 is the goal of the optimization. The numerical results of the complex optimization with the highest desirability function are shown in Table8.

Table 8. Numerical results of optimization (highest desirability function).

Parameter/Property Goal Unit

A: Extrusion temperature 260 ◦C B: Flow rate multiplier 130 % C: Layer thickness 0.3 mm Tensile strength 9.36 N/mm2 Maximum tensile force 144.31 N Tensile modulus 264.24 N/mm2

A graphical representation of optimized adjustable parameters is shown in Figures 19–21. All three observed FFF parameters (extrusion temperature, flow rate multiplier, and layer thickness) have to be maximized within the previously determined processing window in order to maximize the tensile properties of the green specimens. From Figures 19–21, it is clear that increasing the flow rate multiplier resulted in the highest increase of all observed tensile properties, while extrusion temperature had the lowest effect on the observed properties. As already mentioned, the extrusion temperature only had a strong effect on the polymeric components (i.e., 45% vol. of the feedstock); therefore, its effects on the mechanical properties were generally at a lower level compared to the properties of pure polymeric FFF specimens [49]. For confirming the accuracy of the estimated values of tensile properties, a new set of green specimens was reprinted with the parameters defined in Table8. Figure 22 presents a reprinted specimen with the optimized FFF parameters. Table9 presents the results of tensile testing, as well as variance from the estimated values. Figure 23 presents the tensile strength–strain diagram for the reprinted specimens (opt_1, opt_2 and opt_3), as well as the diagram of the average value (opt_av). All the values of the tensile properties from Table9 show good correlation with the estimated values obtained from the DoE optimization (Table8), which confirms that DoE can be used for the prediction of properties of FFF printed specimens with satisfactory accuracy. Upon using the model obtained by the DoE to set the printing parameters, the tensile strength was improved by 17%, the maximum force was improved by 6%, and the tensile modulus was improved by 23% as compared to trial 13, which originally gave the best results. Materials 2020, 13, x FOR PEER REVIEW 17 of 24

Tensile modulus 264.24 N/mm2 Materials 2020, 13, 774 17 of 23 A graphical representation of optimized adjustable parameters is shown in Figures 19–21.

MaterialsFigure 2020, 13 19., x OptimizedFOR PEER REVIEW extrusion temperature (flow(flow rate multiplier 130%, layer thickness 0.3 mm). 18 of 24

FigureFigure 20.20. Optimized flowflow raterate multipliermultiplier (extrusion(extrusion temperaturetemperature 260260 ◦°C,C, layerlayer thicknessthickness 0.30.3 mm).mm).

Figure 21. Optimized layer thickness (extrusion temperature 260 °C, flow rate multiplier 130%).

Materials 2020, 13, x FOR PEER REVIEW 18 of 24

Materials 2020, 13, 774 18 of 23 Figure 20. Optimized flow rate multiplier (extrusion temperature 260 °C, layer thickness 0.3 mm).

Materials 2020, 13, x FOR PEER REVIEW 19 of 24

All three observed FFF parameters (extrusion temperature, flow rate multiplier, and layer thickness) have to be maximized within the previously determined processing window in order to maximize the tensile properties of the green specimens. From Figures 19–21, it is clear that increasing the flow rate multiplier resulted in the highest increase of all observed tensile properties, while extrusion temperature had the lowest effect on the observed properties. As already mentioned, the extrusion temperature only had a strong effect on the polymeric components (i.e., 45% vol. of the feedstock); therefore, its effects on the mechanical properties were generally at a lower level compared to the properties of pure polymeric FFF specimens [49]. For confirming the accuracy of the estimated values of tensile properties, a new set of green specimens was reprinted with the parameters defined in Table 8. Figure 22 presents a reprinted specimen with the optimized FFF parameters.

Figure 21. Optimized layer thickness (extrusion temperaturetemperature 260 ◦°C,C, flowflow rate multiplier 130%).

FigureFigure 22. 22. SpecimenSpecimen reprinted reprinted with with optimized optimized fused fused filame filamentnt fabrication fabrication (FFF) (FFF) parameters parameters (extrusion (extrusion temperaturetemperature 260 260 °C,◦C, flow flow rate rate multiplier multiplier 130%, 130%, layer layer thickness thickness 0.30 0.30 mm). mm). Table 9. Tensile properties of the reprinted green specimens. Table 9 presents the results of tensile testing, as well as variance from the estimated values. Property Value sd Unit Variance from Estimated Figure 23 presents the tensile strength–strain± diagram for the reprinted specimens (opt_1, opt_2 and Tensile strength 9.95 0.27 N/mm2 +6.3 opt_3), as well as the diagram of the average± value (opt_av). Maximum tensile force 132.27 2.86 N 8.3 ± − Tensile modulus 275.14 6.22 N/mm2 +4.1 ±

Materials 2020, 13, x FOR PEER REVIEW 20 of 24

Table 9. Tensile properties of the reprinted green specimens.

Property Value ± sd Unit Variance from Estimated Tensile strength 9.95 ± 0.27 N/mm2 +6.3 Maximum tensile 132.27 ± 2.86 N −8.3 force Materials 2020, 13, 774 19 of 23 Tensile modulus 275.14 ± 6.22 N/mm2 +4.1

FigureFigure 23. 23. TensileTensile strength–strain strength–strain diagram diagram for for reprinted reprinted (optimized) (optimized) specimens.

4. Conclusions and Future Work All the values of the tensile properties from Table 9 show good correlation with the estimated valuesIn obtained the paper, from the etheffects DoE of threeoptimization FFF parameters (Table 8), (extrusion which confirms temperature, that DoE flow can rate be multiplier, used for andthe predictionlayer thickness) of properties on the tensile of FFF propertiesprinted specimens (tensile strength with satisfactory and tensile accuracy. modulus) Upon of the using stainless-steel the model obtained(17-4PH)–polymer by the DoE composite to set the dog-bone printing specimensparameters were, the presented.tensile strength For analyzing was improved the eff byects, 17%, central the maximumcomposite force design was with improved three parameters by 6%, and was the used.tensile Emodulusffects of allwas selected improved FFF by parameters 23% as compared showed tothe trial same 13, trend;which originally increasing gave the mentionedthe best results. parameters resulted in increased tensile properties of the green specimens. Flow rate multiplier had the strongest effect on tensile properties since more 4.material Conclusions was pushed and Future through Work the nozzle, resulting in more compact specimens in which the deposited strandsIn the were paper, better the connected effects of and three overlapping, FFF parameters leading (extrusion to a reduction temperature, of voids betweenflow rate strands. multiplier, The andinterlayer layer thickness) contacts could on the be tensile the weakest properties points (tensi of thele strength printed and specimens tensile dependingmodulus) of on the the stainless- printing steelconditions, (17-4PH)–polymer since there wascomposite an incomplete dog-bone di ffspecimensusion of polymer were presented. chains between For analyzing adjacent the strands, effects, a centralreduced composite cross-section design due towith the introductionthree parameters of voids, was and used. fracture Effects mechanic-type of all selected stress FFF concentrations. parameters showedTherefore, the decreasing same trend; the increasing number of the layers mentioned (increasing parameters the layer resulted thickness) in increased resulted in tensile green properties specimens ofwith the largergreen tensilespecimens. properties. Flow rate A multiplier lower extrusion had the temperature strongest effect interfered on tensile with properties material since deposition, more materialresulting was in more pushed air gaps through and reduced the nozzle, minimal resulting cross-section in more of thecompact specimens specimens and, therefore, in which lower the depositedtensile properties. strands were Extrusion better atconnected lower temperatures and overlapping, also negatively leading to a ffaected reduction the bond of voids between between two strands.different The layers, interlayer which ledcontacts to lower could tensile be the properties. weakest points In this of research, the printed only specimens the polymer depending components on the(45% printing vol.) were conditions, melted since during there FFF was process; an incomplete therefore, diffusion the effect of of polymer extrusion chains temperature between on adjacent tensile strands,properties a reduced was not cross-section as strong as in due the to case the of introduc FFF of puretion of polymer voids, and materials. fracture mechanic-type stress concentrations.The results Therefore, of this analysis decreasing can be the used number in future of researchlayers (increasing for comparison the layer with thickness) properties resulted of final inparts green obtained specimens after greenwith larger parts undergotensile properties debinding. A and lower sintering. extrusion This temperature comparison interfered will show ifwith the materialsame trend deposition, between tensileresulting properties in more obtained air gaps afterand FFFreduced and afterminimal sintering cross-section are present, of the and specimens if the level and,of the therefore, effect of tensilelower tensile properties properties. obtained Extrusion after the at FFF lower process temperatures holds after also the negatively specimens affected are sintered. the bond between two different layers, which led to lower tensile properties. In this research, only the Author Contributions: Conceptualisation, J.G.-G. and D.G.; methodology, D.G.; software, D.G., validation, J.G.-G. and C.H., investigation, D.G., J.G.-G. and S.C., writing-original draft preparation, D.G. and J.G.-G., writing—review and editing, D.G., J.G.-G. and S.C., supervision, C.H., funding acquisition, D.G. All authors have read and agreed to the published version of the manuscript. Funding: This research and the APC were funded by European Union’s Horizon 2020 Research and Innovation Program (Grant agreement No. 810708), which allowed the collaboration between Croatian and Austrian researchers. The authors also acknowledge the financial support of the Austrian Promotion Agency (Project No. 860385). Conflicts of Interest: The authors declare no conflict of interest. Materials 2020, 13, 774 20 of 23

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