Materials and Design 86 (2015) 902912

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Materials and Design

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Mechanical properties of parts fabricatedwith inkjet 3D printing throughefficient experimental design

J. Mueller a,, K. Shea a, C. Daraio ba Engineering Design and Computing Laboratory, Department of Mechanical and Process Engineering, ETH Zurich, 8092 Zurich, Switzerlandb Materials by Design and Nonlinear Dynamics, Department of Mechanical and Process Engineering, ETH Zurich, 8092 Zurich, Switzerland

Corresponding author.E-mail addresses: jm@ethz.ch (J. Mueller), kshea@ethz

(C. Daraio).

http://dx.doi.org/10.1016/j.matdes.2015.07.1290264-1275/ 2015 Elsevier Ltd. All rights reserved.

a b s t r a c t

a r t i c l e i n f o

Article history:Received 22 March 2015Received in revised form 21 July 2015Accepted 23 July 2015Available online 30 July 2015

Keywords:Additive manufacturingDesign of experimentsInkjet 3D printingMechanical propertiesProcess characterization

To design and optimize parts for additive manufacturing (AM) processes it is necessary to understand their var-iations in geometric and mechanical properties. In this work, such variations of inkjet 3D printed structures aresystematically investigated by analyzing parameters of the whole process. The aim is to determine and quantifythe parameters that lead to themost accurate geometry and to the best mechanical properties. Using this under-standing, it is possible to build accurate partmodels and optimize, fabricate and test themsuccessfully. Significantimpacts on the mechanical properties are found, in descending order, for the number of intersections betweenlayers and nozzles orthogonal to the load-direction, the exposure time to ultraviolet light, the position on theprinting table and the expiry date of the raw material. Nozzle blockage significantly affects the geometry andalso themachine's warm-up time is an important factor. Minor effects are found for the storage time and the sur-face roughness is not affected by any factor. Since AMmaterials change rapidly and the characterization processwill have to be repeated, it is shown how to fully exploit the Design of Experiments method to create a cost andtime efficient design with a high statistical accuracy.

2015 Elsevier Ltd. All rights reserved.

1. Introduction

In contrast to some conventional manufacturing processes, AdditiveManufacturing (AM) part properties can depend on structural and pro-cess parameters rather than purely on material properties. Complex in-teraction effects are created yielding highly anisotropicmaterials wherethe anisotropy often varies both locally within parts and globally be-tween apparently identical parts. Designers cannot rely on values fromstatic material databases anymore making the material selection pro-cess dynamic and complex. This is one of the main issues designersface when creating optimized mechanical structures fabricated withAM.

Further, continuing progress due to large amounts of moneyinvested in AM research [1] pushes the boundaries of printable designs[2,3], and creates diverse printing processes and materials. Additionalprocess parameters are introduced and suppliers are improving theirmaterial formulations [1], highlighting the need for a sophisticatedand efficient test method. To put this into context, a Design for AdditiveManufacturing (DfAM) product design cycle, e.g. for designing a cus-tomized helmet, is presented in Fig. 1. It starts with the AM characteri-zation, the subject of this paper, which also determines the printabilityof the parts and features. Quantitative and simulation models are built

.ch (K. Shea), daraio@ethz.ch

based on the testing for use in optimization [4,5]. To improve the qualityof the models, the materialprocessstructure interactions are part ofthe iterative process and a crucial first step to capitalize on the uniquecapabilities of AM processes. Shown in white background color is theconventional process.

Design of Experiments (DoE) is an efficient and established testmethod and commonly used in industry and research [6]. However, itscorrect application is not as trivial as commercially available softwareoften suggests and not always found in published work [79]. A correctapplication is crucial for both obtaining accurate and repeatable results,as well as keeping the experimental cost low.

On the fabrication side, systematic testing of metal AM processes isstandardized [10] and many processes have been characterized [11].This is not the case for polymer-based processes,where a larger variabil-ity of technologies exists [12], making it harder to build a universallyvalid standard. One of the most advanced printers in the polymer fieldis the Stratasys Objet500 Connex3 [13], which uses inkjet 3D printingtechnology. While printers based on that technology have been investi-gated before [6,1418], there is no characterization of the Connex3available, which is more advanced in the technology and offers noveland unique features such as the capability of printing the highest num-ber of differentmodelmaterials [13,19]. Further, thematerial propertiesthemanufacturers provide vary over 40% [19] and little is known aboutthe impact of the process and material on structural performance.

For those reasons, in this article i) an efficient way of collecting rele-vant data with DoE is demonstrated and ii) the complete process of

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Fig. 1. DfAMmethodology for customized products.

1 The directions are defined according to the ASTM F2792-12a standard [43].

903J. Mueller et al. / Materials and Design 86 (2015) 902912

inkjet 3D printing is extensively analyzed, ranging from the characteris-tics of the raw material over the printing process to the storage of thefinal part, with a focus on tensile properties. An initial study on thistopic was published in [20].

The paper is organized as follows. First, the previous work examin-ing the process capability of inkjet 3D printing is elaborated in thefollowing section. It is followed by the experimental methods, whichdescribe the statistical design, the investigated parameters and the ex-perimental and metrological set-up. Then, the results are presentedand discussed based on how to ideally set the parameters to achievethe best possible results for designing parts within the constraints ofthis AM technology.

2. Background

2.1. Design of experiments

In contrast to the classic one-factor-at-a-time (OFAT) approach[21,22], where factors are investigated one-by-one, DoE makes use ofstatistics [2224]. The levels of multiple factors are changed at thesame time to reach higher efficiency [25]. Factors are defined as inputparameters and levels as their associated settings. For the experiments,DoE provides a table outlining the run order of the experimentswith therespective configuration of the factors. All known factors which are notpart of the DoE should be kept constant throughout the tests [22].Through randomization [26] of the run order, the DoE can compensatefor the influence of uncontrollable and unknown factors (randomerror sources) and hence achieve higher statistical accuracies comparedto conventional methods [27]. If a factor is of interest, but hard tochange, blocks can be integrated [21]. The factors are then randomizedonly within the blocks [22].

Analysis of Variance (ANOVA) is used to analyze the results by calcu-lating themeans of each level for each factor [22,28]. The difference be-tween the means is called (main) effect and reflects the impact on theoutput of the experiment [29]. By comparing the means of multiplelevel-factor combinations, interaction effects can be found [30]. For in-stance, a two-factor interaction effect indicates that a response of factor1 is significant only when factor 2 is set at a certain level or vice versa.Since main effects are included in interaction effects, interaction effectsare of higher importance and the same is true comparing low order tohigh order interaction effects [31]. By comparing the variance of the ef-fects to the variance of the residuals, the statistical significance is calcu-lated. The ANOVA table provides this information in the form variancewithin groups (residual mean square, MSres) and variance betweenthe compared groups (treatment mean square, MStreat) [32]. The meansquare is the ratio of the sumof squares (SSres, SStreat) and their adjacentdegrees of freedom (df). The F ratio shows a potential impact of thetreatment groups for F N 1 and is calculated with MSres/MStreat. Fromthe F value, the p value is obtained, which indicates whether an effectis significant or not [22].

Normally little insight into the process is available, hence it is in thenature of such analyses that not all investigated factors are of relevance,

which iswhy it is common to initially perform a screening design [22]. Ascreening design gives a rough overviewwith a poor statistical accuracy[33]. In the next step, a newdesign is created only for the significant fac-tors found and the experiments are repeated. To decrease the overallnumber of tests, we show how to skip the screening design by makingreasonable assumptions while maintaining high statistical accuracy.

2.2. Inkjet 3D printing

In inkjet 3D printing [34], a liquidized photo-polymer is heated toabout 73 C, jetted onto a surface and instantly cured with UV light.Most commercial printers contain at least two print heads similar tothe ones in conventional printing, one for the support material andone for the model material [35]. Additional print heads can be addedfor higher material throughput or to print multiple materials [36],which is one major advantage of the process [37]. Each print head con-sists of numerous, linearly aligned nozzles. Thin layers of curedmaterialpile up while the build tray moves down until the part is finished [35].

An early examination of the influence of part orientation on me-chanical strength and hardness of parts printed on an Objet Eden 260was conducted by Kesy and Kotlinski [15]. For transverse orientationsin the XZ-plane, the parts demonstrated a yield point, whereas forparts laying in the XY-plane, brittle rupture was dominant and a re-duced mechanical strength was observed, an effect they attributed todifferent UV exposure times. The geometric accuracy of parts printedon the same model was investigated by Singh [14]. Blanco, Fernandezand Noriega [38] looked into the effect of part orientation on the relax-ation modulus of parts printed in an Objet30 desktop printer. Scalefactors, which needed to be accounted for manually on older modelslike the Objet Eden 330, were optimized by Brajlih, Drstvensek, Kovacicand Balic [16]. Pilipovi, Raos and Sercer [39] investigated themechanicalproperties, dimensions and surface roughnesses of parts printed fromdifferent Vero-materials, similar to the material used in this work. Alsoon the Eden 330, Cazon, Morer and Matey [40] found significant effectsfor the printing orientations. They also found, in agreement with Vieira,Paggi and Salmoria [41], a significant increase of the elasticmodulus dueto over-curing. In another article, Udroiu and Mihail [17] report thatObjet Eden 350's glossy option resulted in smoother surfaces comparedto the mat option. Design rules were derived by Gibson et al. [18], whoinvestigated the application of living hinges printed in the samemodel.

Adamczak, Bochnia and Laczmarska [42] looked into the variance ofparts printed on an Objet350 Connex and showed that under very spe-cific conditions little variance is found. The Objet350 Connex can printup to three discrete materials at a time and was also studied by Barcliftand Williams [6]. Focusing on in-process parameters, they examinedthe influence of the parts' longitudinal alignment on the printing tablealong the X and Y directions,1 the transverse alignment in X, Y and Zdirection and the part spacing for VeroWhite (FullCure 830) material.A significant impact was found only for the latter one, where a tight

Fig. 3. Printing table indicating the specimens' position, orientation and part spacing. Indi-cated are the tested specimen and the two additional specimens which are used for thepart spacings, but discarded after the print.

Fig. 2. DoE process showing the initial (screening) design (Step 1) and the effects ofremoving interaction effects (Step 2) and factors (Step 3).

904 J. Mueller et al. / Materials and Design 86 (2015) 902912

spacing yielded a higher UV exposure time per part and thus a strongermechanical strength. They also pointed out the complexity and interre-lation of impacting factors and demonstrated the need for a systematicapproach.

However, many of these investigations are based on early printermodels and have in common that they do not take into account impor-tant considerations such as factor interaction or over-curing effects.Also, manymore potentially impacting factors than the ones investigat-ed before are available, including the out-of-process parameters. Anindependent and comprehensive analysis has yet to be performed forthe inkjet process and for the Objet500 Connex3 printer, the subject ofthis paper. Compared to the previous models it offers an improved

Table 1Tested factors of the DoEwith their corresponding settings. The unit of the numbers in theupper half is millimeters.

Factor Name Level (low) Level (high)

A Position (X) 41.75 448.25B Position (Y) 41.75 348.25C Longitudinal dir. X YD Transverse dir. X/Y ZE Part spacing (X) 10 343F Part spacing (Y) 10 243

Block G expiry date material

1 20142 2015

technology and allows combination of three different resins to printup to 82 model materials per job [19]. As the Connex3 is one of themost advanced commercially available multi-material printers [13], itis representative for the current state-of-the-art of inkjet 3D printing.Due to continuous improvement of material formulations, there is alsoa new VeroWhite material (VeroWhitePlus (Fullcure 835)) availablewhat is tested and compared in this paper.

3. Materials and methods

In this section, the input factors are defined and the fabricationand experimental analysis shown. Also, the statistical approach of themethod is explained.

3.1. Statistical method

The experimental design is based on the procedure presented inSection 2 and shown in Fig. 2. To increase the accuracy and reduce theeffect of noise, the levels of the factors are chosen in the maximumpossible distance.

Step 1. Main effects are of lower importance than interaction effects andlow-order interaction effects of lower importance than high-order effects. Interaction effects of four factors and above arehighly unlikely [44]. Therefore, a half fractional factorial design,which confounds the effects we are interested in only with suchhigh order effects is used. It provides high statistical accuracy forinteractions up to three factors while reducing the number oftests by 50% compared to a full factorial design, which requiresall the possible combinations of levels and factors to be tested.

Step 2. Insignificant interaction effects i are removed and the ANOVA isrepeated. This step increases the amount of degrees of freedomavailable for the residuals, to which the effects are compared to,and enhances the statistical power of the design.

Step 3. Insignificant factors h are removed from the design and theANOVA is repeated. For h = 1 it yields a full factorial design,which can analyze all possible interaction effects. When analyz-ing all interactions in a full factorial design, however, no degreesof freedom are available for the residuals. It is therefore recom-mended to still waive high order interactions. For h N 1, replica-tions are created, further increasing the statistical accuracy.

For the OFAT experiments, a t-test is conducted, which comparestwo different treatment groups to determinewhether there is a real dif-ference between the means. The t-test also provides a significance level

Fig. 4. A printed sample after removing the support structure. The magnification showsthe layers as visible under a light microscope; the length of the scale bar is 100 m.

905J. Mueller et al. / Materials and Design 86 (2015) 902912

p. A common threshold for the standard significance level of = 0.05[45], indicating that effects with p b are significant, is chosen andused throughout this work.

Fig. 5. Aging effect on elastic modulus (E), ultimate (tensile) strength (u) and total strainat break (u). The symbols depict the means of five tests each, and the error bars thestandard deviation.

3.2. Input factors

Important input factors found in literature are investigated andcomplementedwith additional factors found by analyzing the completeprinting process via the Eight Steps in Additive Manufacturing [12]. Atotal of 12 factors are identified, of which seven are examinedwith DoE.They are summarized in Table 1 and defined as follows.

A, B The positions X and Y of the parts' centers of gravity on the print-ing table, where the low and high levels represent the minimumand maximum reachable coordinates (Fig. 3).

C, D The orientation of the parts' longitudinal and transverse direction(Fig. 3). The longitudinal direction is either X or Y. The transversedirection depends on the longitudinal direction. For a longitudi-nal orientation in X, the low level of the transverse direction isY and vice versa, indicating that the part is aligned horizontallyin the XY plane. The transverse direction in Z is defined as thehigh level.

E, F Part-spacing is an indirect measure of the UV intensity. For eachtest specimen, which is printed in an individual job, two addi-tional specimens are added in both the X and Y direction, butnot part of the analysis (Fig. 3). The minimum and maximumlevels are chosen according to the print table size.

G Two batches with different expiry dates (one year apart, denotedas 2014 and 2015) of the same material type are examined. Theexpiry date represents the approximate, overall serviceable lifeas defined by Stratasys. Changing the material in the printer iscostly, hence blocks are used for this factor.

Table 2Differences between a cold machine with clean nozzles (RT) and i.) a warm machine with c(Warm/not clean) in terms of mechanical and geometric properties.

RTMean (s.d.)

Warm/cleanMean (s.d.)

Length (L0) [mm] 63.43 (0.02) 63.42 (0.02)Width (W0) [mm] 9.51 (0.02) 9.53 (0.02)Width cross section (Wc) [mm] 3.12 (0.02) 3.14 (0.02)Thickness (T) [mm] 3.16 (0.01) 3.16 (0.01)Mass [g] 1.75 (0.01) 1.77 (0.01)Elastic modulus [MPa] 2924 (44) 2922 (76)Ultimate strength [MPa] 67.30 (1.57) 69.03 (1.15)Rupture strain [%] 5.35 (0.34) 5.70 (0.99)Ra (top) [m] 3.37 (0.45) 3.26 (0.46)Rz (top) [m] 16.45 (2.08) 16.09 (2.14)Rmax (top) [m] 20.92 (4.25) 20.73 (2.36)Max. deviation from thickness [m] 26.67 (8.66) 27.78 (8.33)

It is important to learn about the five remaining factors prior toperforming the main DoE test, because they can increase the accuracyand especially efficiency of the following tests. Since the levels ofthose five factors are also costly and/or time-consuming to change andsince there are no interaction effects expected, a DoE analysis, wherethe levels often change after each run, is not necessary. The followingparameters are therefore investigated beforehand using OFAT.

H Longitudinal orientation in Z direction: Due to the slim specimengeometry, a support structure is required for this orientation. Asupport structure could add unwanted effects, which is why thisfactor is investigated separately.

I Warm-up time of the machine: A batch of specimens is printed onthe cold machine and compared to specimens printed on thewarm machine. A random, but for all tests identical job of tenhours is printed in between to warm the machine up.

J Cleanliness of the print heads' nozzles: Reflections of the UV light orother time-dependent effects can cure material on the print headand block the nozzles. Therefore, for the warm state described in(I), it is distinguished between clean and not clean: The print-head

lean nozzles (Warm/clean) and ii.) a warm machine which was printing for about 12 h

t p Warm/not cleanMean (s.d.)

t p

1.35 0.195 63.40 (0.02) 3.37 0.0042.06 0.056 9.50 (0.01) 1.62 0.1373.36 0.007 3.11 (0.01) 1.25 0.2301.11 0.286 2.83 (0.10) 9.64 b0.0016.57 b0.001 1.66 (0.02) 10.35 b0.001

0.08 0.941 2984 (113) 1.48 0.1692.67 0.018 68.13 (2.68) 0.80 0.4381.00 0.342 4.42 (0.44) 5.04 b0.001

0.51 0.614 4.17 (1.36) 1.67 0.1270.36 0.727 18.34 (6.32) 0.86 0.4130.12 0.910 31.49 (13.10) 2.30 0.045

0.28 0.785 231.11 (91.03) 6.71 b0.001

Fig. 6.Aging effect on the specimenmass. The symbols depict themeans of five tests each,the error bars the standard deviation.

906 J. Mueller et al. / Materials and Design 86 (2015) 902912

is either cleaned before the second print job or not. In each job, threeparts are fabricated and three replications are made in randomizedruns.

K Time between printing and testing: To test the effect of aging, aperiod of 21 days is scheduled with decreasing intervals of 21, 17,13, 9, 6, 3, 1 and 0 days before testing. Ten specimens are printedper tray, oriented longitudinally in Y and transversely in theZ-direction. The part spacing is fixed at 10 mm and they are storedin constant conditions.

L Storage in support material: The support material is removed fromfive of the ten parts described in (K). The five remaining parts arestored inside the support material. For the analysis, the means ofeach group are compared pairwise to compare identical settings.

VeroWhitePlus (RGD835) material is used and the remainingmaterial cartridge slots of the printer are filled with TangoBlackPlus,VeroYellow and SUP705. Factors not of interest, but with potentialinfluence on the result, are kept constant. That is, for example, the print-ing mode, support material composition, environmental conditions ofstorage of raw materials and test-specimens, printing and testing.

3.3. Fabrication and removal of support material

All specimens are printed on a Stratasys Objet500 Connex3, whichstands in an air-conditioned room. The printer contains eight parallel

Table 3Full ANOVA table of the mechanical properties. A/B: Position X/Y, C/D: Longitudinal/transverse

Elastic modulus Ultimate (te

Source df Adj SS Adj MS F p Adj SS

Blocks 1 49,905 49,904.80 7.78 0.021 184.45A 1 765 765.30 0.12 0.738 5.15B 1 4407 4407.30 0.69 0.429 5.00C 1 1629 1629.10 0.25 0.626 6.22D 1 9772 9772.10 1.52 0.248 76.34E 1 3315 3314.60 0.52 0.490 2.20F 1 5852 5852.40 0.91 0.364 40.12A*B 1 6599 6599.30 1.03 0.337 0.08A*C 1 13217 13217.10 2.06 0.185 2.22A*D 1 2 2.40 b0.01 0.985 1.81A*E 1 40 39.70 0.01 0.939 9.66A*F 1 155 155.30 0.02 0.880 1.92B*C 1 b1 b0.01 b0.01 1.000 b0.01B*D 1 43 43.00 0.01 0.937 0.32B*E 1 768 767.60 0.12 0.737 1.73B*F 1 2598 2598.30 0.41 0.540 1.36C*D 1 3119 3119.40 0.49 0.503 10.93C*E 1 8482 8481.90 1.32 0.280 0.73C*F 1 328 328.30 0.05 0.826 6.66D*E 1 29 28.90 b0.01 0.948 0.66D*F 1 3212 3211.70 0.50 0.497 0.01E*F 1 29 28.90 b0.01 0.948 0.16Residuals 9 57,708 6412.00 10.64Total 31 17,1975 368.35

print heads, six ofwhich are pairwise allocated to threemodelmaterialsandwork in sync. Each print head consists of 96 nozzles in a linear array,measuring 50 m in diameter [36]. In theory, Stratasys allows a certainamount of nozzles to be blocked. Since blocked nozzles can lead to arough surface, which changes the spreading behavior of the next layers'liquid [46], the print head is thoroughly cleaned before each print. Tohave the same surface finish for all sides, the mat option of the printeris used, covering all surfaces in support material regardless of the actualneed. This also prevents over-curing due to increased UV exposure [38].Unless otherwise stated, the support material is mechanically removedfrom the parts. This procedure, rather than using the high-pressurewater jet process, prevents the absorption of water into the structure,potentially changing the results. Themechanical removal of the supportmaterial also removed the need for adding drying and dehydration timeprior to testing. For specimens on which the surface roughness andwaviness are measured, the effect of water absorption is negligiblecompared to mechanical surface damage, which is why the water jetis used to clean those specimens (Krumm RK 5 XL VA).

3.4. Experimental analysis

The elastic modulus (E), ultimate (tensile) strength (u) and totalstrain at break (u) are measured in accordance to the ASTM D638-10standard [55]. To stay within the vertical travel length of the printerfor the longitudinal alignment in Z, Type IV specimen geometry ischosen and used for all tests for comparability. The measurements aretaken using an Instron ElectroPuls E3000 in combination with aDynacell load cell of 5 kN load capacity with a linearity and repeatabilitybetter than 0.25% in the tested range. A constant testing speed of50 mm/min is used for all tests. Further, a Nikon eclipse LV100microscope with a L Plan 2.5/0.075 lens is used to map the fracturesurface.

The dimensions and surface roughnesses are measured on aMitutoyo Micrometer Series 102 (accuracy of 2 m) and a Perthenperthometer M4P, respectively. For the measurement of the waviness,a standardmicrometer with extra slim grippers is used. AMetler ToledoXS205 DualRange scale (linearity of 0.2 mg, repeatability of 0.01 mg)is used to measure the mass.

dir., E/F: Part spacing X/Y.

nsile) strength Total strain at break

Adj MS F p Adj SS Adj MS F p

184.45 155.97 b0.001 11.67 11.67 19.87 0.0025.15 4.35 0.067 6.95 6.95 11.83 0.0075.00 4.23 0.070 0.83 0.83 1.41 0.2656.22 5.26 0.047 40.68 40.68 69.30 b0.001

76.34 64.55 b0.001 6.17 6.17 10.51 0.0102.20 1.86 0.206 4.53 4.53 7.72 0.021

40.12 33.92 b0.001 0.01 0.01 0.02 0.8800.08 0.07 0.804 0.03 0.03 0.04 0.8392.22 1.88 0.204 7.06 7.06 12.03 0.0071.81 1.53 0.247 1.42 1.42 2.42 0.1549.66 8.17 0.019 0.08 0.08 0.14 0.7141.92 1.62 0.235 0.42 0.41 0.71 0.422

b0.01 b0.01 1.000 b0.01 b0.01 b0.01 1.0000.32 0.27 0.613 b0.01 b0.01 0.01 0.9421.73 1.46 0.257 1.27 1.27 2.16 0.1761.36 1.15 0.312 0.52 0.51 0.88 0.373

10.93 9.24 0.014 8.62 8.62 14.68 0.0040.73 0.62 0.451 7.25 7.25 12.35 0.0076.66 5.63 0.042 0.78 0.78 1.32 0.2800.66 0.56 0.475 10.09 10.09 17.19 0.0020.01 0.01 0.918 0.03 0.03 0.05 0.8340.16 0.13 0.724 0.88 0.88 1.50 0.2511.18 5.28 0.59

114.56

Table 4ANOVA table of ultimate strength effects for the25 full factorial design after takingout B. A:Position X, C/D: Longitudinal/transverse dir., E/F: Part spacing X/Y.

Source df Adj SS Adj MS F p

Blocks 1 184.45 184.45 144.59 b0.001A 1 5.15 5.15 4.04 0.063C 1 6.22 6.22 4.88 0.043D 1 76.34 76.34 59.84 b0.001E 1 2.20 2.20 1.72 0.209F 1 40.12 40.12 31.45 b0.001

A*C 1 2.22 2.22 1.74 0.207A*D 1 1.81 1.81 1.42 0.252A*E 1 9.66 9.66 7.57 0.015A*F 1 1.92 1.92 1.50 0.239C*D 1 10.93 10.93 8.57 0.010C*E 1 0.73 0.73 0.58 0.460C*F 1 6.66 6.66 5.22 0.037D*E 1 0.66 0.66 0.52 0.484D*F 1 0.01 0.01 0.01 0.920E*F 1 0.16 0.16 0.12 0.731Residuals 15 19.13 1.28Total 31 368.35

Table 5ANOVA table for elongation of break, 24 full factorial design with 2 replicates after takingout B and F. A: Position X, C/D: Longitudinal/transverse dir., E: Part spacing X.

Source df Adj SS Adj MS F p

Blocks 1 11.69 11.69 23.25 b0.001A 1 6.94 6.94 13.80 0.001C 1 40.73 40.73 81.00 b0.001D 1 6.18 6.18 12.29 0.002E 1 4.55 4.55 9.04 0.007

A*C 1 7.09 7.09 14.10 0.001A*D 1 1.42 1.42 2.82 0.108A*E 1 0.08 0.08 0.16 0.691C*D 1 8.59 8.59 17.09 0.001C*E 1 7.28 7.28 14.47 0.001D*E 1 10.06 10.06 20.00 b0.001Residuals 20 10.06 0.50Total 31 114.64

907J. Mueller et al. / Materials and Design 86 (2015) 902912

4. Results

Fig. 4 shows a printed sample after removal of the support structurewith clearly visible layers. The results for the factors investigated onsuch samples are presented starting with the OFAT and then the DoEexperiments. All statistical tests conducted in this section are checkedfor model adequacy using histograms, normal probability plots ofresiduals and versus fits of residuals and predicted values [22]. Nothingsignificant is revealed.

4.1. Warm-up time and cleanliness of nozzles

At = 5%, the warming up of the machine has no statistical signifi-cance on all of the properties except on the width of the cross sectionand the mass, for which the difference between the means is 0.64%and 1.14%, respectively (Table 2). However, nozzle blockage is signifi-cant especially for the geometric properties, i.e. the length (0.05%),specimen mass (5.14%), maximum thickness (10.44%), and thus themaximumdeviation from the thickness (766.55%). Of all themechanicalproperties, only the elongation of break is affected (17.38%). Further, itis observed that the standard deviation increases when the nozzlesare not cleaned.

Fig. 7. Interaction effects of the ultimate strength. The legend refers to the second value of thecompared interaction. A: PositionX, C/D: Longitudinal/transverse dir., E/F: Part spacingX/Y. -1 stands for the low and 1 for the high level as given in Table 1.

4.2. Time between printing and testing with different storage conditions

In spite of the small standard deviations, the results do not showclear trends for the elastic modulus and ultimate strength (Fig. 5).However, for the ultimate strength, slightly higher values are ob-served for parts with removed support material. An opposite effectis observed for the elastic modulus. The measured temperature inthe storage room with no UV exposure present averages 21.84 C(0.62) and the humidity 48.73% (1.89). For the fracture strain, theclean storage shows a downward trend with a jump towards theend, decreasing by about 50%.

Increased storage time shows an upward trend in mass (Fig. 6).The maximum means of the mass after 21 days are 1.7602 g for theclean and 1.7818 g for the part stored in the support material. Incomparison with zero storage time, they are around 2.5% higher.Further, it is observed that the discrepancy between parts free ofsupport material and parts inside support material increases withtime. The calculated p values confirm a statistical significance forboth 21 versus 0 days of storage and stored clean versus inside thesupport structure.

4.3. Part position, orientation, spacing and material batch

Due to insignificant three-factor interaction effects for all investigatedoutput factors, they are removed and theANOVA is repeated formain andtwo-factor interaction effects (Table 3).

No significant impacts are found on the elastic modulus for eithermain effects or two-factor interaction effects, even after repeating theANOVA without the insignificant two-factor interaction effects. For theultimate strength, the significant interactions are A*E2 (p = 0.019),C*D (p = 0.014) and C*F (p = 0.042). All factors with significant maineffects are included herein. B is insignificant in both, main and two-factor interaction effects andhence deleted. The resultingANOVA repre-sents a 25 full factorial design. No significant interactions are found forfive-, four- and three-factor interactions, thus the analysis is reducedto two-factor interaction effects providing sufficient degrees of freedomfor the residuals (Table 4).

One can see that, compared to the full ANOVA, the p values arenow smaller for all of the interaction effects: A*E (p = 0.015), C*D(p=0.010) and C*F (p=0.037). As all relevantmain effects are includ-ed, only the interaction effects are shown (Fig. 7). Generally, the lowlevels of A, C, E and F provide higher output values, whereas the oppo-site is valid for D. The strongest effect originates from D, where themean of the vertical transverse alignment is 4.41% higher than the onefor horizontally aligned specimens. In F, the difference between the

2 Interaction effects are denoted by factor1*factor2.

Fig. 8. Interaction effects of total strain at break. The legend refers to the second value ofthe compared interaction. A: Position X, C/D: Longitudinal/transverse dir., E: Part spacingX. -1 stands for the low and 1 for the high level as given in Table 1.

Table 6Mean values of the tested factors of the DoE. A/B: Position X/Y, C/D: Longitudinal/transverse dir., E/F: Part spacing X/Y.

Factor Level Mean (s.d.)E [MPa] u [MPa] u [%]

A 41.75 2873 (108) 69.62 (3.29) 6.02 (1.25)448.25 2863 (96) 68.82 (4.36) 6.95 (2.37)

908 J. Mueller et al. / Materials and Design 86 (2015) 902912

lower and upper level is 3.68%, whereas for all others it is about 1.5%.The highest mean values result from a combination of high D and low F.

A significant influence of A*C (p = 0.007), C*D (p = 0.004), C*E(p = 0.007) and D*E (p = 0.002) is found for the total strain at break.B and F are insignificant for either of the outputs and therefore removed,which results, after updating the ANOVA, in a full factorial design withtwo replications (Table 5). A total of 20 df is now available for theresiduals, significantly increasing the statistical power. The effects arestill the same, but with p values decreasing to 0.001 or lower, the likeli-hoodof the effects being significant is evenhigher: A*C (p=0.001), C*D(p = 0.001), C*E (p = 0.001) and D*E (p b 0.001). As before, all maineffects are part of the interaction effects.

For A, the low levels cause a reduced total strain at break for all com-binations of the interactions (Fig. 8). Higher strains are reached for thelow levels of C, D and E with the only exception being the high level ofE in combination with D, which is, however, not statistically significant.With a difference of more than 30% between the means of the orienta-tion along X and Y, the largest effect size is found for C, followed byfactors A and D with differences close to 15%. A summary of all meanvalues is given in Table 6.

For the set-up indicated in Fig. 3, measurements of the temperatureon the surface of the printing table right after the finished job are madeand surface-fitted to the entire area of the table (Fig. 9). Values arefound between 33 C and 35 C, of which the highest ones occur nearthe idle position of the print head. Generally, higher temperatures arefound near the specimens, and low temperatures further away. It canalso be seen, that the temperatures between the two specimens to theleft are higher than the temperatures between the two specimens atthe top, and that the temperature at the bottom left position is higherthan the one at the top right position. The lowest values are found inthe lower right corner. Since UV light emits heat, the temperaturedistribution is also an indicator for the UV intensity received at eachposition of the table.

B 41.75 2880 (101) 69.61 (3.87) 6.32 (1.98)348.25 2856 (103) 68.82 (3.86) 6.64 (1.92)

C X 2861 (99) 69.66 (3.52) 7.61 (2.18)Y 2875 (106) 68.78 (4.17) 5.36 (0.44)

D X/Y 2850 (97) 67.67 (3.62) 6.92 (2.56)Z 2885 (105) 70.76 (3.46) 6.04 (0.82)

E 10 2878 (97) 69.48 (3.38) 6.86 (2.52)343 2858 (107) 68.96 (4.32) 6.11 (1.00)

F 10 2881 (86) 70.34 (3.71) 6.46 (1.79)243 2854 (115) 68.10 (3.71) 6.50 (2.11)

Between the blocks of different material expiry dates, p-values below 5% are reached forall mechanical properties (Table 7). Within a year, the elastic modulus is lowered by 79MPa (2.79%), the ultimate strength by 4.8 MPa (7.18%) and the total strain at break is in-creased by 1.21% (20.58%).

4.4. Longitudinal direction in Z

The means of the results for the longitudinal orientation in Z arecompared to themeans of the DoE results. Since the latter ones consistsof multiple settings, a normal distribution cannot be assumed, makingthe t-test is invalid. Instead, the MannWhitneyWilcoxon test isused, which replaces the t-value with a W-value (Table 8). The MannWhitneyWilcoxon test has a smaller statistical power when comparedto the t-test, but allows to compare populations that do not obey normaldistribution. Significant effects are found for the elastic modulus

(7.93%), ultimate strength (40.61%), and total strain at break(+72.54%).

4.5. Fracture surfaces

For all printing orientations, microscope images of the fracture sur-faces are taken and shown in Fig. 10. The initialization of the fractureis for all specimens close to, but not exactly at the edge, and close tothe corners. Moving from the position of the initiation towards theedge, a delamination of the printed layers is seen in the form of cracksin the XY plane, perpendicular to the Z axis. Moving from the positionof the initiation towards the inside of the specimens, an astral expansionbecomes visible. For Fig. 10ad, where the Z direction is in-plane withthe fracture surface, intra-laminar failure occurs interrupting the astralexpansion with cracks along the layer-intersections (orthogonal to Z).When Z is out-of-plane, the failure mode is predominantly inter-laminar. The astral expansion is then interrupted by cracks along the Xdirection, which are the intersections between the individual nozzlesof the print-head (Fig. 10e and f). Further, it can be seen that for a trans-verse specimen orientation along Z, the initiation is closer to thesmoother surface (Fig. 10 and d). In the two cases of Z being neitheraligned along the longitudinal nor along the transverse specimen direc-tion, the initiation seems to be closer to the rougher, outer surface(Fig. 10a and c).

Similarities in the general appearance appear pairwise and arelinked to the orientation of the longitudinal direction of the specimens:The surface of the specimen in Fig. 10a looks similar to the one in 10b,the one in Fig. 10c looks similar to the one in 10d and the one inFig. 10e looks similar to the one in 10 f.

5. Discussion

The Stratasys provided data for VeroWhitePlus are 20003000 MPafor the elastic modulus, 5065 MPa in tensile strength and 1025% intotal strain at break [48]. The values found in this work are on averageclose to the upper boundary for the elastic modulus while the ultimatestrength exceeds the listed upper boundary by more than 5 MPa (8%).For the total strain at break the experimental values are considerablylower than the lower boundary of the range. Since, in previously pub-lished research, other printer models were used, the results cannot becompared directly. On a qualitative basis, generally similar trends arereported for the factors tested, even though not always statistically sig-nificant [6,15,38]. It is also important to note that the mechanical prop-erties of photo-polymers are timedependent. Since they change linearly[38], tests undertaken in constant conditions remain comparable andthe results can be generalized.

Table 7F-test results of the difference in mechanical properties between the blocks.

Block Mean (s.d.) F p

E [MPa] 2014 2828 (65) 12.43 0.0022015 2907 (63)

u [MPa] 2014 66.82 (2.65) 90.55 b0.0012015 71.62 (2.29)

u [%] 2014 7.09 (2.48) 6.40 0.0182015 5.88 (0.86)

909J. Mueller et al. / Materials and Design 86 (2015) 902912

5.1. Warm-up time and cleanliness of nozzles

Two test series were performed to compare i.) the cold printer withthe warm printer, for which the nozzles were cleaned before the printsand ii.) the cold printerwith thewarmprinterwith cleannozzles only inthe cold state. i.) Considering the material, which is sprayed with about73 C on a printing table of room temperature, there is a gradient ofmore than 50 C which introduces local residual stresses potentiallypreventing contractions when the material touches the surface apotential reason for the increased cross-sectional widths of W and Wc.While the machine is running, parts of the printer heat up due tofriction, heat emission and UV light. The gradients of a warm machineare therefore smaller (Fig. 9), hence reducing the effect. The resulting,larger surface area of the warm structure can absorb more moisturefrom the air, which potentially leads to the higher mass observed.ii.) A dirty print head can lead to blocked nozzles, which yield a smallerflow rate. That, in turn, decreases the dimensional properties as ob-served in the length, thickness and thus the mass of the printed parts.Since not all nozzles were blocked and due to the longitudinal specimenorientation along Y, the machine was still able to produce the desiredwidth. The lower rupture strain can be explained by both the increasedsurface roughness and the maximum deviation from the thickness,yielding stress concentrations.

5.2. Time between printing and testing with different storage conditions

Over the duration of 21 days, a clear trend is only found for the frac-ture strain of the clean specimens, which indicates that the specimenscure further, even without exposition to UV light, and that the supportmaterial prevents this effect. Considering the values at the beginningand endof the other settings' ranges, and the fact that the same constantconditions as for all other tests are used, concludes that a potentiallyhidden effect of aging is relatively small compared to other factors. Tolearnmore, replications are required and a longer period of time shouldbe considered. Concerning the mass, the existence of a moisture resis-tance property of the material indicates the sensitivity to humidity insurrounding air [49]. That also explains the raise in weight with in-creased storage time. Cooling the samples down to room temperaturewithin a short period of time, the effect increases. The increasing gapbetween the storage of clean and shrouded samples shows that thesupport material slows the absorption process down.

Fig. 9. Temperature-distribution (C) on the printing table after finishing printing the in-dicated specimens. The measured values are fitted through a piecewise cubic interpola-tion [47]. The room temperature at the time of measurement was about 21.8 (C).

5.3. Expiry date of the material

The uncuredmaterial's aging effect is mentioned, but not quantified,by Gibson, Rosen and Stucker [12]. Here, the results show a statisticallymeaningful effect for the elastic modulus, ultimate strength and thetotal strain at break. As the material becomes stiffer, the compliancedecreases. While it is hard to determine whether the reason is theaging of the material or changes in the material formulation, it isknown that Stratasys continuously improves their materials (comparethe 2009 VeroWhite [50] with VeroWhitePlus from 2014 [48]).

5.4. Part position, orientation, spacing and material batch

The absence of significant effects for the elastic modulus can poten-tially be attributed to the larger standard deviations compared to theother outputs. The size of the residuals is about 25% of the total sum ofsquares, yielding a decreased F ratio an indication that an impact onthe elastic modulus can still exist. That also means, however, that apotentially hidden effect would be relatively small.

With respect to the ultimate strength, significant effects are foundfor all factors but the Y position. Since the idle position of the printhead is close the X(min)/Y(max) corner of the printing table (Fig. 11),there are two plausible explanations for factors A and B the X and Yposition on the printing table. The first reason is mechanicallymotivated in that the machine is optimized for this position, e.g. withrespect to manufacturing tolerances. The first reason can also includeelimination of disturbances during the operation of the printer in alonger perspective: The wear on certain parts of the printer, such asthe linear guides, is lower further away from the software's automatedplacement position since the majority of parts printed are rather smallin size thus utilizing more the corner around the idle position. Second,the automatic placement near the idle position is responsible for anincreased UV exposure of nearby parts, of which the temperature distri-bution in Fig. 9 is an indicator. The print head always moves back to theorigin in X before moving in Y-direction (Fig. 11). This also heats thetable up to a higher level along the Y-axis at X(min), leading to the effectdescribed previously (Fig. 9).

In the specimens' longitudinal alignment along X (Factor C),fewer nozzles are used compared to the alignment along Y, resultingin a smaller number of weakening intersections between materialdeposition within the layers. This is schematically shown in Fig. 12.The resulting parts are compared in Fig. 13a and b for the longitudinalalignment along X and in Fig. 13c and d for the longitudinal alignmentin Y. From the comparison it can be seen that, within the layers, indicat-ed by the shading, XY and XZ have longer, but fewer active nozzles, in-dicated by cylinders, compared to YX and YZ. Further, the intersections

Table 8MannWhitneyWilcoxon test comparing the longitudinal alignment along X/Y with thealignment along Z.

Mean (X/Y) Mean (Z) W p

E [MPa] 2918.15 2686.82 380 b0.001u [MPa] 69.05 41.01 384 b0.001u [%] 7.10 1.95 384 b0.001

Fig. 11.Moving directions of the print head. Also shown is the idle position relative to thedatum.

Fig. 10. Test specimens indicating the print directions (cylinders) and layers (shading ofthe cylinders) for the different print orientations. The first symbol indicates the longitudinaldirection on the printing table and the second one the transverse direction.

910 J. Mueller et al. / Materials and Design 86 (2015) 902912

of the latter ones are aligned orthogonally to the direction of the appliedload. When the length of the specimens is higher than the effectivelength of the print head Wpe or intersecting it due to positioning, theprint head has to move twice, adding both an additional intersectionof higher order (Fig. 12) and increased UV exposure.

For the transverse alignment (Factor D), the vertical directionconsists of more layers and thus more intersections in load direction(Fig. 12) and a higher UV exposure time, because the print head has tomove more often. This is contrasted in Fig. 13a and c (fewer layers)and in Fig. 13b and d (more layers).

Theminor impact of the part spacing inX (Factor E) can be explainedwith the print head, which moves back and forth in X with a relativelyhigh speed, regardless of how much material is printed in that layer.For larger distances, the exposure time therefore only increasesmarginally.

Assuming that the print head width Wpe can cover one specimenin Y-direction with each X-movement, a small distance between two

parts makes the print head move twice at an almost identical position,increasing the exposure time for both parts. When the parts are farapart, the print head still has to move twice, but the radiated lightonly reaches one specimen. This explains the stronger specimens for asmall part spacing in the Y direction (Factor F).

Compared to the elastic modulus and ultimate strength, oppositeeffects in total strain at break are found for the position in X and forthe longitudinal specimen orientation. Both of these factors are linkedto increased UV exposure time. It is therefore assumed that UV lighthardens the material, having a negative effect on the total strain atbreak. The longitudinal alignment and the spacing in X show similartrends like the elastic modulus and ultimate strength. As describedbefore, they are not directly linked to the UV exposure time, confirmingthe validity of the described mechanisms.

5.5. Longitudinal direction in Z

Due to the higher number of layers (Fig. 13e and f), printing in thevertical direction takes longer compared to other orientations. Thatleads to the highest UV exposure time of all the factors. However, thehigh number of layers also leads to the highest number of intersections.As the mechanical properties of parts longitudinally aligned along Z areconsiderably lower than for the others, the weakening effect of morelayers must be greater than the strengthening effect of the increasedUV exposure. It is also thinkable that, despite the shielding, thematerialis partially over-cured.

5.6. Fracture surfaces

A rough surface is normally responsible for high stress concentra-tions [51]. Due to lack of movement constraints, however, relaxationtakes place in the outer parts of the cross-sectional area of the printedspecimens [52]. The stress in load-direction is reduced at the edge, lead-ing to a crack initiation away from it. Due to contraction and rectangularshape of the cross-section, the stresses accumulate in the corners,whichleads to a failure at that position.

Delamination of the printing layers can be classified into i.) globaldelamination,where the layers are printed orthogonal to the load direc-tion (Z is out-of-plane, Fig. 10e and f) and ii.) local delamination, wherethe Z axis is in-plane and the layer intersections are not exposed to anormal load (Fig. 10a, b, c and d). While i.) can be explained with theload normal to the layers pulling them apart, the local delamination in

Fig. 12. Layer thickness (Tle) and effective printing width of the head (Wpe) and individualnozzles (Wne) schematically illustrated through cylinders.

911J. Mueller et al. / Materials and Design 86 (2015) 902912

ii.) is attributed to two effects. First, due to the relaxation explainedpreviously, the outer volumes are required to strain. Inhomogeneityinduced through the printing process shows that the intra-laminarbonding isweaker than the inter-laminar bonding, hence the layers sep-arate. Second, inhomogeneity also occurswithin the layers. This leads tofree-edge warping, which, in turn, induces positive inter-laminar andshear stresses, pulling the layers apart [53,54].

5.7. Implications for testing, design and optimization

The one-factor-at-a-timemethod is used to preliminarily test for thefactors that are both of interest and potentially time-saving in the maintests. The method revealed that a cold machine produces similarmechanical, but not geometric properties like a warm machine. Tomaintain a high geometric accuracy, it is important to clean the print

Fig. 13. Partial view of the test specimens indicating the print directions (cylinders) andlayers (shading of the cylinders) for the different print orientations. The first symbol indi-cates the longitudinal direction on the printing table and the second one the transversedirection.

head after each job. Comparable properties are achieved by keepingthe time between printing and testing constant, because the parts'mass and mechanical properties change with time. Due to differenteffects on the aging process, the support structure should be removedright away.

For the investigation of the main factors, Design of Experiments ischosen, where legitimate assumptions drastically reduced the testingtime compared to conventional methods. A modification of the initialdesign allowed for the study of even the high order interaction effectsand increased the statistical accuracy further. The best combination ofthe factor's levels in terms of elastic modulus and ultimate strength isfound to be for parts printed close to the X/Y idle position of the printhead. For the applied load direction, an alignment along the X axis ispreferable, followed by an alignment along the Y axis. Since thematerialdecays with time, the newest production date shall be used and whenprinting multiple parts in one job, they should be arranged closely. Toincrease the total strain at break, generally speaking, the oppositerecommendations are true.

The standard deviations and residuals are relatively small, indicatingthat all major impacting input factors are found. It illustrates that,in controlled environments, accurate, reproducible and especially pre-dictable part properties can be achieved, which is of major importancefor the design and optimization of load bearing, functional structuresproduced with AM.

6. Conclusions

This paper systematically investigates thewhole process of inkjet 3Dprinting to both determine the best conditions under which to fabricateand to provide reliable empirical data. For industry and research, accu-rate data on mechanical properties and process knowledge is essentialfor the design, modeling, simulation and optimization of parts for AM.Factors influencing the parts' properties are identified, quantified andranked to give best practice for reliably achieving the best geometricand mechanical properties. Since most effects are related to fundamen-tal properties of the process, the results are applicable to other inkjet-based printers. The aim of this understanding is to enable the designand optimization of functional parts, thus going beyond the currentfocus on prototypes for this process. It is also shown that by carefullyselecting and defining the test order and method, an efficient experi-mental design for testing AM parts can be created.

Acknowledgments

This research is supported by the ETH Zurich, Seed Project SP-MaP0214, Additive Manufacturing of Complex-Shaped Parts with LocallyTunable Materials. The authors also acknowledge Shi En Kim forperforming preliminary experimental tests.

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Mechanical properties of parts fabricated with inkjet 3D printing through efficient experimental design1. Introduction2. Background2.1. Design of experiments2.2. Inkjet 3D printing

3. Materials and methods3.1. Statistical method3.2. Input factors3.3. Fabrication and removal of support material3.4. Experimental analysis

4. Results4.1. Warm-up time and cleanliness of nozzles4.2. Time between printing and testing with different storage conditions4.3. Part position, orientation, spacing and material batch4.4. Longitudinal direction in Z4.5. Fracture surfaces

5. Discussion5.1. Warm-up time and cleanliness of nozzles5.2. Time between printing and testing with different storage conditions5.3. Expiry date of the material5.4. Part position, orientation, spacing and material batch5.5. Longitudinal direction in Z5.6. Fracture surfaces5.7. Implications for testing, design and optimization

6. ConclusionsAcknowledgmentsReferences