applied sciences

Article for Additive Manufacturing: Tool Review and a Case Study

Daniel Moreno Nieto 1,* and Daniel Moreno Sánchez 2

1 Departamento de Ingeniería Mecánica y Diseño Industrial, Escuela Superior de Ingeniería, Universidad de Cádiz, Puerto Real, 11510 Cádiz, Spain 2 Departamento de Ciencia de los Materiales e Ingeniería Metalúrgica y Química Inorgánica, Facultad de Ciencias, IMEYMAT, Campus Río San Pedro, Universidad de Cádiz, PuertoReal, 11510 Cádiz, Spain; [email protected] * Correspondence: [email protected]; Tel.: +34-676923332

Abstract: This paper aims to collect in a structured manner different -aided (CAE) tools especially developed for additive manufacturing (AM) that maximize the capabilities of this technology regarding product development. The flexibility of the AM process allows the manu- facture of highly complex shapes that are not possible to produce by any other existing technology. This fact enables the use of some existing design tools like topology optimization that has already existed for decades and is used in limited cases, together with other novel developments like lattice design tools. These two technologies or design approaches demand a highly flexible manufacturing system to be applied and could not be used before, due to the conventional industrial process limita- tions. In this paper, these technologies will be described and combined together with other generic or specific design tools, introducing the study case of an additive manufactured mechanical design of a  bicycle stem. 

Citation: Moreno Nieto, D.; Moreno Keywords: additive manufacturing; ; fused deposition modeling; ; Sánchez, D. Design for Additive industrial design; CAD computer aided design; topology optimization; lattice design Manufacturing: Tool Review and a Case Study. Appl. Sci. 2021, 11, 1571. https://doi.org/10.3390/app 11041571 1. Introduction Additive manufacturing (AM) is a set of manufacturing processes that consist in Academic Editor: Marco Mandolini the generation of three-dimensional models from digital files, using different equipment and technologies that build objects layer by layer [1–4]. These technologies are reaching Received: 11 January 2021 the age of maturity due to their effective incorporation in different industries, besides Accepted: 3 February 2021 the pioneering aerospace and automotive industries, such as consumer products. There Published: 9 February 2021 are many advantages that additive manufacturing technologies offer to and engineers for the development of new parts and products. Publisher’s Note: MDPI stays neutral Advantages, the freedom of constructed geometries, which allows the elaboration of with regard to jurisdictional claims in published maps and institutional affil- complex shapes that would not be possible by other technologies [5], the reduction of parts iations. in the assemblies, by simplifying them or allowing the printing of the assembled parts [6–8], the capability of locating the necessary properties in specific areas or developing variable properties in the geometries of the parts and the possibility of manufacturing optimized structures that modify their properties according to the scale to which they refer, from the micro to the macro scale [9,10], are the most remarkable. Copyright: © 2021 by the authors. Through these advantages, additive manufacturing in the current state of development Licensee MDPI, Basel, Switzerland. is increasingly finding its place in industry, while understanding that it is not a substitute This article is an open access article distributed under the terms and technology, but rather complementary to current production technologies, in cases where conditions of the Creative Commons some of the characteristics mentioned above are required. That is, it will take its place within Attribution (CC BY) license (https:// the production processes and coexisting technologies, while having special importance in creativecommons.org/licenses/by/ parts with highly complex geometries, in small series and in customized products. 4.0/).

Appl. Sci. 2021, 11, 1571. https://doi.org/10.3390/app11041571 https://www.mdpi.com/journal/applsci Appl. Sci. 2021, 11, x FOR PEER REVIEW 2 of 13

Appl. Sci. 2021, 11, 1571 2 of 12 importance in parts with highly complex geometries, in small series and in customized products. The limitations of these processes have also been identified: the geometric character- isticsThe (tolerances limitations in the of thesedefinition processes of wall have thicknesses, also been holes, identified: rounding, the geometric cantilevers, characteris- bridges ticsand (tolerancesangles) and in the the anisotropy definition ofof wallthe thicknesses,process that holes,affects rounding, the mechanical cantilevers, properties bridges of andprinted angles) parts and [11,12]. the Those anisotropy inherent of the to the process execution that affectsof the process, the mechanical such as the properties orientation of printedof the part parts or [the11, 12definition]. Those of inherent the supports, to the execution deposition of rates, the process, finishes such or production as the orientation times, ofare the decisive part or for the the definition correct ofdefinition the supports, of the deposition geometries rates, [13–15], finishes as well or production as other factors times, aresuch decisive as scale forlimitations, the correct the definition absence of of spec theific geometries design and [13 simulation–15], as well tools as and other economic factors suchconsiderations. as scale limitations, All these the factors absence are ofrelated specific to design the execution and simulation of the design tools and for economic additive considerations.manufacturing [16,17]. All these factors are related to the execution of the design for additive manufacturingCurrently, [new16,17 design]. prescriptions and standards are appearing, providing the de- signerCurrently, a way to newmitigate design the prescriptionslimitations of and the standardstechnologies are and appearing, increase providingthe functional the designerperformance a way of tothe mitigate final fabricated the limitations parts, ofknown the technologies as design for and additive increase manufacturing the functional performance(DfAM) [18–22]. of theSome final aspects fabricated to be considered parts, known and as that design are directly for additive related manufacturing with the man- (DfAM) [18–22]. Some aspects to be considered and that are directly related with the ufacturing process are the disposition of holes that enable the evacuation of the residual manufacturing process are the disposition of holes that enable the evacuation of the material in the powder bed or liquid resin material or the deposition orientation in fused residual material in the powder bed or liquid resin material or the deposition orientation deposition modeling (FDM), for example. in fused deposition modeling (FDM), for example. In this context, in recent years, there has been an important advance in the field of In this context, in recent years, there has been an important advance in the field specific engineering technologies for additive manufacturing, with the continuous ap- of specific engineering technologies for additive manufacturing, with the continuous pearance of numerous tools that consider the materials and their properties as variables, appearance of numerous tools that consider the materials and their properties as variables, allowing for the prediction of their behavior and thus optimizing for manufacture. allowing for the prediction of their behavior and thus optimizing designs for manufacture. Prior to the description of these tools, we will review in a general way the main stages of Prior to the description of these tools, we will review in a general way the main stages of the work process for the design and additive manufacturing of parts. the work process for the design and additive manufacturing of parts.

2. The Additive Manufacturing WorkflowWorkflow The approachapproach toto the the additive additive manufacturing manufacturing processes processes establishes establishes an orderlyan orderly workflow, work- soflow, that so by that relying by relying on different on different tools, processing tools, processing files are files generated are generated for subsequent for subsequent printing andprinting post-processing. and post-processing. There are There five are fundamental five fundamental stages stages in the additivein the additive manufacturing manufac- process,turing process, which arewhich listed are below listed andbelow shown and shown in a diagram in a diagram in Figure in1 Figure. 1.

Figure 1. Additive manufacturing (AM) workflow. Note: CAD (Computer-Assisted Design); CAE (Computer-Aided- Figure 1. Additive manufacturing (AM) workflow. Note: CAD (Computer-Assisted Design); CAE (Computer-Aided- Engineering). Engineering).

(a)(a) Design:Design: For For the the development development of of the the parts parts and and products products that that will will be bemanufactured manufactured by additiveby additive processes, processes, the thefirst first stage stage consists consists of the of thegeneration generation of three-dimensional of three-dimensional de- signsdesigns by bymeans means of ofcomputer-assisted computer-assisted design design tools tools (CAD). (CAD). The The characteristics characteristics of thethe processesprocesses allow allow the generation of complex geometries, however, not all shapesshapes areare always viable and they are closely linked to the technology used. The construction always viable and they are closely linked to the technology used. The construction of of 3D models can be done with conventional solid and surface modeling programs; likewise, due to the flexibility of the process, the use of advanced modeling tools, such as polygonal meshes or NURBS surfaces, is very common. (b) Verification: Once the design process is completed, the next step is to export the files to the standards. The most common file format is STL, which consists of Appl. Sci. 2021, 11, 1571 3 of 12

a triangulated surface mesh that defines the complete geometry [23]. The export of files is done for their correct inclusion in the lamination tools or slicers. However, a previous step of surface verification is recommended, since sometimes discontinuities or incorrect orientations of the normals that define the surface triangles could be produced. (c) Slicing: The lamination programs or slicers previously mentioned are the tools that generate the machine code with the characteristics of the process and the parameters, as well as the trajectories. It is important to define the correct parameters of the process according to the characteristics of the design and materials. The main parameters shared by most processes are: layer height, manufacturing speed, temperature and percentage of filling. The result of this process definition is the machine path files, which are transferred to the printing equipment for process activation. (d) 3D printing: This is the physical process in which the materialization of the parts using the 3D printers in question is done. Its characteristics vary depending on the technology selected. A common feature in all the technologies is that this is a long pro- cess and usually requires post-processing compared with traditional manufacturing processes such as injection molding. (e) Post-processing: Depending on the characteristics of the process, more or less inter- vention is necessary to achieve the specific finish and properties of the printed parts. Tasks common to all technologies are the removal of parts from the printing surface, the removal of supports and mechanical processes of surface finishing, as well as heat and surface treatments, if necessary.

3. Additive Manufacturing Design Tools In order to take advantage of and mitigate the limitations of these AM processes, different tools have appeared in recent years that maximize the potential of the constructive capabilities offered by additive manufacturing technologies. These programs consist of engineering and CAD platforms such as mesostructured design and optimization programs, along with process management and simulation solutions. One of the main objectives set in the development of this work is to configure an updated workflow, ordered and structured to optimize processes from the integration and exchange of files, as well as to maximize the potential of the possibilities of forming that AM technologies present, supported by these specific tools. In Figure2 is presented different CAD and computer-aided engineering (CAE) tools currently available for the AM design process. Some of these programs previously existed on the market and have been adapted to these technologies, as well as other new specific tools that are appearing as the development and implementation of them advance. Within the software tools, in addition to the traditional CAD programs, such as para- metric design programs, e.g., Catia and Solidworks (Dassault Systèmes, Vélizy-Villacoublay, France), Inventor (, San Rafael, CA, USA) or NX (Siemens, Munich, Germany), we have to consider expanding the range of tools. Thanks to the design freedom offered by layer-by-layer construction in the AM technologies, which allows us to shape virtually any geometry, we must add other surface design tools, which include the above programs, and other new ones such as Rhino (Robert McNeel & Associates, Seattle, WA, USA) or Alias and 3D Studio (Autodesk, San Rafael, CA, USA). AM allows us to create objects with organic shapes and geometric complexity without a great impact on the cost or complexity of manufacturing. This freedom already existed in digital design for animation or video games, while CAD software traditionally associated with mechanical design had limited capabilities. Although in the latest versions of the abovementioned CAD software, the possibility of making complex geometries more easily has already been implemented, certain specialized software is still required. These programs usually work with 3D design tools based on NURBS or editable polygonal mesh that allow a freer and more organic design without limitations when generating geometries or parts. Appl. Sci. 2021, 11, x FORAppl. PEER Sci. REVIEW2021, 11, 1571 4 of 13 4 of 12

TOPOLOGY PROCESS IN SERVICE PREPRINTING DESIGN 3D MESH OPTIMIZATION SIMULATION SIMULATION SLICING

Figure 2. Tools that canFigure be used 2. Tools in the that AM can beprocess. used in the AM process.

Within the softwareAnother tools, trend in addition in AM is to the the use traditional of optimization CAD programs, software, based such onas developmentspar- ametric design programs,that have hade.g., moreCatia than and 20Solidworks years of use (Dassault in the industry, Systèmes, however, France), they Inven- have never had tor (Autodesk, Unitedan extensive States) use, or NX because (Siemens the solutions, Germany), they provide,we have in to geometric consider terms, expanding are always very the range of tools.complex Thanks and to the traditional design freed productionom offered processes by layer-by-layer for machining or construction casting did notin meet the the AM technologies,requirements which allows for proper us to production.shape virtually However, any geometry, with the emergence we must add of AM other technologies surface design tools,and theirwhich layer-by-layer include the production above programs, systems, theseand othe geometriesr new resultingones such from as different optimizations, whether volumetric, shape or topological, as schematized in Figure3, Rhino (Robert McNeel & Associates, United States) or Alias and 3D Studio (Autodesk, are perfectly achievable. The optimization tools determine formal solutions to different United States). AMrequirements allows us throughto create the objects application with oforganic numerical shapes models and in geometric iterative processes, com- based Appl. Sci. 2021, 11, x FOR PEER REVIEW 5 of 13 plexity without aon great different impact calculation on the cost algorithms or complexity of shape, of volumemanufacturing. or load [24 This], trying freedom to obtain ideal already existed insolutions digital design with respect for animation to the geometries or video of thegames, parts. while CAD software tra- ditionally associated with mechanical design had limited capabilities. Although in the lat- est versions of the abovementioned CAD software, the possibility of making complex ge- ometries more easily has already been implemented, certain specialized software is still required. These programs usually work with 3D design tools based on NURBS or editable polygonal mesh that allow a freer and more organic design without limitations when gen- erating geometries or parts. Another trend in AM is the use of optimization software, based on developments that have had more than 20 years of use in the industry, however, they have never had an extensive use, because the solutions they provide, in geometric terms, are always very complex and traditional production processes for machining or casting did not meet the requirements for Figureproper 3.3. Simple production.Simple beam beam parametric However,parametric optimization optimizationwith the (a emergence) of ( shapea) of shape (b) andof (AMb topology) and technologies topology (c). Adapted (c). Adapted from [1]. from and their layer-by-layer[1]. production systems, these geometries resulting from different op- Among the most widespread tools in the processes of AM, we must highlight the timizations, whether volumetric, shape or topological, as schematized in Figure 3, are per- topologicalAmong optimization the most (TO).widespread In this type tools of tool, in the starting processes from some of AM, established we must objectives highlight the fectly achievable.(usually The optimization minimizing tools mass dete or maximizingrmine formal rigidity) solutions and someto different requirements require- of load and topological optimization (TO). In this type of tool, starting from some established objec- ments through therestrictions application of design,of numerical an orientated models solution in iterative adapted processes, to the defined based objectives on differ- is obtained. ent calculation algorithmsThetives solutions (usually of shape, provided minimizi volume byng this mass or tool load or serve maximizing[24], as trying a reference torigidity) obtain shape andideal of the some solutions part designs.requirements Some of load with respect to theandcommercial geometries restrictions solutions of theof design, parts. are TOSCA, an orientated from Dassault solution Systems, adapted a tool to integratedthe defined in objectives the Gen- is ob- tained.erative DesignThe solutions module provided of Catia V.6, by multi-materialsthis tool serve as such a reference as Paramatters shape (Paramatters, of the part designs. Ventura,Some commercial CA, USA), solutions Inspire based are TOSCA, on Optistruct from (Altair, Dassault Troy, Systems, NY, USA), a tool Pareto integrated (Sciart in the GenerativeSoftware, Madison, Design WI, module USA) of or Catia the Limitstate V.6, mult Formi-materials (Limitstate, such Sheffield, as Paramatters UK). There (Paramatters, are United States), Inspire based on Optistruct (Altair, United States), Pareto (Sciart Software, United States) or the Limitstate Form (Limitstate, United Kingdom). There are also pro- cesses defined in traditional CAE tools, such as finite element calculation software Ansys (Ansys Inc., United States), Abaqus (Dassault Systèmes, France), Comsol (Comsol Group, Sweden) or Nastran (Autodesk, United States), HyperWorks (Altair, United States), which usually incorporate the simulation of the optimized parts for verification of the modifica- tions, although they do not consider the anisotropic behavior of the printed parts. We differentiate in this section the topological optimization tools, continuous and discrete, differentiated according to the type of algorithm and the way of locating the load vectors. The first is based on continuous volumes and the second on systems of beams intercon- nected to the points that are subjected to maximum stress. The most used algorithms for the optimization of these structures are the solid iso- tropic microstructure with penalty (SIMP) algorithm and the bidirectional evolutionary structural optimization (BESO) algorithm [24]. The established algorithms for topological optimization focus on conventional manufacturing systems and can be used in additive manufacturing if the constraints, usually volumetric and strain energy, are minimized. Currently, TO is used in different sectors, such as wind [25] and automotive sectors [26] or the redesign of casting parts [27]. Additionally, one of the latest trends in TO is the use of a topology optimization algorithm while considering the –time of the process. This concept has been well implemented in the bridge created by MX3D [28]. The process considered the evolution of the structure to self-support the weight of two robotic arms during the manufacturing, using wire arc additive manufacturing (WAAM) technology. With the same objective of minimizing weight and trying to maintain mechanical properties, other programs, called mesostructure, trusses, lattices or lattice design tools are appearing, mainly oriented to powder bed technologies, which allow for modifying solids by generating lattices or trusses with different geometric characteristics that max- imize properties, reducing weight significantly. These tools present methods for the defi- nition of these mesostructures, controlling their densities, and are even able to define the mass center of the pieces. Programs like Netfabb (Autodesk, United States), 3-Matic (Ma- terialise, Belgium) or Simpleware (Synopsys, United States), or the renewed nTop suite (Ntopology, United States), usually incorporate the simulation of the optimized parts for verification of the modifications, again without considering the laminar character of the process and the anisotropy of the parts. The identification of problems prior to 3D printing using simulation tools is a key factor for the correct implementation of these technologies. The deformation of the parts Appl. Sci. 2021, 11, 1571 5 of 12

also processes defined in traditional CAE tools, such as finite element calculation software Ansys (Ansys Inc., Canonsburg, PA, USA), Abaqus (Dassault Systèmes, Vélizy-Villacoublay, France), Comsol (Comsol Group, Stockholm, Sweden) or Nastran (Autodesk, San Rafael, CA, USA), HyperWorks (Altair, Troy, NY, USA), which usually incorporate the simulation of the optimized parts for verification of the modifications, although they do not consider the anisotropic behavior of the printed parts. We differentiate in this section the topological optimization tools, continuous and discrete, differentiated according to the type of algo- rithm and the way of locating the load vectors. The first is based on continuous volumes and the second on systems of beams interconnected to the points that are subjected to maximum stress. The most used algorithms for the optimization of these structures are the solid isotropic microstructure with penalty (SIMP) algorithm and the bidirectional evolutionary struc- tural optimization (BESO) algorithm [24]. The established algorithms for topological optimization focus on conventional manufacturing systems and can be used in additive manufacturing if the constraints, usually volumetric and strain energy, are minimized. Currently, TO is used in different sectors, such as wind [25] and automotive sectors [26] or the redesign of casting parts [27]. Additionally, one of the latest trends in TO is the use of a topology optimization algorithm while considering the space–time of the process. This concept has been well implemented in the bridge created by MX3D [28]. The process considered the evolution of the structure to self-support the weight of two robotic arms during the manufacturing, using wire arc additive manufacturing (WAAM) technology. With the same objective of minimizing weight and trying to maintain mechanical properties, other programs, called mesostructure, trusses, lattices or lattice design tools are appearing, mainly oriented to powder bed technologies, which allow for modifying solids by generating lattices or trusses with different geometric characteristics that maximize properties, reducing weight significantly. These tools present methods for the definition of these mesostructures, controlling their densities, and are even able to define the mass center of the pieces. Programs like Netfabb (Autodesk, San Rafael, CA, USA), 3-Matic (Materialise, Lovaina, Belgium) or Simpleware (Synopsys, San Jose, CA, USA), or the renewed nTop suite (Ntopology, New York, NY, USA), usually incorporate the simulation of the optimized parts for verification of the modifications, again without considering the laminar character of the process and the anisotropy of the parts. The identification of problems prior to 3D printing using simulation tools is a key factor for the correct implementation of these technologies. The deformation of the parts by thermomechanical processes or warping, together with the accumulation of tensions, inform us about the stability and success of the printing, with these being the main bottle- necks that block the wide expansion of these technologies. The advances in the materials and the design will allow the best control of these processes. However, the correct simula- tion of the 3D printing processes will help in the early detection of possible errors, with notable savings in materials and time [29]. The simulation of printing processes is a novel process that is still in its early stages of development. There is further development within metal AM technologies, especially for powder bed fusion processes, and not for direct energy deposition or powder bed fusion processes, notably the tools Simufact™, Ansys or Netfabb. However, in March 2017, the first commercial tool for the simulation of polymer materials processes appeared, Digimat (e-Xstream). Until then, the only existing developments were for metals. By means of these simulations, we can calculate the geometric deformations of the printed parts, as well as the residual stresses, once the printing process is completed. These process simulations allow us to obtain different types of information: (i) they allow optimizing the process parameters to minimize the accumulated tensions and the deformations of the pieces, during and after printing; (ii) they allow us to determine the most suitable printing position; (iii) they allow us to determine the characteristics of the material that better adapt to the printing process; or (iv) they allow the optimization of the support structures. Appl. Sci. 2021, 11, 1571 6 of 12

All these processes bring the solution closer to the optimum solution as the parameters are modified. These tools also allow for integration with other finite element calculation systems, which will make it possible to predict the behavior of printed parts subjected to the loads and contour restrictions of the parts in service, taking into account the deformations and stresses of the parts once they have been produced. The pre-production tools include different solutions that go through the revision and repair of the 3D printing files obtained from the three-dimensional model, generally of the STL type, where the polygons define the 3D model, ensuring closed surfaces and that the normal is correctly oriented. Examples of programs in this line are MeshMixer (Autodesk, San Rafael, CA, USA) MeshFix and MeshLab (Visual Computer Lab, Pisa, Italy); some are private and others are free pieces of software that are available and executable online. On the other hand, following the same line of free and private software, there are tools that help to manage production by optimizing the use of printing volume or by defining support structures, where necessary, that facilitate subsequent post-processing and space utilization. Examples are Netfabb, Magics or the application for powder bed fusion AM by Delmia (Dassault Systèmes, Vélizy-Villacoublay, France). At this point, we cannot leave aside essential tools in the process of AM. These are the slicers or software that transform the geometric models in the machine code. There are free and private software tools; we highlight Cura (Ultimaker, Utretch, The Netherlands), Slicer3D (Harvard, US) and Simplify 3D (Cincinnati, OH, USA), and the main difference is the control possibilities, with these last ones offering more control options and the recreation of the 3D printing process in virtual media. This functionality helps in the early detection of printing errors. In these applications, it is possible to carry out an exhaustive control of the position, size and orientation of the piece as well as a multitude of process control variables, from the most essential ones, such as layer height, temperature and printing speed, to other more specific ones, such as the speed and retraction of the material in fused filament fabrication (FFF) processes. In Table1, a summary of the described tools that cover different needs and design approaches to exploit the capabilities of AM throughout the design, simulation and pre- production processes is described. This list intends to give an overview to different stakeholders and other researchers to understand the capabilities and different metrics of the tools, in order to facilitate the decision-making process of selecting a specific tool that could match their specific need. In this table, specific software descriptions are given with the main function of every tool, its relation to AM, whether it is directly related or not, the characteristics of usability, the complexity of the tool and price.

Table 1. List of remarkable software used in additive manufacturing design processes.

Scheme Oriented to AM Main Functions Related to AM Ease of Use Cost * SolidWorks/Inventor/ Not specifically but Solid and surface parametric Easy Medium PTC Creo/ useful modeling and basic FEA Solid and surface modeling/Basic Low/Free student NX/Fusion360 Yes Easy simulation version Not specifically but Free CAD Solid and surface modeling Medium Free useful Catia Yes Solid and surface modeling Easy High Not specifically but Rhinoceros 3D Surface and freeform modeling Easy Low useful Not specifically but Organic modeling and animation Medium Free useful Not specifically but Medium/Free 3D Max Organic modeling and animation Medium useful student version Appl. Sci. 2021, 11, 1571 7 of 12

Table 1. Cont.

Scheme Oriented to AM Main Functions Related to AM Ease of Use Cost * Optimization/Lattice/Simulation/ Medium/Free Inspire Yes Easy Printing setup student version Abaqus, HyperWorks, Not specifically but Simulations and TO Complex High Ansys useful Basic model- Medium/Free Ntop Yes ing/Lattice/TO/Simulation/Printing Complex student version setup Modeling/Lattice/Mesh 3D Matic Yes Medium Medium editor/Topology optimization Netfabb Yes Lattice/Mesh editor Medium High Pareto Yes TO Low Medium Tosca Yes TO and printing setup Medium High Paramatters Yes TO Low Low Digimat AM Yes Process simulation (polymers) Low Medium Simufact Yes Process simulation (metals) High High Alphastar Yes FEA/Process simulation Medium High Process condition definition and Cura/Prusa Slicer Yes Low Free G-code generation Process condition definition and Simplify3D Yes Medium Low G-code generation Meshmixer Yes Mesh edition Low Free Mesh edition, process conditions Magics Yes Low High definition and G-code generation * Cost is an estimation from the academic environment based on a comparative analysis. Suppliers give specific quotations depending on final use. They can change depending on whether the client belongs to industry, academia or a research center. Note: TO (Topological Optimization).

4. Results and Discussion. Case Study: A Bicycle Stem Next, the case study design of a bicycle stem will be presented. This part is exposed to different loads and is optimized with two different strategies that will create a more efficient design. The part will undergo a topology optimization process and a lattice approach redesign. The goal of both processes is to reduce the part’s weight while preserving the defined mechanical requirements. There are several publications that show the design process with advanced tools for additive manufacturing. The application of topological optimization in different aero- nautical supports [30] or in classical mechanical elements such as beams or hooks is very common [31,32]. Different studies show the possibilities of lattice structures regarding their behavior and mechanical properties. However, there are not many specific applications or study cases that illustrate the use of these tools for specific cases in terms of their procedure of use and execution with the combined use of these design tools [33]. The bicycle stem has maximum dimensions of 95 mm, and is loaded with to two main loads of 1500 N that simulate the weight of the user, increasing up to 3000 N to consider possible jumps or overloads, as shown in Figure4. The bicycle stem also contains screws that are simulated with a load of 100 N in every hole due to the screw pressure and the pressure direction simulates the tightness of the screws. It also has a restriction of movement in all degrees of freedom due to the connection to the bicycle frame. The material selected for the manufacture and redesign of the part is polyamide 6 or nylon, due to its mechanical strength, hardness, rigidity and good toughness, in addition to a strong mechanical damping capacity and good resistance to fatigue and wear. Appl. Sci. 2021, 11, x FOR PEER REVIEW 8 of 13

There are several publications that show the design process with advanced tools for additive manufacturing. The application of topological optimization in different aeronau- tical supports [30] or in classical mechanical elements such as beams or hooks is very com- mon [31,32]. Different studies show the possibilities of lattice structures regarding their behavior and mechanical properties. However, there are not many specific applications or study cases that illustrate the use of these tools for specific cases in terms of their pro- cedure of use and execution with the combined use of these design tools [33]. The bicycle stem has maximum dimensions of 95 mm, and is loaded with to two main loads of 1500 N that simulate the weight of the user, increasing up to 3000 N to consider possible jumps or overloads, as shown in Figure 4. The bicycle stem also contains screws that are simulated with a load of 100 N in every hole due to the screw pressure and the pressure direction simulates the tightness of the screws. It also has a restriction of move- ment in all degrees of freedom due to the connection to the bicycle frame. The material

Appl. Sci. 2021, 11, 1571 selected for the manufacture and redesign of the part is polyamide 6 or nylon, due to its 8 of 12 mechanical strength, hardness, rigidity and good toughness, in addition to a strong me- chanical damping capacity and good resistance to fatigue and wear.

Figure 4. Main dimensions of the bicycle stem designed in the software SolidWorks™. Figure 4. Main dimensions of the bicycle stem designed in the software SolidWorks™. The initial design was developed with SolidWorks, a parametric design tool, for the The initial design was developed with SolidWorks, a parametric design tool, for the problem specifications. Through simple sketching and basic modeling operations, we can problem specifications. Through simple sketching and basic modeling operations, we can configure the geometry. This will be the starting point for the redesign of the part. The file configure the geometry. This will be the starting point for the redesign of the part. The file was exported in STEP format, which allows its import into the Inspire™ tool of Altair™. was exportedThis topology in STEP optimization format, which tool allows is intuitive its import and into useful the forInspire™ novel userstool of and Altair™. works with This topologythe same optimization calculation tool engine is intuitive as the HyperWorks and useful for tool novel from users the sameand works company, with asthe well as same calculationthe OptiStruct engine software as the solver.HyperWorks The first tool action from forthe asame TO approachcompany, consists as well as of assigningthe OptiStructthe materialsoftware from solver. the The library first to action the imported for a TO pieces approach and, asconsists we have of mentioned,assigning the it will be materialpolyamide from the 6.library It is importantto the imported to define piec withines and, the as assembly we have whichmentioned, volumes it will will be be used polyamidefor optimization 6. It is important and to which define will within not. Wethe willassembly refer towhich the optimizable volumes will volumes be used wherefor the Appl. Sci. 2021, 11, x FOR PEER REVIEW 9 of 13 optimizationmaterial and removal which happenswill not. We “design will refer spaces” to the and optimizable those that cannotvolumes be where altered the “non-design ma- terial removalspaces”, happens as illustrated “design in Figure spaces”5. Theand volumethose that of the cannot design be spacesaltered will “non-design be increased as spaces”,much as illustrated as possible in to Figure allow 5. the The solver volume to identify of the thedesign most spaces suitable will solution. be increased as much as possible to allow the solver to identify the most suitable solution.

Figure 5. Definition of loads and constraints, as well as design and non-design spaces in the Inspire™ Figuretool for 5. theDefinition modified of stemloads geometry. and constraints, as well as design and non-design spaces in the In- spire™ tool for the modified stem geometry. The first step is to perform a static stress calculation according to the defined loads to verifyThe first that step the is part to meetsperform the a objectivesstatic stress and, calculation above all, according that the to parts the havedefined room loads for toimprovement verify that the for part subsequent meets the redesign. objectives We make and, aabove stress all, simulation that the andparts observe have room the safety for improvementcoefficient of eachfor subsequent of the parts redesign. of the piece, We as ma illustratedke a stress in Figuresimulation6. and observe the safety coefficient of each of the parts of the piece, as illustrated in Figure 6.

Figure 6. Result of the finite elements analysis expressed as safety factors of the part using the Inspire™ tool.

The result clearly expresses that the part is susceptible to optimization since the val- ues of the safety factor greatly exceed a factor of 1.2 that we accept as the admissible limit. Once the need to reduce the mass of this part has been determined, we define a topological optimization that maintains the mentioned safety factor of 1.2, minimizing the mass and maximizing the rigidity of the part. The result will be a poorly defined organic geometry that we will reconstruct using NURBS surfaces that help us to generate a continuous and well-defined surface, as illustrated in Figure 7. This result will also be analyzed by a static calculation to validate the adopted design solution. With this approach to the redesign of the piece, a notable decrease in weight has been achieved, going from 46.36 g to 24.93 g, which mean a reduction of 53.8% in the optimized piece without losing functionality and according to the design specifications defined at the beginning. Again, this solution is validated by means of finite element analysis (FEA) Appl. Sci. 2021, 11, x FOR PEER REVIEW 9 of 13

Figure 5. Definition of loads and constraints, as well as design and non-design spaces in the In- spire™ tool for the modified stem geometry.

The first step is to perform a static stress calculation according to the defined loads to verify that the part meets the objectives and, above all, that the parts have room for Appl. Sci. 2021, 11, 1571 improvement for subsequent redesign. We make a stress simulation and observe 9the of 12 safety coefficient of each of the parts of the piece, as illustrated in Figure 6.

FigureFigure 6. Result 6. Result of the of thefinite finite elements elements analysis analysis expre expressedssed as safety as safety factors factors of the ofpart the using part the using the Inspire™Inspire™ tool. tool.

TheThe result result clearly clearly expresses expresses that that the the part part is is susceptible susceptible to optimization sincesince thethe valuesval- uesof of the the safety safety factor factor greatly greatly exceedexceed aa factor of 1.2 1.2 that that we we accept accept as as the the admissible admissible limit. limit. OnceOnce the the need need to toreduce reduce the the mass mass of ofthis this part part has has been been determined, determined, we we define define a topological a topological Appl. Sci. 2021, 11, x FOR PEER REVIEW 10 of 13 optimizationoptimization that that maintains maintains the the mentioned mentioned safety safety factor factor of of1.2, 1.2, minimizing minimizing the the mass mass and and maximizingmaximizing the the rigidity rigidity of ofthe the part. part. The The result result will will be be a poorly a poorly defined defined organic organic geometry geometry thatthat we we will will reconstruct reconstruct using using NURBS NURBS surfaces surfaces that that help help us us to to generate generate a continuous a continuous and and well-definedtools.well-defined This solutionsurface, surface, asnot as illustrated illustratedonly will in reduce in Figure Figure costs 7.7 .This This and result result production will will also also times be be analyzed analyzed but can by byalso a astatic staticmean calculationimportantcalculation to savings tovalidate validate in theenergy the adopted adopted consumption design design solution. solution.with the use of the redesigned part. With this approach to the redesign of the piece, a notable decrease in weight has been achieved, going from 46.36 g to 24.93 g, which mean a reduction of 53.8% in the optimized piece without losing functionality and according to the design specifications defined at the beginning. Again, this solution is validated by means of finite element analysis (FEA)

Figure 7. Result of the topological optimization on the left, the mi middleddle image shows the highest stress concentration areas and, on the right, the smoothed surface usingusing NURBS, carried out with InspireInspire software.software.

ThisWith optimized this approach model to the is intended redesign ofto thetake piece, a further a notable step decreasetowards inweight weight reduction. has been Usingachieved, the goinglattice fromtools 46.36 that have g to 24.93 already g, which been mentioned mean a reduction and, more of 53.8% precisely, in the Ntop optimized soft- ware,piece withoutwe intend losing to further functionality reduce andthe accordingweight by toreplacing the design the specifications continuous material defined of at the partbeginning. of the piece Again, that this can solution be optimized is validated by generating by means ofa finitemicrostructure element analysis of trusses (FEA) without tools. losingThis solution mechanical not only properties will reduce and costsmaintaining and production its resistance. times It but is canimportant also mean to emphasize important thatsavings the intools energy used consumption do not allow with the validation the use of theof the redesigned results by part. means of calculation by finiteThis elements. optimized The simulation model is intended strategy shou to takeld be a further based on step a mult towardsiscale weight homogenization reduction. basedUsing on the the lattice analysis tools thatof a haverepresentative already been volu mentionedme element. and, Therefore, more precisely, the result Ntop presented software, belowwe intend is merely to further illustrative reduce of the the weight redesign by replacing process for the mesostructure continuous material gratings. of the part of the pieceThe import/export that can be optimized of files is by again generating done with a microstructure STEP files. The of lattice trusses structure without will losing be appliedmechanical in the properties main bodies and in maintaining a combination its resistance. of a shell operation It is important and the to internal emphasize lattices. that Ntopthe tools software used dooffers not a allow wide therange validation of structures of the to results be applied, by means which of are calculation different by in finitetheir geometryelements. and The are simulation structured strategy by continuous should be be basedams onor walls, a multiscale which homogenizationcan be hexagonal, based tet- rahedral,on the analysis cubic ofor arandom, representative among volume others, element.with different Therefore, configurations the result presentedof each of below their definitions.is merely illustrative In this case, of thewe apply redesign a specific process structure, for mesostructure octec, that gratings. is an octahedral structure with only eight beams. The result is a 2 mm shell that covers the entire part together with a wired structure infill that will allow, depending on the load requirements, a certain thickness that can also be variable. This allows us to modify the density of the piece by region and even define the position of the center of mass of the part. The steps followed to obtain the lattice structure, illustrated in Figure 8, are (i) deter- mination of the optimization area, in this case the central body of the bicycle stem. (ii) Definition of the shell thickness and type and size of the structure. (iii) Modification of the wire structure to ensure that there is connection to the parts, and that there are no open structures that reduce their mechanical characteristics. (iv) Definition of the thickness of the cellular structure or lattice, in this case, 1 mm in diameter for each segment. (v) The Boolean union of all the parts that will provide a continuous piece capable of being printed. (vi) Finally, the exportation of the new part in a printable file, such as STL. Appl. Sci. 2021, 11, 1571 10 of 12

The import/export of files is again done with STEP files. The lattice structure will be applied in the main bodies in a combination of a shell operation and the internal lattices. Ntop software offers a wide range of structures to be applied, which are different in their geometry and are structured by continuous beams or walls, which can be hexagonal, tetrahedral, cubic or random, among others, with different configurations of each of their definitions. In this case, we apply a specific structure, octec, that is an octahedral structure with only eight beams. The result is a 2 mm shell that covers the entire part together with a wired structure infill that will allow, depending on the load requirements, a certain thickness that can also be variable. This allows us to modify the density of the piece by region and even define the position of the center of mass of the part. The steps followed to obtain the lattice structure, illustrated in Figure8, are (i) de- termination of the optimization area, in this case the central body of the bicycle stem. (ii) Definition of the shell thickness and type and size of the structure. (iii) Modification of the wire structure to ensure that there is connection to the parts, and that there are no open structures that reduce their mechanical characteristics. (iv) Definition of the thickness of the cellular structure or lattice, in this case, 1 mm in diameter for each segment. (v) The Appl. Sci. 2021, 11, x FOR PEER REVIEWBoolean union of all the parts that will provide a continuous piece capable of being printed.11 of 13

(vi) Finally, the exportation of the new part in a printable file, such as STL.

FigureFigure 8.8. SectionSection view view of of the the result result of ofthe the redesign redesign using using lattice-type lattice-type tools tools with with Ntop Ntop platform platform software.software.

TheThe result, as observed observed in in Figure Figure 7,7 ,presen presentsts a atopology-optimized topology-optimized geometry geometry that that has hasreduced reduced weight weight due dueto the to application the application of the of octec the octeclattice, lattice, while maintaining while maintaining the perfor- the performancemance of the ofproduct, the product, with lower with lower weight, weight, production production time and time cost. and cost.

5.5. ConclusionsConclusions ThisThis articlearticle presents presents an an introduction introduction to to design design for for additive additive manufacturing, manufacturing, illustrating illustrat- theing mainthe main advantages advantages and and disadvantages disadvantages of of these these technologies technologies along along with with the the different different stagesstages thatthat make up up the the process. process. The The main main part part consists consists ofof a review a review and and explanation explanation of the of thedifferent different tools tools involved involved in each in each stage stage of the of process, the process, focusing focusing on additive on additive manufacturing manufac- turingdesign. design. In this Inway, this different way, different computer-aided computer-aided design designtools are tools presented. are presented. Some of Some these oftools these are tools well areknown well in known the scientific in the scientificand engineering and engineering community, community, while other, while less other,tradi- lesstional traditional tools, are tools, new areand new exclusive and exclusive for desig forn designoriented oriented to additive to additive manufacture. manufacture. These Thesetools, tools,in their in application, their application, will allow willallow us to usextract to extract the maximal the maximal capacities capacities of these of these pro- processes,cesses, when when it is it a is question a question of obtaining of obtaining robust robust and and light light design design for forpieces pieces that that need need re- reducedduced masses. masses. Likewise, Likewise, this this article article illustrates illustrates the the redesign redesign process oriented towardstowards thethe additiveadditive manufacturemanufacture ofof aa characteristiccharacteristic partpart ofof mechanicalmechanical design:design: aa bicyclebicycle stem.stem. InIn thisthis process, significant improvements in mass reduction are achieved through the application of topological and mesostructural optimization tools, illustrating their use step by step.

Author Contributions: Both authors, Daniel Moreno Nieto and Daniel Moreno Sánchez partici- pated in conceptualization, methodology, software, validation, formal analysis, investigation, re- sources, data curation, writing—original draft preparation, writing—review and editing, visualiza- tion, supervision, project administration and funding acquisition. All authors have read and agreed to the published version of the manuscript.” Funding: This research received no external funding Institutional Review Board Statement: The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Review Board Informed Consent Statement: Informed consent was obtained from all subjects involved in the study Data Availability Statement: No new data were created or analyzed in this study. Data sharing is not applicable to this article. Conflicts of Interest: The authors declare no conflict of interest. Acknowledgements: The authors would like to acknowledge the support of Junta de Andalucía (INNANOMAT research group, TEP946) and the department of mechanical engineering and indus- trial design at the Engineering School from Cadiz University. Appl. Sci. 2021, 11, 1571 11 of 12

process, significant improvements in mass reduction are achieved through the application of topological and mesostructural optimization tools, illustrating their use step by step.

Author Contributions: Both authors, D.M.N. and D.M.S. participated in conceptualization, method- ology, software, validation, formal analysis, investigation, resources, data curation, writing—original draft preparation, writing—review and editing, , supervision, project administration and funding acquisition. All authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding. Institutional Review Board Statement: The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Review Board. Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. Data Availability Statement: No new data were created or analyzed in this study. Data sharing is not applicable to this article. Acknowledgments: The authors would like to acknowledge the support of Junta de Andalucía (IN- NANOMAT research group, TEP946) and the department of mechanical engineering and industrial design at the Engineering School from Cadiz University. Conflicts of Interest: The authors declare no conflict of interest.

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