Modelling the Process of Fused Deposition Modelling and the Effect of Temperature on the Mechanical, Roughness, and Porosity Properties of Resulting Composite Products

Advances in the additive manufacturing (AM) processes have opened up the possibilities of widely using them in various structural sectors. Since 1980s this technology has been in permanent mutations. The ramification of the AM technology makes it difficult to obtain a clear impression of its potentialities. Predicting and controlling the mechanical characteristics of printed products is crucial for their final practical use. This study mainly aims to characterize the impact of printing parameters on the characteristics of printed articles and to evaluate their significance.

Introduction

The Additive Manufacturing (AM) is a sophisticated technology used for three-dimensional processing by joining materials, usually layer by layer. This process offers the benefit of creating any complex object starting from a 3D representation of its external surface. It goes with a short realization time, cost efficiency, and minimum need for tooling. A wide variety of materials can be used in this process, such as ceramics, polymers, metals, alloys, and composites [1, 2], which allow them to invade different industrial sectors including, aerospace [3], building [4,5,6], biomedical [7,8,9,10], education [11], and also to use it for personal needs, such as art and hobb ies.

Actually, the AM is the most usable manufacturing process in medical industry to combat the recent pandemic (Covid-19 virus) [12,13,14]. New AM applications have appeared to withstand this virus, such as manufacturing medical face masks.

In a few recent years, the range of AM feedstock has been enlarged significantly by adding new materials to it, such as nanoparticles and smart and biobased materials to expand and to strengthen its application domains by helping in the protection of environment [2, 15,16,17,18,19].

The AM includes a large number of processes. All they differ in the principle of operation, the layer deposition manner, and the materials used to produce parts. There are three different categories of AM processes — liquid-, solid-, and powder-based ones. Depending on these categories, the material transformation process ranges from polymerization, binding, to melting [20]. In Fig. 1, the AM processes are compared in terms of material and product characteristics [2, 21,22,23]. The cost and speed are among the primary considerations when choosing an adequate printing machine. The Fused Deposition Modelling (FDM) is the least expensive process, with a low expenditure of energy. For this reason, it is the main technique used nowadays, especially to improve the quality of FDM-printed products, including their mechanical and thermal characteristics.

Fig. 1.
figure1

AM classification based on the Main machine characteristics (a) and esthetic features (b): 1 — build cost, 2 — build speed, 3 — dimensional accuracy, and 4 — surface quality.

This article reflects the challenges regarding the parameter identification of printed products and the sensitivity analysis of the parameters affecting their quality the most. It also analyzes their main characteristics, including surface quality, porosity, and mechanical features.

Fused Deposition Modelling (FDM)

The FDM is an additive manufacturing process where thin filaments of a plastic material are used to build objects by adding their layers. It was patented by Scott Crump in 1988 [24] and commercialized by Stratasys in the USA. The FDM printing process begins with adjustment of the melting temperature. Then, the machine is fueled with a filament feedstock, which is pushed to the heated liquefier via a stepper motor to a pinch roller mechanism to be melted there. The different steps of the feeding process present multiple mechanical and thermal actions (tension, compression, and heating). The melted material obtained is then extruded selectively through a small print nozzle that traces the cross-sectional geometry of parts by roads or by beads given by the STL model (Fig. 2) [25,26,27].

Fig. 2.
figure2

Fused deposition modelling (FDM) (a) and nozzle geometry (b): 1 — build platform, 2 — foam base, 3 — part, 4 — build material filament spool, 5 — support material filament spool, 6 — print nozle, 7 — feed pinch rollers, 8 — heated liquefier, 9 — section 1, 10 — section 2, and 11 — section 3.

The nonlinearity of the melt properties generated during printing mainly depends on its temperature and shear rate. The feedstock feed rate is controlled in the liquefier in order to maintain the volumetric flow rate constant. The melt flow in the liquefier is described by the generalized Newtonian power law where τ is the shear stress, \( \dot{\upgamma} \) is the shear rate, and m and Φ are material constants.

The liquefier geometry is divided into different sections, as shown in Fig. 2 [28], and the temperature variation during and after the extrusion process is described by the equation

$$ \rho {c}_p\frac{\partial T}{\partial t}=\lambda \left(\frac{\partial^2T}{\partial {x}^2}+\frac{\partial^2T}{\partial {y}^2}+\frac{\partial^2T}{\partial {z}^2}\right), $$

where ρ , cp , and λ are the density, the specific heat capacity (at a constant pressure), and the coefficient of thermal conductivity, respectively.

Furthermore, the latent heat in the transition phase of polymers during the extrusion process also cannot be ignored. The enthalpy in this case is

$$ H=\int \rho C(T) dT, $$

where ρ is the density, C is the specific heat, and T is temperature

Parameter Analysis and Discussion

Many researchers have investigated the properties of parts made by the FDM and the process parameters characterizing the deposited layer geometries, which are presented in Figs. 3 and 4.

Fig. 3.
figure3

Principal FDM process parameters.

Fig. 4.
figure4

FDM tool path parameters: 1 — raster, 2 — raster angle, 3 — raster width, 4 — perimeter, and 5 — air gap.

Surface roughness and porosity

Among the critical properties of FDM products treated are their surface quality and dimensional accuracy [29]. According to the recent reports and results, the surface roughness is affected most by the layer thickness, followed by the raster width and building orientation of a part [30]. The latter parameter greatly affects the dimensional accuracy, followed by the layer thickness [31]. A small layer thickness, as well as a small raster width of filaments, improves the surface quality.

A void between deposited filaments, called “air gap”, which is a crucial parameter of the final part of FDM, has a greater impact on the dimensional accuracy than the surface roughness. There are three types of air gaps. A positive air gap means the presence of a void between roads, a zero gap means that there are no voids between them (they touch each other), and a negative one means that roads overlap. The porosity of a part is indispensable in the case of FDM-mode products, due to the manufacturing method based on road deposition next to each other. The use of negative air gap factors may decrease the porosity, which reduces dimensional errors, but impairs the surface quality of final parts [32]. Therefore, to achieve a minimum dimensional error and ensure a good surface quality, it is recommended to use the following combination: a small layer thickness, an average raster width, a zero air gap, and the 0°/90° orientation of rods [33]. Besides, some esthetic defects can be removed by postprocessing techniques, including mechanical ones, such as the milling, the CNC, the abrasive or vibratory bowl machining, or chemical techniques by applying vapor or a slight amount of acetone to dissolve the rough or porous parts in order to achieve the best final quality [34].

The effect of raster angle on the esthetic properties of final parts have also been investigated. It is found that the effect of this parameter depends on the material printed. Generally, the +45°/–45° angles have found to give the best surface quality and dimensional accuracy [35]. The aesthetic properties of final FDM products depend mainly on the layer thickness and printing orientation.

Mechanical properties

When printing functional parts, their crucial features are Young’s modulus, the ultimate tensile strength, yield strength, and ductility. These parameters influence the mechanical properties of FDM-made parts to different degrees.

It is worth mentioning that the main FDM parameter to obtain a functional part is the part fill that specifies the percentage of material [36,37,38]. This parameter should be fixed at high values, which are linked to negative values of the air gap parameter.

There exists an extensive range of FDM feedstock materials, of which acrylonitrile butadiene styrene (ABS) and polylactic acid (PLA) have been widely studied owing to their good mechanical properties. A literature survey shows that up to 2/3 of the studies reported concern exactly these two materials. It reveals that the building orientation and raster angle are the factors that influence the tensile properties of products, including Young’s modulus, the ultimate tensile strength, and ductility most significantly, followed by the layer thickness and other FDM parameters. Building ABS and PLA parts in the plane direction is the optimal direction to ensure the highest Young’s modulus [39,40,41], but the impact of raster angle is substantially different. The highest ultimate strength is obtained by printing at 45° and 0°/90° angles for PLA [40] and ABS [42, 43] samples, respectively. The layer thickness is also an important input parameter affecting their tensile properties. It has been shown that small layer thicknesses (less than 1 mm) are the most adequate to realize FDMmade parts with good mechanical characteristics [36, 39, 40, 44]. The interlayer and interraster bondings are among the weakest ones in the FDM process. Therefore, the raster width should be great to cover the full adhesion surface in order to ensure a high degree of cohesion in the part [40, 45].

The FDM feedstock is not restricted to ABS and PLA materials. There are several polymers that are also classified as stiff and strong FDM materials, e.g., polycarbonate (PC), polypropy lene (PP), PEEK, UTEM, and polyamide (PA).

For PC, PEEK, and PLA, the same raster angles and building orientation are recommended [38, 42]. PP, PA and UTEM 9085 are similar to ABS, for which the zero raster angle is the best to reach a high Young’s modulus and the ultimate tensile strength [46,47,48,49].

As for the fracture toughness, it is highest at the zero raster angle, which may increase the fracture toughness Kc to about 2 and 5 MPa·m1/2 for ABS [50,51,52] and PLA [44] respectively. The fracture toughness can also be improved by increasing the roughness degree of material mixture, because the grains present in the material tend to resist crack growth [53].

Impact of printing temperature

Much attention has been focused on finding the optimal tool path parameters and on clarifying their impact on the printing pattern and the 3D-printing object. But the relation between these printing parameters and the printing temperature is often neglected. One of the major concerns related to the fused deposition modelling process is to maintain an adequate printing temperature to ensure a smooth printing operation.

An inadequate extrusion temperature range can damage the product. Low temperatures can lead to a low layer adhesion (Fig. 5), peeling off of layers, and even nozzle clogging. At a high printing temperature, large thermal gradients can arise, and attempts to of maintain a constant layer height can alter the desirable geometry of parts [31, 54].

Fig. 5.
figure5

Low adhesion along the junction between layers in a FDM-printed part [54].

In all conditions, high or moderate temperatures are recommended. An increased temperature raises the average temperature between layers, and more time above Tg is spent, which improves the interlayer welding. Moreover, the raster angle and width become more adjusted and ensure a high adhesion in layers [55,56,57]. The layers are flattened, and the surface roughness of the whole part decreases.

The anisotropy of printed parts is better controllable at high printing temperatures. The voids in the mesostructure with a cross-linked filament arrangement is the principal factor increasing the porosity f [58,59,60]

A low temperature hinders the adequate flow deposition through the nozzle and may generate discontinuous rasters and decrease the cohesiveness between the deposited filaments. A high printing temperature decreases the porosity of printed parts by minimizing the thermal transfers of deposited rasters and maximizing the cooling time during the printing operation (Fig. 6) [61]. Guessasma [62] confirmed the existence of this phenomenon and proposed an approximate formula for the porosity f and the printing temperature Tp based on microtomography measurements, namely,

$$ f\left(\%\right)=19.2-0.06{T}_{\mathrm{p}}\left({}^{\circ}\mathrm{C}\right) $$
Fig. 6.
figure6

Filament cohesiveness at various printing temperatures (a) and the apparent density ρ (b) and porosity f (c) as functions of printing temperature [64].

This linear model shows that pores are not distributed arbitrarily in the printed part — they are concentrated at the intersection of printed rasters (Fig. 7).

Fig. 7.
figure7

The porosity f of a 3D-printed PLA revealed by the X-ray microtomography: cross-sectional views (a) and porosity network arrangement (b) [62]: 1 — void, 2 — raster, 3 — layer, 4 — frame, 5 — width, 6 — length, 7 — porosity network, 8 — surface porosity, 9 — building direction, and 10 — PA filament.

The printing temperature strongly correlates with mechanical properties, with anisotropy of the printed pattern being the main reason for its mechanical weakness. As already mentioned, a high printing temperature improves the interfilament welding and leads to a high adhesion between layers [61, 63, 64], which increases the elastic modulus and tensile strength. A summary of the results of literature studies is presented in Fig. 8, where it is shown that the mechanical properties of different FDM-made polymer composites depend on printing temperature [31, 38, 39, 42,43,44, 46, 48, 50,51,52, 54, 64,65,66,67,68,69,70,71,72,73]. Further investigations are needed to determine the optimal values of FDM process parameters by employing various design optimization methods and techniques [74,75,76,77,78].

Fig. 8.
figure8

Uniaxial tensile strength (UTS) (a), Young’s modulus E (b), and fracture toughness Kc (c) as a functions of printing temperature Tp .

Conclusion

The first part of this article was dedicated to an overview of the additive manufacturing and fused deposition processes. Various printing parameters and their influence on the quality of printed patterns were considered and recent results of temperature influence on their roughness and porosity during the FDM process were judged.

The crucial factors to be taken into account before building a part were examined, and it was found that the most significant ones were those related to tool path parameters, such as the layer thickness and part building orientation.

The influence of the principal printing parameter was described by a theoretical model characterizing the thermal behavior of parts during the printing process. Finally, the impact of printing temperature on the porosity and the mechanical behavior of printing polymers was summarized.

Nonetheless, there still are a few impediments which hinder one to obtain a product with excellent mechanical properties. The control of porosity of printed parts, which worsens their mechanical properties is still a problem. Voids in deposited trajectories and between layers reduce cohesion and, as result, small cracks may appear and propagate in parts. Therefore, fatigue studies are required to obtain a further insight into this phenomenon.

References

  1. 1.

    S. Guessasma, W. Zhang, J. Zhu, et al., “Challenges of additive manufacturing technologies from an optimisation perspective,” International Journal for Simulation and Multidisciplinary Design Optimization, 6, A9 (2015).

    Article  Google Scholar 

  2. 2.

    T. D. Ngo, A. Kashani, G. Imbalzano, K. T. Q. Nguyen, and D. Hui, “Additive manufacturing (3D printing): A review of materials, methods, applications and challenges,” Composites Part B: Engineering, 143, 172-196 (2018).

    CAS  Article  Google Scholar 

  3. 3.

    L. J. Kumar and C. K. Nair, “Current trends of additive manufacturing in the aerospace industry,”. In : Advances in 3D printing & additive manufacturing technologies, Springer, Singapore (2017). pp. 39-54.

  4. 4.

    A. Nadal, J. Pavón, and O. Liébana, “3D printing for construction: a procedural and material-based approach,” Informes de la Construcción, 69, 546, e193, (2017).

  5. 5.

    Y. W. D. Tay, B. Panda, S. C. Paul, et al., “3D printing trends in building and construction industry: a review,” Virtual and Physical Prototyping, 12, No. 3, 261-276 (2017).

  6. 6.

    J. Xu, L. Ding, and P. E. Love, “Digital reproduction of historical building ornamental components: From 3D scanning to 3D printing,” Automation in Construction, 76, 85-96 (2017).

    Article  Google Scholar 

  7. 7.

    A. S. Mangat, S. Singh, M. Gupta, et al., “Experimental investigations on natural fiber embedded additive manufacturing-based biodegradable st0ructures for biomedical applications,” Rapid Prototyping Journal, 24, 1221-1234 (2018).

    Article  Google Scholar 

  8. 8.

    J. Avila, S. Bose, and A. Bandyopadhyay, “Additive manufacturing of titanium and titanium alloys for biomedical applications,” Titanium in Medical and Dental Applications, 325-343 (2018).

  9. 9.

    F. Liravi and E. Toyserkani, “Additive manufacturing of silicone structures: A review and prospective,” Additive Manufacturing, 24, 232-242 (2018).

    CAS  Article  Google Scholar 

  10. 10.

    M. Trivedi, J. Jee, S. Silva, et al., “Additive manufacturing of pharmaceuticals for precision medicine applications: A review of the promises and perils in implementation,” Additive Manufacturing, 23, 319-328 (2018).

    CAS  Article  Google Scholar 

  11. 11.

    S. Ford and T. Minshall, “Invited review article: Where and how 3D printing is used in teaching and education,” Additive Manufacturing, 25, 131-150 (2019).

    Article  Google Scholar 

  12. 12.

    R. Srinivasan, A. Mian, J. Gockel, et al., “Additive Manufacturing and How 3D Printing is Fighting COVID-19,” Additive Manufacturing, 5, 1-2020 (2020).

    Article  Google Scholar 

  13. 13.

    J. M. Zuniga and A. Cortes, “The role of additive manufacturing and antimicrobial polymers in the COVID-19 pandemic,” Expert Review of Medical Devices, 17, No. 6, 477-481(2020).

  14. 14.

    J. M. Pearce, “A review of open source ventilators for COVID-19 and future pandemics,” F1000Research, 9, 218 (2020).

  15. 15.

    J. Y. Lee, J. An, and C. K. Chua, “Fundamentals and applications of 3D printing for novel materials,” Applied Materials Today, 7, 120-133 (2017).

    Article  Google Scholar 

  16. 16.

    B. Bhushan and M. Caspers, “An overview of additive manufacturing (3D printing) for microfabrication,” Microsystem Technologies, 23, 1117-1124 (2017).

    Article  Google Scholar 

  17. 17.

    X. Wang, M. Jiang, Z. Zhou, J. Gou, and D. Hui, “3D printing of polymer matrix composites: A review and prospective,” Composites Part B: Engineering, 110, 442-458 (2017).

    CAS  Article  Google Scholar 

  18. 18.

    J. S. Cuellar, G. Smit, D. Plettenburg, et al., “Additive manufacturing of non-assembly mechanisms,” Additive Manufacturing, 21, 150-158 (2018).

    Article  Google Scholar 

  19. 19.

    D. Rejeski, F. Zhao, and Y. Huang, “Research needs and recommendations on environmental implications of additive manufacturing,” Additive Manufacturing, 19, 21-28 (2018).

    Article  Google Scholar 

  20. 20.

    C. Teng, D. Pal, H. Gong, K. Zeng, et al., “A review of defect modeling in laser material processing,” Additive Manufacturing), 14, 137-147 (2017).

  21. 21.

    L. J. Kumar, P. M. Pandey, and D. I. Wimpenny, “Comparison of bonding strength of Ti–6Al–4V alloy deposit and substrate processed by laser metal deposition,” 3D Printing and Additive Manufacturing Technologies, Springer, 29- 38, (2019)

  22. 22.

    W. T. Carter, M. G. Jones, L. Yuan et ,al., “Control of solidification in laser powder bed fusion additive manufacturingusing a diode laser fiber array,” U.S. Patent No. 10532556, Jan. 14, 2020.

  23. 23.

    F. Khodabakhshi, M. H. Farshidianfar, A. P. Gerlich, et al., “Effects of laser additive manufacturing on microstructure and crystallographic texture of austenitic and martensitic stainless steels,” Additive Manufacturing, 31, 100915 (2020).

    CAS  Article  Google Scholar 

  24. 24.

    S. S. Crump, “Apparatus and method for creating three-dimensional objects,” U.S. Patent No. 5121329, June 9, 1992.

  25. 25.

    G. D. Goh, Y. L. Yap, H. Tan, S. L. Sing, G. L. Goh, and W. Y. Yeong, “Process–structure–properties in polymer additive manufacturing via material extrusion: A review,” Critical Reviews in Solid State and Materials Sciences, 45, 113-133 (2020).

    CAS  Article  Google Scholar 

  26. 26.

    H. Wu, W. Fahy, S. Kim, H. Kim, et al., “Recent developments in polymers/polymer nanocomposites for additive manufacturing,” Progress in Materials Science, 111, 100638 (2020).

    CAS  Article  Google Scholar 

  27. 27.

    S. Daminabo, S. Goel, S. Grammatikos, H. Nezhad, and V. K. Thakur, “Fused deposition modeling-based additive manufacturing (3D printing): techniques for polymer material systems,” Materials Today Chemistry, 16, 100248 (2020).

    CAS  Article  Google Scholar 

  28. 28.

    Y. Zhang and V. Shapiro, “Linear-time thermal simulation of as-manufactured fused deposition modeling components,” Journal of Manufacturing Science and Engineering, 140, 071002 (2018).

    Article  Google Scholar 

  29. 29.

    A. Qattawi and M. A. Ablat, “Design consideration for additive manufacturing: fused deposition modelling,” Open Journal of Applied Sciences, 7, 291 (2017).

    Google Scholar 

  30. 30.

    E. Vahabli and S. Rahmati, “Improvement of FDM parts’ surface quality using optimized neural networks–medical case studies,” Rapid Prototyping Journal, 23, 825-842 (2017).

    Article  Google Scholar 

  31. 31.

    S. Mahmood, A. Qureshi, and D. Talamona, “Taguchi based process optimization for dimension and tolerance control for fused deposition modelling,” Additive Manufacturing, 21, 183-190 (2018).

    Article  Google Scholar 

  32. 32.

    H. Nouri, S. Guessasma, and S. Belhabib, “Structural imperfections in additive manufacturing perceived from the X-ray micro-tomography perspective,” Journal of Materials Processing Technology, 234, 113-124 (2016).

    CAS  Article  Google Scholar 

  33. 33.

    P. K. Garg, R. Singh, and I. Ahuja, “Multi-objective optimization of dimensional accuracy, surface roughness and hardness of hybrid investment cast components,” Rapid Prototyping Journal, 23, 845-857 (2017).

    Article  Google Scholar 

  34. 34.

    J. S. Chohan and R. Singh, “Pre and post processing techniques to improve surface characteristics of FDM parts: a state of art review and future applications,” Rapid Prototyping Journal, 23, 495-513 (2017).

    Article  Google Scholar 

  35. 35.

    A. Armillotta and M. Cavallaro, “Edge quality in fused deposition modeling: I. Definition and analysis,” Rapid Prototyping Journal, 23, 1079-1087 (2017).

    Article  Google Scholar 

  36. 36.

    X. Zhou, S. J. Hsieh, and C. C. Ting, “Modelling and estimation of tensile behaviour of polylactic acid parts manufactured by fused deposition modelling using finite element analysis and knowledge-based library,” Virtual and Physical Prototyping, 13, No. 3, 177-190 (2018).

    Article  Google Scholar 

  37. 37.

    Y. Y. Aw, C. K. Yeoh, M. A. Idris, P. L. The, et al., “Effect of printing parameters on tensile, dynamic mechanical, and thermoelectric properties of FDM 3D printed CABS/ZnO composites,” Materials, 11, No. 4, 466 (2018).

  38. 38.

    X. Deng, Z. Zeng, B. Peng, et al., “Mechanical properties optimization of poly-ether-ether-ketone via fused deposition modeling,” Materials, 11, No. 2, 216 (2018).

    Article  CAS  Google Scholar 

  39. 39.

    J. Chacón, M. Caminero, E. García-Plaza, and P. Núñez, “Additive manufacturing of PLA structures using fused deposition modelling: Effect of process parameters on mechanical properties and their optimal selection,” Materials & Design, 124, 143-157 (2017).

    Article  CAS  Google Scholar 

  40. 40.

    X. Liu, M. Zhang, S. Li, L. Si, et al., “Mechanical property parametric appraisal of fused deposition modeling parts based on the gray Taguchi method,” The International Journal of Advanced Manufacturing Technology, 89, 2387- 2397 (2017).

    Article  Google Scholar 

  41. 41.

    D. A. Türk, F. Brenni, M. Zogg, and M. Meboldt, “Mechanical characterization of 3D printed polymers for fiber reinforced polymers processing,” Materials & Design, 118, 256-265 (2017).

    Article  CAS  Google Scholar 

  42. 42.

    J. T. Cantrell, S. Rohde, D. Damiani, R. Gurnani, et al., “Experimental characterization of the mechanical properties of 3D-printed ABS and polycarbonate parts,” Rapid Prototyping Journal, 23, 811-824 (2017).

    Article  Google Scholar 

  43. 43.

    S. Mahmood, A. Qureshi, K. L. Goh, and D. Talamona, “Tensile strength of partially filled FFF printed parts: experimental results,” Rapid Prototyping Journal, 23, 122-128 (2017).

    Article  Google Scholar 

  44. 44.

    Y. Song, Y. Li, W. Song, K. Yee, et al., “Measurements of the mechanical response of unidirectional 3D-printed PLA,” Materials & Design, 123, 154-164 (2017).

    CAS  Article  Google Scholar 

  45. 45.

    M. S. Uddin, M. F. R. Sidek, M. A. Faizal, et al., “Evaluating mechanical properties and failure mechanisms of fused deposition modeling acrylonitrile butadiene styrene parts,” Journal of Manufacturing Science and Engineering, 139, No. 8, 081018, (2017).

    Article  Google Scholar 

  46. 46.

    M. Milosevic, D. Stoof, and K. Pickering, “Characterizing the Mechanical Properties of Fused Deposition Modelling Natural Fiber Recycled Polypropylene Composites,” Journal of Composites Science, 1, 1, 7 (2017).

    Article  CAS  Google Scholar 

  47. 47.

    L. Wang and D. J. Gardner, “Effect of fused layer modeling (FLM) processing parameters on impact strength of cellular polypropylene,” Polymer, 113, 74-80 (2017).

    CAS  Article  Google Scholar 

  48. 48.

    D. Stoof and K. Pickering, “Sustainable composite fused deposition modelling filament using recycled pre-consumer polypropylene,” Composites Part B: Engineering, 135, 110-118 (2018).

    CAS  Article  Google Scholar 

  49. 49.

    R. J. Zaldivar, D. B. Witkin, T. McLouth, et al., “Influence of processing and orientation print effects on the mechanical and thermal behavior of 3D-Printed ULTEM® 9085 Material,” Additive Manufacturing, 13, 71-80 (2017).

    CAS  Article  Google Scholar 

  50. 50.

    T. D. McLouth, J. V. Severino, P. M. Adams, D. N. Patel, and R. J. Zaldivar, “The impact of print orientation and raster pattern on fracture toughness in additively manufactured ABS,” Additive Manufacturing, 18, 103-109 (2017).

    CAS  Article  Google Scholar 

  51. 51.

    N. Aliheidari, R. Tripuraneni, A. Ameli, and S. Nadimpalli, “Fracture resistance measurement of fused deposition modeling 3D printed polymers,” Polymer Testing, 60, 94-101 (2017).

    CAS  Article  Google Scholar 

  52. 52.

    K. R. Hart and E. D. Wetzel, “Fracture behavior of additively manufactured acrylonitrile butadiene styrene (ABS) materials,” Engineering Fracture Mechanics, 177, 1-13 (2017).

    Article  Google Scholar 

  53. 53.

    V. Damodaran, A. G. Castellanos, M. Milostan, and P. Prabhakar, “Improving the Mode-II interlaminar fracture toughness of polymeric matrix composites through additive manufacturing,” Materials & Design, 157, 60-73 (2018).

    CAS  Article  Google Scholar 

  54. 54.

    K. Abouzaid, S. Guessasma, S. Belhabib, D. Bassir, and A. Chouaf, “Thermal mechanical characterization of copolyester for additive manufacturing using FDM,” International Journal for Simulation and Multidisciplinary Design Optimization, 10, A9 (2019).

    Article  Google Scholar 

  55. 55.

    D. J. Braconnier, R. E. Jensen, and A. M. Peterson, “Processing parameter correlations in material extrusion additive manufacturing,” Additive Manufacturing, 31, 100924 (2020).

    CAS  Article  Google Scholar 

  56. 56.

    T. J. Coogan and D. O. Kazmer, “Bond and part strength in fused deposition modeling,” Rapid Prototyping Journal, 23, No. 2, 414-422 (2017).

    Article  Google Scholar 

  57. 57.

    C. S. Davis, K. E. Hillgartner, S. H. Han, and J. E. Seppala, “Mechanical strength of welding zones produced by polymer extrusion additive manufacturing,” Additive manufacturing, 16, 162-166 (2017).

    CAS  Article  Google Scholar 

  58. 58.

    S. Guessasma, S. Belhabib, and H. Nouri, “Understanding the microstructural role of bio-sourced 3D printed structures on the tensile performance,” Polymer Testing, 77, 105924 (2019).

    Article  CAS  Google Scholar 

  59. 59.

    S. Guessasma, S. Belhabib, and H. Nouri, “Microstructure, Thermal and mechanical behavior of 3D printed acrylonitrile styrene acrylate,” Macromolecular Materials and Engineering, 304, No.7, 1800793 (2019).

    Article  CAS  Google Scholar 

  60. 60.

    S. G. Lekhnitskii, Elasticity Theory of Anisotropic Bodies [in Russian], Nauka, Moscow (1977).

    Google Scholar 

  61. 61.

    S. Guessasma, S. Belhabib, and H. Nouri, “Printability and Tensile Performance of 3D Printed Polyethylene Terephthalate Glycol Using Fused Deposition Modelling,” Polymers, 11, No. 7, 1220 (2019).

    Article  CAS  Google Scholar 

  62. 62.

    S. Guessasma, S. Belhabib, and A. Altın, “On the Tensile Behaviour of Bio-sourced 3D-Printed Structures from a Microstructural Perspective,” Polymers, 12, No. 5, 1060 (2020).

    CAS  Article  Google Scholar 

  63. 63.

    A. A. D’Amico, A. Debaie, and A. M. Peterson, “Effect of layer thickness on irreversible thermal expansion and interlayer strength in fused deposition modeling,” Rapid Prototyping Journal, 23, No. 5, 943-953 (2017).

    Article  Google Scholar 

  64. 64.

    K. Abouzaid, S. Guessasma, S. Belhabib, D. Bassir, and A. Chouaf, “Printability of co-polyester using fused deposition modelling and related mechanical performance,” European Polymer Journal, 108, 262-273 (2018).

    CAS  Article  Google Scholar 

  65. 65.

    A. N. Dickson, J. N. Barry, K. A. McDonnell, and D. P. Dowling, “Fabrication of continuous carbon, glass and kevlar fibre reinforced polymer composites using additive manufacturing,” Additive Manufacturing, 16, 146-152 (2017).

    CAS  Article  Google Scholar 

  66. 66.

    R. T. L. Ferreira, I. C. Amatte, T. A. Dutra, and D. Bürger, “Experimental characterization and micrography of 3D printed PLA and PLA reinforced with short carbon fibers,” Composites Part B: Engineering, 124, 88-100 (2017).

    CAS  Article  Google Scholar 

  67. 67.

    E. Gkartzou, E. P. Koumoulos, and C. A. Charitidis, “Production and 3D printing processing of bio-based thermoplastic filament,” Manufacturing Review, 4, No. 1 (2017).

  68. 68.

    Y. Jin, Y. Wan, B. Zhang, and Z. Liu, “Modeling of the chemical finishing process for polylactic acid parts in fused deposition modeling and investigation of its tensile properties,” Journal of Materials Processing Technology, 240, 233-239 (2017).

    CAS  Article  Google Scholar 

  69. 69.

    C. Koch, L. Van Hulle, and N. Rudolph, “Investigation of mechanical anisotropy of the fused filament fabrication process via customized tool path generation,” Additive Manufacturing, 16, 138-145 (2017).

    Article  Google Scholar 

  70. 70.

    N. G. Tanikella, B. Wittbrodt, and J. M. Pearce, “Tensile strength of commercial polymer materials for fused filament fabrication 3D printing,” Additive Manufacturing, 15, 40-47 (2017).

    CAS  Article  Google Scholar 

  71. 71.

    Z. Hou, X. Tian, J. Zhang, and D. Li, “3D printed continuous fibre reinforced composite corrugated structure,” Composite Structures, 184, 1005-1010 (2018).

    Article  Google Scholar 

  72. 72.

    H. Li, T. Wang, J. Sun, et al., “The effect of process parameters in fused deposition modelling on bonding degree and mechanical properties,” Rapid Prototyping Journal, 24, 80-92 (2018).

    Article  Google Scholar 

  73. 73.

    L. R. Lopes, A. F. Silva, and O. S. Carneiro, “Multi-material 3D printing: The relevance of materials affinity on the boundary interface performance,” Additive Manufacturing, 23, 45-52 (2018).

    CAS  Article  Google Scholar 

  74. 74.

    S. Bochkareva, N. Y. Grishaeva, B. A. Lyukshin, et al., “A unified approach to determining the effective physicomechanical characteristics of filled polymer composites based on variational principles,” Mech. Compos. Mater., 54, No. 6, 775-788 (2019).

    Article  Google Scholar 

  75. 75.

    E. Barkanov, A. Kovalov, P. Wierach, et al., “Optimized comparative analysis of an active twist for helicopter rotor blades with C-and D-spar designs,” Mech. Compos. Mater., 54, No. 5, 553-566 (2018).

    Article  Google Scholar 

  76. 76.

    T. Galichyan, A. Z. Khurshudyan, and D. FilippoV, “Parameter optimization of laminated multiferroic composites,” Mech. Compos. Mater., 55, No. 2, 211-218 (2019).

    CAS  Article  Google Scholar 

  77. 77.

    R. Turusov and V. Egorov, “Stress state and optimization of the parameters of interrupted and machine surgical sutures of human intestine,” Mech. Compos. Mater., 55, No. 3, 405-412 (2019).

    Article  Google Scholar 

  78. 78.

    J. Majak and S. Hannus, “Orientational design of anisotropic materials using the Hill and Tsai–Wu strength criteria,” Mech. Compos. Mater., 39, No. 6, 509-520 (2003).

    Article  Google Scholar 

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Acknowledgement

The authors are grateful to the French national Research Center (CNRS), National Institute of Research for Agronomy (INRA), and Avenir technology Ltd. for their support to this project.

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Correspondence to D. Bassir.

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Russian translation published in Mekhanika Kompozitnykh Materialov, Vol. 56, No. 6, pp. 1163-1178, November-December, 2020.

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Abouzaid, K., Bassir, D., Guessasma, S. et al. Modelling the Process of Fused Deposition Modelling and the Effect of Temperature on the Mechanical, Roughness, and Porosity Properties of Resulting Composite Products. Mech Compos Mater 56, 805–816 (2021). https://doi.org/10.1007/s11029-021-09925-6

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Keywords

  • additive manufacturing
  • fused deposition modelling
  • composite materials
  • surface roughness
  • porosity
  • parameter identification