Design and Fabrication of a Lightweight Cantilever Beam Using Topology Optimization and Material-Extrusion Additive Manufacturing

Design and Fabrication of a Lightweight Cantilever Beam Using Topology Optimization and Material-Extrusion Additive Manufacturing | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Design and Fabrication of a Lightweight Cantilever Beam Using Topology Optimization and Material-Extrusion Additive Manufacturing ALVI AHMMED This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8704572/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Topology optimization (TO) combined with additive manufacturing (AM) enables the fabrication of lightweight structural components with prescribed load paths that are often difficult or impractical to achieve using conventional manufacturing. In this study, a cantilever-style beam subjected to a 0.5 kg end load was designed, optimized, and fabricated using material-extrusion additive manufacturing. A maximum-stiffness topology optimization with a prescribed mass-reduction constraint was performed using Altair Inspire, followed by manual CAD reconstruction to enforce manufacturability while preserving optimized load paths. The final design was fabricated with polylactic acid (PLA) using fused filament fabrication (FFF) without support structures. Finite element analysis predicted a peak von Mises stress of 7.02 MPa and a maximum displacement of 8.24 mm, corresponding to a factor of safety exceeding 7 relative to PLA yield strength. Compared to the initial design, the optimized beam achieved an 80% mass reduction while successfully supporting the applied load during physical testing. A comparative cost analysis further demonstrated that additive manufacturing reduced unit production cost by approximately 57% relative to conventional CNC machining for this geometry. The results highlight the effectiveness of integrating TO with extrusion-based additive manufacturing for producing structurally efficient, low-cost components. Mechanical Engineering Topology Optimization beam altair Inspire 3D printing additive manufacturing Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Lightweight structural design is a central objective in modern engineering applications spanning aerospace, automotive, marine, and mechanical systems, where reductions in mass directly translate to improved efficiency, reduced material consumption, and lower manufacturing costs. Additive Manufacturing (AM), in this regard has become a possible alternative to traditional manufacturing as it overcomes the limitations of conventional manufacturing processes enabling more geometric freedom. Fused Filament Fabrication (FFF) in particular, due to its potential in fabrication of lightweight structures and open volume structures without need of post processing as required by other AM has gained popularity in various sectors [ 1 ], [ 2 ], [ 3 ], [ 4 ], [ 5 ], [ 6 ], [ 7 ]. In the context of lightweight structure fabrication, Topology optimization (TO) has emerged as a powerful design methodology for achieving lightweight yet mechanically robust structures by determining the optimal material distribution within a prescribed design space under given loads and boundary conditions. Unlike traditional shape or size optimization, topology optimization allows the removal of nonessential material, yielding highly efficient load paths that are often nonintuitive. Foundational work by Bendsøe and Sigmund established the theoretical framework for stiffness-based topology optimization, enabling widespread adoption across structural engineering disciplines [ 8 ]. Subsequent developments and reviews have further refined these methods and clarified their numerical and practical limitations [ 9 ], [ 10 ]. Furthermore, the synergy between TO and AM has been widely recognized in recent years resulting in various studies demonstrating that TO-derived geometries are particularly well-suited for AM processes [ 11 ], [ 12 ], [ 13 ]. However, challenges remain in translating raw topology optimization outputs into manufacturable designs, especially for extrusion-based processes that impose constraints on feature size, overhang angles, and layer-by-layer deposition [ 13 ]. Additionally, while FFF has several advantages over traditional manufacturing, it exhibits anisotropic mechanical behavior, driven primarily by interlayer bonding quality and thermal history during deposition [ 14 ], [ 15 ]. These effects are especially pronounced in load-bearing components such as beams, where print orientation and thermal management directly influence stiffness and strength. Polylactic acid (PLA) is commonly used in FFF due to its biodegradability, dimensional stability, and relatively high stiffness, making it suitable for structural prototypes and low-load applications [ 16 ]. Recent studies have shown that enforcing manufacturability constraints, such as minimum feature thickness, self-supporting geometries, and print orientation during or after topology optimization is essential to ensure successful fabrication and reliable performance [ 12 ], [ 17 ]. As a result, many practical workflows rely on a hybrid approach, in which topology optimization is followed by manual or semi-automated CAD reconstruction to preserve optimized load paths while satisfying manufacturing limitations. In this work, a cantilever-style beam subjected to a fixed end load is designed, optimized, and fabricated using a combined topology optimization and material-extrusion additive manufacturing workflow. A maximum-stiffness topology optimization with a prescribed mass-reduction target is performed using Altair Inspire, followed by manual CAD reconstruction to ensure printability without support structures. The optimized design is evaluated through finite element analysis, fabricated using fused filament fabrication in PLA, and experimentally validated under load. In addition, a cost comparison between additive manufacturing and conventional CNC machining is conducted to assess economic feasibility. This study demonstrates a practical, end-to-end framework for integrating topology optimization with extrusion-based additive manufacturing to achieve substantial mass reduction while maintaining structural performance. Methodology This study follows a systematic workflow integrating topology optimization, finite element analysis, and FFF to design, fabricate, and validate a lightweight cantilever beam. The methodology consists of five primary stages: (i) problem definition and baseline geometry creation, (ii) topology optimization, (iii) CAD reconstruction for manufacturability, (iv) numerical validation, and (v) fabrication and experimental evaluation. Problem Definition and Baseline Geometry The design objective was to develop a self-supporting cantilever-style beam capable of sustaining a concentrated end load of 0.5 kg (approximately 1 lb) while minimizing structural mass within predefined geometric constraints. The beam was fixed at its base, and the applied load acted normal to the top surface at the free end. These boundary conditions represent a common loading scenario encountered in lightweight support brackets and structural arms. An initial baseline geometry was created using SolidWorks, ensuring compliance with the prescribed design envelope and manufacturability considerations (Figure: 1). This initial design served as both a structural reference and a benchmark for evaluating the effectiveness of topology optimization. The baseline geometry was analyzed under the specified loading conditions to establish reference values for stress, displacement, and mass. Topology Optimization Framework Topology optimization was performed using Altair Inspire 2024, employing a density-based approach with a maximum stiffness objective. The optimization aimed to remove non-load-bearing material while maintaining structural rigidity under the applied load. The design space was defined as the upper horizontal portion of the beam, while the base and load interface regions were excluded to preserve functional interfaces. The material was specified as polylactic acid (PLA), with linear elastic behavior assumed for optimization and analysis. A mass reduction target of 15% was imposed during optimization to guide material removal while preventing excessive compliance. In addition, minimum and maximum feature thickness constraints of 6 mm and 12 mm, respectively, were enforced to avoid slender members that could compromise printability or mechanical stability. Upon convergence, the topology optimization produced an organically shaped geometry highlighting primary load paths between the fixed support and the load application point. While structurally efficient, the raw optimization output contained irregular surfaces and thin features unsuitable for direct fabrication via fused filament fabrication. CAD Reconstruction for Manufacturability To ensure manufacturability while preserving optimized load paths, the topology-optimized geometry was manually reconstructed using SolidWorks. This reconstruction process involved interpreting the material distribution suggested by the optimizer and redesigning the geometry using smooth, continuous features with uniform wall thickness. Special attention was given to eliminating unsupported overhangs, sharp transitions, and excessively thin members to enable support-free printing. The reconstructed design maintained symmetry and consistent cross-sections where possible, improving both structural reliability and print quality. This hybrid optimization–reconstruction approach balances computational efficiency with practical manufacturing constraints inherent to material extrusion processes. Numerical Validation Finite element analysis (FEA) was conducted on both the baseline and optimized designs to evaluate structural performance. The same boundary conditions and loading configurations used during topology optimization were applied for consistency. Linear static analysis was performed to compute von Mises stress distributions and maximum displacement. For the optimized beam, the numerical results were assessed against the material yield strength of PLA to determine the factor of safety. Displacement values were also examined to ensure that deflections remained within acceptable limits for functional use. This numerical validation step confirmed that the optimized geometry met both strength and stiffness requirements despite significant mass reduction. Fabrication and Experimental Evaluation The finalized CAD model was exported as a stereolithography (STL) file and processed using Ultimaker Cura slicing software. The beam was fabricated using an Ender 3 S1 Pro printer with a 0.4 mm nozzle diameter and a layer height of 0.2 mm. The part was printed with 100% infill to isolate geometric effects from infill-related variability. No support structures were used. Printing was conducted at a nozzle temperature of 200 °C and a build plate temperature of 60 °C. The print orientation was selected to maximize structural stability and interlayer bonding in the primary load-bearing direction. After fabrication, the printed beam was subjected to a physical load test using a 0.5 kg mass applied at the free end to verify structural integrity and deformation behavior. Table 1 summarizes the process parameters used. Table 1 : Process Parameter Parameter Layer Height (mm) Line Width (mm) Infill (%) Nozzle Temperature (°C) Bed Temperature (°C) Value 0.2 0.46 100 200 60 Cost Comparison Method To evaluate economic feasibility, a comparative cost analysis was performed between additive manufacturing and conventional CNC machining. Cost components included material consumption, energy usage, labor time, machine depreciation, and tooling requirements. The additive manufacturing cost model reflects low material waste and minimal tooling, while the CNC machining model accounts for higher labor and equipment costs. This comparison provides insight into the suitability of additive manufacturing for producing topology-optimized structural components. Results and Discussion Topology Optimization Outcome The topology optimization process successfully identified an efficient material distribution that preserved the primary load paths between the fixed support and the load application region while eliminating non-essential material. The optimized geometry exhibits a truss-like configuration with smoothly transitioning members, characteristic of stiffness-driven topology optimization under cantilever loading. Compared to the baseline design, the optimized structure concentrates material along tensile and compressive stress trajectories, confirming the effectiveness of the maximum-stiffness objective in promoting mechanically efficient layouts (Figure: 2). Although the optimization was constrained to a modest mass reduction target during computation, the resulting geometry enabled substantially greater material savings after CAD reconstruction. This outcome highlights an important practical insight: topology optimization often provides a qualitative guide to load transfer rather than a directly manufacturable shape, and additional mass reduction can be achieved through informed geometric refinement without sacrificing performance. Numerical Performance Comparison Finite element analysis reveals a clear trade-off between mass reduction and structural response. The baseline beam exhibited a maximum von Mises stress of approximately 3.2 MPa and a maximum displacement of 4.16 mm under the applied load. In contrast, the optimized beam experienced a higher peak stress of 7.02 MPa and a maximum displacement of 8.24 mm. While these values represent an increase relative to the baseline design, they remain well below the yield strength of PLA, taken conservatively as 50 MPa. Despite the increase in stress and displacement, the optimized design maintains a factor of safety exceeding 7, indicating that the structure remains firmly within the elastic regime. The increase in compliance is an expected and acceptable consequence of aggressive mass reduction and reflects the classic stiffness–weight trade-off inherent to lightweight structural design. Importantly, the stress distribution in the optimized beam is more uniform than in the baseline design, suggesting improved load sharing and reduced stress concentrations. Table 2 provides summary of the design comparison. Table 2 : Comparative analysis of designs Design Volume (cm 3 ) Mass (g) Max von-Mises Stress (Mpa) Max Displacement (mm) Mass Reduction (%) Initial Beam 231.00 288.75 3.20 4.16 80 Optimized Beam 45.88 57.25 7.02 8.24 Mass Reduction and Structural Efficiency One of the most significant outcomes of this study is the achieved mass reduction of approximately 80%, with the optimized beam mass reduced from 288.75 g to 57.25 g. This dramatic reduction underscores the effectiveness of combining topology optimization with manual CAD reconstruction. When evaluated in terms of structural efficiency defined as load-carrying capability per unit mass the optimized beam demonstrates a substantial improvement over the baseline design. Such efficiency gains are particularly relevant for applications where weight is a critical constraint, including aerospace brackets, lightweight fixtures, and support arms. The results demonstrate that extrusion-based additive manufacturing, despite its material and geometric limitations, can successfully realize highly efficient topology-optimized structures when design intent and process constraints are properly aligned. Experimental Validation Physical testing of the fabricated beam confirmed the numerical predictions. The optimized structure successfully supported the applied 0.5 kg load without visible cracking, fracture, or excessive deformation. The observed deformation pattern qualitatively matched the displacement contours predicted by finite element analysis, with maximum deflection occurring near the free end of the beam (Figure 4 c). The agreement between simulation and experiment suggests that the assumptions used in the numerical model linear elastic material behavior and idealized boundary conditions are reasonable for the loading regime considered. Moreover, the absence of failure or instability during testing indicates that the reconstructed geometry effectively preserved the critical load paths identified during topology optimization. Additive Manufacturing Considerations The optimized beam was fabricated without support structures, demonstrating that topology-optimized designs can be successfully adapted for support-free material extrusion when manufacturability is explicitly considered during reconstruction. The use of 100% infill eliminated internal porosity effects, allowing the mechanical response to be dominated by geometry rather than infill architecture. However, the results also highlight limitations intrinsic to fused filament fabrication. The increased displacement observed in the optimized design may be partially attributed to interlayer compliance and anisotropy inherent to layer-by-layer deposition. While these effects did not compromise structural integrity in this study, they may become more critical under higher loads or cyclic loading conditions. Future work incorporating enhanced thermal management or alternative raster strategies could further improve stiffness and interlayer bonding [18], [19], [20]. Table 3 : Cost Comparison between methods Cost Breakdown for AM Cost Type Cost Per Unit Total Unit Cost Material Cost (PLA) $20/kg 0.06 kg $1.2 Energy Cost (Machine) $0.2/kWh 0.84 kWh $0.16 Labor Cost $20/hr 2 hr $40 Machine Depreciation $0.1/hr 9 hr $0.9 Total Cost $42.26 Cost Breakdown for CNC Cost Type Cost Per Unit Total Unit Cost Material Cost (Aluminium) $12/kg 0.12 kg $1.44 Energy Cost (Machine) $0.2/kWh 10 kWh $2 Labor Cost $40/hr 2 hr $80 Machine Depreciation $5/hr 2 hr $10 Tool Cost $5/pcs 1 pcs $5 Total Cost $98.44 Cost Performance The cost comparison indicates that additive manufacturing offers a substantial economic advantage for producing the optimized beam geometry. The total unit cost for additive manufacturing was approximately 57% lower than that of conventional CNC machining, driven primarily by reduced labor requirements, minimal material waste, and the elimination of tooling. This cost advantage is particularly significant for low-volume or customized components, where the flexibility of additive manufacturing outweighs its longer build times. The results (Table 3) suggest that topology optimization not only enhances structural efficiency but also amplifies the economic benefits of additive manufacturing by enabling material savings that directly translate to cost reductions. Discussion Summary Overall, the results demonstrate that a combined topology optimization and material-extrusion additive manufacturing workflow can achieve substantial mass reduction while maintaining adequate structural performance and cost efficiency. The optimized beam satisfies strength, stiffness, manufacturability, and economic criteria, validating the proposed design approach. While the study is limited to static loading and a single material system, the methodology is broadly applicable and can be extended to more complex loading scenarios, materials, and optimization objectives. Conclusion This study demonstrated an end-to-end workflow integrating topology optimization, numerical analysis, and material-extrusion additive manufacturing for the design and fabrication of a lightweight cantilever beam. A maximum-stiffness topology optimization was performed to guide material redistribution, followed by manual CAD reconstruction to ensure manufacturability without support structures. The optimized beam achieved an approximately 80% reduction in mass relative to the baseline design while maintaining structural integrity under a 0.5 kg end load. Finite element analysis predicted a peak von Mises stress well below the yield strength of PLA, and experimental testing confirmed the numerical results, validating the effectiveness of the proposed design methodology. Beyond mechanical performance, the study highlighted the economic advantages of additive manufacturing for topology-optimized components. A comparative cost analysis showed that fused filament fabrication reduced production cost by approximately 57% compared to conventional CNC machining for the studied geometry. These results underscore the potential of combining topology optimization with extrusion-based additive manufacturing to produce structurally efficient, low-cost components for low-volume and customized applications. Future work will extend this framework to more complex loading conditions, including dynamic and fatigue loading, to assess long-term durability. Incorporating manufacturability constraints directly within the topology optimization stage such as overhang angle limits and anisotropic material behavior—could further reduce the need for manual reconstruction. In addition, enhanced thermal management strategies during printing may be explored to improve interlayer bonding and stiffness, particularly for slender load-bearing members. Finally, data-driven and machine-learning-assisted optimization approaches may be integrated to accelerate design iteration and enable adaptive parameter selection for improved structural performance. References Y. Abderrafai et al. , “Additive manufacturing and characterization of high temperature thermoplastic blends for potential aerospace applications,” Compos. Sci. Technol. , vol. 231, 2023, doi: 10.1016/j.compscitech.2022.109839. M. Gharibshahian et al. , “Recent advances on 3D-printed PCL-based composite scaffolds for bone tissue engineering,” 2023. doi: 10.3389/fbioe.2023.1168504. E. Cuan-Urquizo and R. Guerra Silva, “Fused Filament Fabrication of cellular, lattice and porous mechanical metamaterials: a review,” 2023. doi: 10.1080/17452759.2023.2224300. R. Ahmed, R. S. Niloy, M. R. Mozumder, and T. A. 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Available: https://www.researchgate.net/publication/388830803_AN_INVESTIGATION_ON_THE_APPLICATIONS_OF_ADDITIVE_MANUFACTURING_IN_THE_MARINE_INDUSTRY R. Wildman, I. Ashcroft, and M. Abdi, “Design optimization for an additively manufactured automotive component,” International Journal of Powertrains , vol. 7, no. 2/3, 2018, doi: 10.1504/ijpt.2018.10009559. M. P. Bendsøe and O. Sigmund, Topology Optimization: Theory, Methods, and Applications , 2nd ed. Berlin, Heidelberg: Springer, 2004. doi: 10.1007/978-3-662-05086-6. G. I. N. Rozvany, “A critical review of established methods of structural topology optimization,” Structural and Multidisciplinary Optimization , vol. 37, no. 3, 2009, doi: 10.1007/s00158-007-0217-0. O. Sigmund, “A 99 line topology optimization code written in matlab,” Structural and Multidisciplinary Optimization , vol. 21, no. 2, 2001, doi: 10.1007/s001580050176. H. Jiang, Z. He, E. Li, and C. 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Kreiger, and J. M. Pearce, “Mechanical properties of components fabricated with open-source 3-D printers under realistic environmental conditions,” Mater. Des. , vol. 58, 2014, doi: 10.1016/j.matdes.2014.02.038. M. Bi, P. Tran, and Y. M. Xie, “Topology optimization of 3D continuum structures under geometric self-supporting constraint,” Addit. Manuf. , vol. 36, 2020, doi: 10.1016/j.addma.2020.101422. P. Patel, R. Ahmed, T. A. Shanto, A. Jain, and R. M. Taylor, “Experimental characterization of enhanced fused filament fabrication (FFF) of tall thin-walled structures using polylactic acid (PLA),” The International Journal of Advanced Manufacturing Technology , vol. 139, no. 11, pp. 5663–5675, 2025, doi: 10.1007/s00170-025-16171-w. T. A. Shanto, M. A. Shahriar, T. Ahmed, M. J. Zulqernine, and R. M. Taylor, “Predicting mechanical strength in FDM printed ABS parts with in-process annealing: A machine learning approach,” in Proceedings of the IISE Annual Conference & Expo 2025 , 2025, pp. 1–6. doi: 10.21872/2025IISE_6734. T. A. Shanto, H. R. Pavel, R. Ahmed, M. Abdullah, and R. M. Taylor, “Leveraging Large Language Models for Process Parameter Optimization in 3D-printed ABS Polymer Specimens,” IISE Annual Conference. Proceedings , pp. 1–6, 2025, doi: https://doi.org/10.21872/2025IISE_6901. Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8704572","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":580806660,"identity":"71a7af59-9d91-4092-80e7-7eb232e4f499","order_by":0,"name":"ALVI AHMMED","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBElEQVRIiWNgGAWjYFACxgcHGBgOgFgGBxL/2YBEGg/g18JsANNi+OADWxpISwNBLQxQLcaGM9gOg8XwajFvP8x4gKHmTrRue/M2aR6e83Zr2w8DbamxicalReZMMtDMY89yt505VibNI3E7eduZRKCWY2m5DTi0SDDkHzjAwHY4d9uNHDNpHoPbyWYHgFoYGw7j1sL/GGjLP6CW+2+AWhLOJZudf0hAiwTQYYxtIFt4gN4/cMDO7AYhWySAtiT2AbWcSSt88LEhOcHsBtCWBHx+4U9m/vDhG1DL8cMbgL6wszc7n/7wwYcaG5xawCABiZ3YgC5CENiTongUjIJRMApGBgAAWw9uH/twKZQAAAAASUVORK5CYII=","orcid":"https://orcid.org/0009-0007-5246-4260","institution":"The University of Texas at Arlington","correspondingAuthor":true,"prefix":"","firstName":"ALVI","middleName":"","lastName":"AHMMED","suffix":""}],"badges":[],"createdAt":"2026-01-27 01:23:45","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-8704572/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8704572/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101283772,"identity":"9cba2ac6-22f1-4d0a-93b6-a4e89c4b539a","added_by":"auto","created_at":"2026-01-28 06:02:08","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":124439,"visible":true,"origin":"","legend":"\u003cp\u003eInitial design constraints that are provided from the beam design. The grey outline indicates the given constraints. All dimensions are in inches\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8704572/v1/79c6878e36e864686725199c.png"},{"id":101296927,"identity":"3de31fd7-5cc4-44b2-9d2c-1f92dd605198","added_by":"auto","created_at":"2026-01-28 09:23:22","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":160868,"visible":true,"origin":"","legend":"\u003cp\u003eThe optimized beam, done by Altair Inspire. The brown region indicates the design space. Reconstructed Geometry based on TO Results.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8704572/v1/2389096b37f6efeebf8966ce.png"},{"id":101283773,"identity":"00e9c515-05cc-4867-a31d-daaf7bdf8131","added_by":"auto","created_at":"2026-01-28 06:02:08","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":119535,"visible":true,"origin":"","legend":"\u003cp\u003eNumerical Analysis of the optimized beam design (a) Displacement (max 8.24mm (b) von-Mises Stress (max 7.02 Mpa)\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8704572/v1/2d6aa1fb6113fc9c81dc4937.png"},{"id":101283775,"identity":"dd651c02-2b49-4467-9b22-2b5b2b15eb1c","added_by":"auto","created_at":"2026-01-28 06:02:08","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":335616,"visible":true,"origin":"","legend":"\u003cp\u003eFinal 3D printed part-(a) During print (b) Printed final part (c) Printed part under load (1 lb)\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8704572/v1/cca4bd958fcc0dfdcaef67b3.png"},{"id":101299102,"identity":"45a1ecdc-2025-46bd-836f-396f35ed4548","added_by":"auto","created_at":"2026-01-28 09:39:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1464659,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8704572/v1/28fbf51f-8d25-4335-8ad4-1198fe4e3531.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eDesign and Fabrication of a Lightweight Cantilever Beam Using Topology Optimization and Material-Extrusion Additive Manufacturing\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eLightweight structural design is a central objective in modern engineering applications spanning aerospace, automotive, marine, and mechanical systems, where reductions in mass directly translate to improved efficiency, reduced material consumption, and lower manufacturing costs. Additive Manufacturing (AM), in this regard has become a possible alternative to traditional manufacturing as it overcomes the limitations of conventional manufacturing processes enabling more geometric freedom. Fused Filament Fabrication (FFF) in particular, due to its potential in fabrication of lightweight structures and open volume structures without need of post processing as required by other AM has gained popularity in various sectors [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the context of lightweight structure fabrication, Topology optimization (TO) has emerged as a powerful design methodology for achieving lightweight yet mechanically robust structures by determining the optimal material distribution within a prescribed design space under given loads and boundary conditions. Unlike traditional shape or size optimization, topology optimization allows the removal of nonessential material, yielding highly efficient load paths that are often nonintuitive. Foundational work by Bends\u0026oslash;e and Sigmund established the theoretical framework for stiffness-based topology optimization, enabling widespread adoption across structural engineering disciplines [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Subsequent developments and reviews have further refined these methods and clarified their numerical and practical limitations [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFurthermore, the synergy between TO and AM has been widely recognized in recent years resulting in various studies demonstrating that TO-derived geometries are particularly well-suited for AM processes [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. However, challenges remain in translating raw topology optimization outputs into manufacturable designs, especially for extrusion-based processes that impose constraints on feature size, overhang angles, and layer-by-layer deposition [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Additionally, while FFF has several advantages over traditional manufacturing, it exhibits anisotropic mechanical behavior, driven primarily by interlayer bonding quality and thermal history during deposition [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. These effects are especially pronounced in load-bearing components such as beams, where print orientation and thermal management directly influence stiffness and strength. Polylactic acid (PLA) is commonly used in FFF due to its biodegradability, dimensional stability, and relatively high stiffness, making it suitable for structural prototypes and low-load applications [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRecent studies have shown that enforcing manufacturability constraints, such as minimum feature thickness, self-supporting geometries, and print orientation during or after topology optimization is essential to ensure successful fabrication and reliable performance [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. As a result, many practical workflows rely on a hybrid approach, in which topology optimization is followed by manual or semi-automated CAD reconstruction to preserve optimized load paths while satisfying manufacturing limitations.\u003c/p\u003e \u003cp\u003eIn this work, a cantilever-style beam subjected to a fixed end load is designed, optimized, and fabricated using a combined topology optimization and material-extrusion additive manufacturing workflow. A maximum-stiffness topology optimization with a prescribed mass-reduction target is performed using Altair Inspire, followed by manual CAD reconstruction to ensure printability without support structures. The optimized design is evaluated through finite element analysis, fabricated using fused filament fabrication in PLA, and experimentally validated under load. In addition, a cost comparison between additive manufacturing and conventional CNC machining is conducted to assess economic feasibility. This study demonstrates a practical, end-to-end framework for integrating topology optimization with extrusion-based additive manufacturing to achieve substantial mass reduction while maintaining structural performance.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cp\u003eThis study follows a systematic workflow integrating topology optimization, finite element analysis, and FFF to design, fabricate, and validate a lightweight cantilever beam. The methodology consists of five primary stages: (i) problem definition and baseline geometry creation, (ii) topology optimization, (iii) CAD reconstruction for manufacturability, (iv) numerical validation, and (v) fabrication and experimental evaluation.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eProblem Definition and Baseline Geometry\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe design objective was to develop a self-supporting cantilever-style beam capable of sustaining a concentrated end load of 0.5 kg (approximately 1 lb) while minimizing structural mass within predefined geometric constraints. The beam was fixed at its base, and the applied load acted normal to the top surface at the free end. These boundary conditions represent a common loading scenario encountered in lightweight support brackets and structural arms.\u003c/p\u003e\n\u003cp\u003eAn initial baseline geometry was created using SolidWorks, ensuring compliance with the prescribed design envelope and manufacturability considerations (Figure: 1). This initial design served as both a structural reference and a benchmark for evaluating the effectiveness of topology optimization. The baseline geometry was analyzed under the specified loading conditions to establish reference values for stress, displacement, and mass.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eTopology Optimization Framework\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eTopology optimization was performed using Altair Inspire 2024, employing a density-based approach with a maximum stiffness objective. The optimization aimed to remove non-load-bearing material while maintaining structural rigidity under the applied load. The design space was defined as the upper horizontal portion of the beam, while the base and load interface regions were excluded to preserve functional interfaces.\u003c/p\u003e\n\u003cp\u003eThe material was specified as polylactic acid (PLA), with linear elastic behavior assumed for optimization and analysis. A mass reduction target of 15% was imposed during optimization to guide material removal while preventing excessive compliance. In addition, minimum and maximum feature thickness constraints of 6 mm and 12 mm, respectively, were enforced to avoid slender members that could compromise printability or mechanical stability.\u003c/p\u003e\n\u003cp\u003eUpon convergence, the topology optimization produced an organically shaped geometry highlighting primary load paths between the fixed support and the load application point. While structurally efficient, the raw optimization output contained irregular surfaces and thin features unsuitable for direct fabrication via fused filament fabrication.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eCAD Reconstruction for Manufacturability\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eTo ensure manufacturability while preserving optimized load paths, the topology-optimized geometry was manually reconstructed using SolidWorks. This reconstruction process involved interpreting the material distribution suggested by the optimizer and redesigning the geometry using smooth, continuous features with uniform wall thickness.\u003c/p\u003e\n\u003cp\u003eSpecial attention was given to eliminating unsupported overhangs, sharp transitions, and excessively thin members to enable support-free printing. The reconstructed design maintained symmetry and consistent cross-sections where possible, improving both structural reliability and print quality. This hybrid optimization\u0026ndash;reconstruction approach balances computational efficiency with practical manufacturing constraints inherent to material extrusion processes.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eNumerical Validation\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eFinite element analysis (FEA) was conducted on both the baseline and optimized designs to evaluate structural performance. The same boundary conditions and loading configurations used during topology optimization were applied for consistency. Linear static analysis was performed to compute von Mises stress distributions and maximum displacement.\u003c/p\u003e\n\u003cp\u003eFor the optimized beam, the numerical results were assessed against the material yield strength of PLA to determine the factor of safety. Displacement values were also examined to ensure that deflections remained within acceptable limits for functional use. This numerical validation step confirmed that the optimized geometry met both strength and stiffness requirements despite significant mass reduction.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eFabrication and Experimental Evaluation\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe finalized CAD model was exported as a stereolithography (STL) file and processed using Ultimaker Cura slicing software. The beam was fabricated using an Ender 3 S1 Pro printer with a 0.4 mm nozzle diameter and a layer height of 0.2 mm. The part was printed with 100% infill to isolate geometric effects from infill-related variability. No support structures were used.\u003c/p\u003e\n\u003cp\u003ePrinting was conducted at a nozzle temperature of 200 \u0026deg;C and a build plate temperature of 60 \u0026deg;C. The print orientation was selected to maximize structural stability and interlayer bonding in the primary load-bearing direction. After fabrication, the printed beam was subjected to a physical load test using a 0.5 kg mass applied at the free end to verify structural integrity and deformation behavior. Table 1 summarizes the process parameters used.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e Process Parameter\u003c/p\u003e\n\u003cdiv align=\"Left\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLayer Height\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(mm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLine Width\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(mm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInfill\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNozzle Temperature\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u0026deg;C)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBed Temperature\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u0026deg;C)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003eValue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003ch2\u003e\u003cstrong\u003eCost Comparison Method\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eTo evaluate economic feasibility, a comparative cost analysis was performed between additive manufacturing and conventional CNC machining. Cost components included material consumption, energy usage, labor time, machine depreciation, and tooling requirements. The additive manufacturing cost model reflects low material waste and minimal tooling, while the CNC machining model accounts for higher labor and equipment costs. This comparison provides insight into the suitability of additive manufacturing for producing topology-optimized structural components.\u003c/p\u003e"},{"header":"Results and Discussion","content":"\u003ch2\u003e\u003cstrong\u003eTopology Optimization Outcome\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe topology optimization process successfully identified an efficient material distribution that preserved the primary load paths between the fixed support and the load application region while eliminating non-essential material. The optimized geometry exhibits a truss-like configuration with smoothly transitioning members, characteristic of stiffness-driven topology optimization under cantilever loading. Compared to the baseline design, the optimized structure concentrates material along tensile and compressive stress trajectories, confirming the effectiveness of the maximum-stiffness objective in promoting mechanically efficient layouts (Figure: 2).\u003c/p\u003e\n\u003cp\u003eAlthough the optimization was constrained to a modest mass reduction target during computation, the resulting geometry enabled substantially greater material savings after CAD reconstruction. This outcome highlights an important practical insight: topology optimization often provides a qualitative guide to load transfer rather than a directly manufacturable shape, and additional mass reduction can be achieved through informed geometric refinement without sacrificing performance.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eNumerical Performance Comparison\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eFinite element analysis reveals a clear trade-off between mass reduction and structural response. The baseline beam exhibited a maximum von Mises stress of approximately 3.2 MPa and a maximum displacement of 4.16 mm under the applied load. In contrast, the optimized beam experienced a higher peak stress of 7.02 MPa and a maximum displacement of 8.24 mm. While these values represent an increase relative to the baseline design, they remain well below the yield strength of PLA, taken conservatively as 50 MPa.\u003c/p\u003e\n\u003cp\u003eDespite the increase in stress and displacement, the optimized design maintains a factor of safety exceeding 7, indicating that the structure remains firmly within the elastic regime. The increase in compliance is an expected and acceptable consequence of aggressive mass reduction and reflects the classic stiffness\u0026ndash;weight trade-off inherent to lightweight structural design. Importantly, the stress distribution in the optimized beam is more uniform than in the baseline design, suggesting improved load sharing and reduced stress concentrations. Table 2 provides summary of the design comparison.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e Comparative analysis of designs\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDesign\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVolume (cm\u003csup\u003e3\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMass (g)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMax von-Mises Stress (Mpa)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMax Displacement (mm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMass Reduction\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eInitial Beam\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e231.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e288.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e3.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e4.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eOptimized Beam\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e45.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e57.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e7.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e8.24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch2\u003e\u003cstrong\u003eMass Reduction and Structural Efficiency\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eOne of the most significant outcomes of this study is the achieved mass reduction of approximately 80%, with the optimized beam mass reduced from 288.75 g to 57.25 g. This dramatic reduction underscores the effectiveness of combining topology optimization with manual CAD reconstruction. When evaluated in terms of structural efficiency defined as load-carrying capability per unit mass the optimized beam demonstrates a substantial improvement over the baseline design.\u003c/p\u003e\n\u003cp\u003eSuch efficiency gains are particularly relevant for applications where weight is a critical constraint, including aerospace brackets, lightweight fixtures, and support arms. The results demonstrate that extrusion-based additive manufacturing, despite its material and geometric limitations, can successfully realize highly efficient topology-optimized structures when design intent and process constraints are properly aligned.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eExperimental Validation\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003ePhysical testing of the fabricated beam confirmed the numerical predictions. The optimized structure successfully supported the applied 0.5 kg load without visible cracking, fracture, or excessive deformation. The observed deformation pattern qualitatively matched the displacement contours predicted by finite element analysis, with maximum deflection occurring near the free end of the beam (Figure 4 c).\u003c/p\u003e\n\u003cp\u003eThe agreement between simulation and experiment suggests that the assumptions used in the numerical model linear elastic material behavior and idealized boundary conditions are reasonable for the loading regime considered. Moreover, the absence of failure or instability during testing indicates that the reconstructed geometry effectively preserved the critical load paths identified during topology optimization.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eAdditive Manufacturing Considerations\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe optimized beam was fabricated without support structures, demonstrating that topology-optimized designs can be successfully adapted for support-free material extrusion when manufacturability is explicitly considered during reconstruction. The use of 100% infill eliminated internal porosity effects, allowing the mechanical response to be dominated by geometry rather than infill architecture.\u003c/p\u003e\n\u003cp\u003eHowever, the results also highlight limitations intrinsic to fused filament fabrication. The increased displacement observed in the optimized design may be partially attributed to interlayer compliance and anisotropy inherent to layer-by-layer deposition. While these effects did not compromise structural integrity in this study, they may become more critical under higher loads or cyclic loading conditions. Future work incorporating enhanced thermal management or alternative raster strategies could further improve stiffness and interlayer bonding [18], [19], [20].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e Cost Comparison between methods\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCost Breakdown for AM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCost Type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCost Per Unit\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Unit\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCost\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003eMaterial Cost (PLA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e$20/kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e0.06 kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e$1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003eEnergy Cost (Machine)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e$0.2/kWh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e0.84 kWh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e$0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003eLabor Cost\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e$20/hr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e2 hr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e$40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003eMachine Depreciation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e$0.1/hr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e9 hr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e$0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 522px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Cost\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e$42.26\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCost Breakdown for CNC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCost Type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCost Per Unit\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Unit\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCost\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003eMaterial Cost (Aluminium)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e$12/kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e0.12 kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e$1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003eEnergy Cost (Machine)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e$0.2/kWh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e10 kWh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e$2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003eLabor Cost\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e$40/hr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e2 hr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e$80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003eMachine Depreciation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e$5/hr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e2 hr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e$10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003eTool Cost\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e$5/pcs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1 pcs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e$5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 522px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Cost\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e$98.44\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eCost Performance\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe cost comparison indicates that additive manufacturing offers a substantial economic advantage for producing the optimized beam geometry. The total unit cost for additive manufacturing was approximately 57% lower than that of conventional CNC machining, driven primarily by reduced labor requirements, minimal material waste, and the elimination of tooling. This cost advantage is particularly significant for low-volume or customized components, where the flexibility of additive manufacturing outweighs its longer build times.\u003c/p\u003e\n\u003cp\u003eThe results (Table 3) suggest that topology optimization not only enhances structural efficiency but also amplifies the economic benefits of additive manufacturing by enabling material savings that directly translate to cost reductions.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eDiscussion Summary\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eOverall, the results demonstrate that a combined topology optimization and material-extrusion additive manufacturing workflow can achieve substantial mass reduction while maintaining adequate structural performance and cost efficiency. The optimized beam satisfies strength, stiffness, manufacturability, and economic criteria, validating the proposed design approach. While the study is limited to static loading and a single material system, the methodology is broadly applicable and can be extended to more complex loading scenarios, materials, and optimization objectives.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study demonstrated an end-to-end workflow integrating topology optimization, numerical analysis, and material-extrusion additive manufacturing for the design and fabrication of a lightweight cantilever beam. A maximum-stiffness topology optimization was performed to guide material redistribution, followed by manual CAD reconstruction to ensure manufacturability without support structures. The optimized beam achieved an approximately 80% reduction in mass relative to the baseline design while maintaining structural integrity under a 0.5 kg end load. Finite element analysis predicted a peak von Mises stress well below the yield strength of PLA, and experimental testing confirmed the numerical results, validating the effectiveness of the proposed design methodology.\u003c/p\u003e \u003cp\u003eBeyond mechanical performance, the study highlighted the economic advantages of additive manufacturing for topology-optimized components. A comparative cost analysis showed that fused filament fabrication reduced production cost by approximately 57% compared to conventional CNC machining for the studied geometry. These results underscore the potential of combining topology optimization with extrusion-based additive manufacturing to produce structurally efficient, low-cost components for low-volume and customized applications.\u003c/p\u003e \u003cp\u003eFuture work will extend this framework to more complex loading conditions, including dynamic and fatigue loading, to assess long-term durability. Incorporating manufacturability constraints directly within the topology optimization stage such as overhang angle limits and anisotropic material behavior\u0026mdash;could further reduce the need for manual reconstruction. In addition, enhanced thermal management strategies during printing may be explored to improve interlayer bonding and stiffness, particularly for slender load-bearing members. Finally, data-driven and machine-learning-assisted optimization approaches may be integrated to accelerate design iteration and enable adaptive parameter selection for improved structural performance.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eY. Abderrafai \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;Additive manufacturing and characterization of high temperature thermoplastic blends for potential aerospace applications,\u0026rdquo; \u003cem\u003eCompos. Sci. Technol.\u003c/em\u003e, vol. 231, 2023, doi: 10.1016/j.compscitech.2022.109839.\u003c/li\u003e\n\u003cli\u003eM. Gharibshahian \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;Recent advances on 3D-printed PCL-based composite scaffolds for bone tissue engineering,\u0026rdquo; 2023. doi: 10.3389/fbioe.2023.1168504.\u003c/li\u003e\n\u003cli\u003eE. Cuan-Urquizo and R. Guerra Silva, \u0026ldquo;Fused Filament Fabrication of cellular, lattice and porous mechanical metamaterials: a review,\u0026rdquo; 2023. doi: 10.1080/17452759.2023.2224300.\u003c/li\u003e\n\u003cli\u003eR. Ahmed, R. S. Niloy, M. R. Mozumder, and T. A. Shanto, \u0026ldquo;Application of Fused Filament Fabrication in Marine Sector, From Rapid Prototyping to Final Product,\u0026rdquo; in \u003cem\u003eProceedings of the 14th International Conference on Marine Technology (MARTEC 2024)\u003c/em\u003e, Sep. 2024, pp. 57\u0026ndash;63. [Online]. Available: https://www.researchgate.net/publication/388682275_APPLICATION_OF_FUSED_FILAMENT_FABRICATION_IN_MARINE_SECTOR_FROM_RAPID_PROTOTYPING_TO_FINAL_PRODUCT\u003c/li\u003e\n\u003cli\u003eA. Dhandapani \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;Evolution, Prospects, and Predicaments of Polymers in Marine Applications: A Potential Successor to Traditional Materials,\u0026rdquo; 2024. doi: 10.3390/recycling9010008.\u003c/li\u003e\n\u003cli\u003eM. J. Zulqernine, Md. A. Alam, M. R. Uddin, I. S. Dola, and T. A. Shanto, \u0026ldquo;An Investigation on the Applications of Additive Manufacturing in the Marine Industry,\u0026rdquo; in \u003cem\u003eProceedings of MARTEC 2024: The International Conference on Marine Technology\u003c/em\u003e, Johor Bahru, Johor, Malaysia, Sep. 2024. [Online]. Available: https://www.researchgate.net/publication/388830803_AN_INVESTIGATION_ON_THE_APPLICATIONS_OF_ADDITIVE_MANUFACTURING_IN_THE_MARINE_INDUSTRY\u003c/li\u003e\n\u003cli\u003eR. Wildman, I. Ashcroft, and M. Abdi, \u0026ldquo;Design optimization for an additively manufactured automotive component,\u0026rdquo; \u003cem\u003eInternational Journal of Powertrains\u003c/em\u003e, vol. 7, no. 2/3, 2018, doi: 10.1504/ijpt.2018.10009559.\u003c/li\u003e\n\u003cli\u003eM. P. Bends\u0026oslash;e and O. Sigmund, \u003cem\u003eTopology Optimization: Theory, Methods, and Applications\u003c/em\u003e, 2nd ed. Berlin, Heidelberg: Springer, 2004. doi: 10.1007/978-3-662-05086-6.\u003c/li\u003e\n\u003cli\u003eG. I. N. Rozvany, \u0026ldquo;A critical review of established methods of structural topology optimization,\u0026rdquo; \u003cem\u003eStructural and Multidisciplinary Optimization\u003c/em\u003e, vol. 37, no. 3, 2009, doi: 10.1007/s00158-007-0217-0.\u003c/li\u003e\n\u003cli\u003eO. Sigmund, \u0026ldquo;A 99 line topology optimization code written in matlab,\u0026rdquo; \u003cem\u003eStructural and Multidisciplinary Optimization\u003c/em\u003e, vol. 21, no. 2, 2001, doi: 10.1007/s001580050176.\u003c/li\u003e\n\u003cli\u003eH. Jiang, Z. He, E. Li, and C. Jiang, \u0026ldquo;Additive manufacturing-driven simultaneous optimization of topology and print direction for thermoelastic structures considering strength failure,\u0026rdquo; \u003cem\u003eJ. Comput. Des. Eng.\u003c/em\u003e, vol. 11, no. 3, pp. 185\u0026ndash;199, Jun. 2024, doi: 10.1093/jcde/qwae043.\u003c/li\u003e\n\u003cli\u003eI. El Khadiri, M. Zemzami, N. Q. Nguyen, M. Abouelmajd, N. Hmina, and S. Belhouideg, \u0026ldquo;Topology optimization methods for additive manufacturing: a review,\u0026rdquo; 2023. doi: 10.1051/smdo/2023015.\u003c/li\u003e\n\u003cli\u003eJ. ZHU, H. ZHOU, C. WANG, L. ZHOU, S. YUAN, and W. ZHANG, \u0026ldquo;A review of topology optimization for additive manufacturing: Status and challenges,\u0026rdquo; 2021. doi: 10.1016/j.cja.2020.09.020.\u003c/li\u003e\n\u003cli\u003eS. H. Ahn, M. Montero, D. Odell, S. Roundy, and P. K. Wright, \u0026ldquo;Anisotropic material properties of fused deposition modeling ABS,\u0026rdquo; \u003cem\u003eRapid Prototyp. J.\u003c/em\u003e, vol. 8, no. 4, 2002, doi: 10.1108/13552540210441166.\u003c/li\u003e\n\u003cli\u003eA. Sebert, J. W. Nelson, and G. Bertacco, \u0026ldquo;Anisotropic mechanical performance of 3D printed polymers,\u0026rdquo; in \u003cem\u003eAdvanced Materials - TechConnect Briefs 2017\u003c/em\u003e, 2017.\u003c/li\u003e\n\u003cli\u003eB. M. Tymrak, M. Kreiger, and J. M. Pearce, \u0026ldquo;Mechanical properties of components fabricated with open-source 3-D printers under realistic environmental conditions,\u0026rdquo; \u003cem\u003eMater. Des.\u003c/em\u003e, vol. 58, 2014, doi: 10.1016/j.matdes.2014.02.038.\u003c/li\u003e\n\u003cli\u003eM. Bi, P. Tran, and Y. M. Xie, \u0026ldquo;Topology optimization of 3D continuum structures under geometric self-supporting constraint,\u0026rdquo; \u003cem\u003eAddit. Manuf.\u003c/em\u003e, vol. 36, 2020, doi: 10.1016/j.addma.2020.101422.\u003c/li\u003e\n\u003cli\u003eP. Patel, R. Ahmed, T. A. Shanto, A. Jain, and R. M. Taylor, \u0026ldquo;Experimental characterization of enhanced fused filament fabrication (FFF) of tall thin-walled structures using polylactic acid (PLA),\u0026rdquo; \u003cem\u003eThe International Journal of Advanced Manufacturing Technology\u003c/em\u003e, vol. 139, no. 11, pp. 5663\u0026ndash;5675, 2025, doi: 10.1007/s00170-025-16171-w.\u003c/li\u003e\n\u003cli\u003eT. A. Shanto, M. A. Shahriar, T. Ahmed, M. J. Zulqernine, and R. M. Taylor, \u0026ldquo;Predicting mechanical strength in FDM printed ABS parts with in-process annealing: A machine learning approach,\u0026rdquo; in \u003cem\u003eProceedings of the IISE Annual Conference \u0026amp; Expo 2025\u003c/em\u003e, 2025, pp. 1\u0026ndash;6. doi: 10.21872/2025IISE_6734.\u003c/li\u003e\n\u003cli\u003eT. A. Shanto, H. R. Pavel, R. Ahmed, M. Abdullah, and R. M. Taylor, \u0026ldquo;Leveraging Large Language Models for Process Parameter Optimization in 3D-printed ABS Polymer Specimens,\u0026rdquo; \u003cem\u003eIISE Annual Conference. Proceedings\u003c/em\u003e, pp. 1\u0026ndash;6, 2025, doi: https://doi.org/10.21872/2025IISE_6901.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Topology Optimization, beam, altair Inspire, 3D printing, additive manufacturing","lastPublishedDoi":"10.21203/rs.3.rs-8704572/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8704572/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTopology optimization (TO) combined with additive manufacturing (AM) enables the fabrication of lightweight structural components with prescribed load paths that are often difficult or impractical to achieve using conventional manufacturing. In this study, a cantilever-style beam subjected to a 0.5 kg end load was designed, optimized, and fabricated using material-extrusion additive manufacturing. A maximum-stiffness topology optimization with a prescribed mass-reduction constraint was performed using Altair Inspire, followed by manual CAD reconstruction to enforce manufacturability while preserving optimized load paths. The final design was fabricated with polylactic acid (PLA) using fused filament fabrication (FFF) without support structures. Finite element analysis predicted a peak von Mises stress of 7.02 MPa and a maximum displacement of 8.24 mm, corresponding to a factor of safety exceeding 7 relative to PLA yield strength. Compared to the initial design, the optimized beam achieved an 80% mass reduction while successfully supporting the applied load during physical testing. A comparative cost analysis further demonstrated that additive manufacturing reduced unit production cost by approximately 57% relative to conventional CNC machining for this geometry. The results highlight the effectiveness of integrating TO with extrusion-based additive manufacturing for producing structurally efficient, low-cost components.\u003c/p\u003e","manuscriptTitle":"Design and Fabrication of a Lightweight Cantilever Beam Using Topology Optimization and Material-Extrusion Additive Manufacturing","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-28 06:02:04","doi":"10.21203/rs.3.rs-8704572/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"60511e9e-d9a6-46ed-a0d2-7e1c53852d17","owner":[],"postedDate":"January 28th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":61785962,"name":"Mechanical Engineering"}],"tags":[],"updatedAt":"2026-01-28T06:02:04+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-28 06:02:04","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8704572","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8704572","identity":"rs-8704572","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}