Bone replacement implants for craniofacial reconstruction require to provide an adequate structural foundation to withstand the physiological loading. With recent advances in 3D printing technology in place of bone grafts using autologous tissues, patient-specific additively manufactured implants are being established as suitable alternates. Since the stress distribution of these structures is complicated, efficient design techniques, such as topology optimization, can deliver optimized designs with enhanced functionality. In this work, a two-scale topology optimization approach is proposed that provides multi-material designs for both macrostructures and microstructures. In the first stage, a multi-resolution topology optimization approach is used to produce multi-material designs with maximum stiffness. Then, a microstructure with a desired property supplants the solid domain. This is beneficial for bone implant design since, in addition to imparting the desired functional property to the design, it also introduces porosity. To show the efficacy of the technique, four different large craniofacial defects due to maxillectomy are considered, and their respective implant designs with multi-materials are shown. These designs show good potential in developing patient-specific optimized designs suitable for additive manufacturing.

The mechanical properties of woven jute fiber-reinforced PLA polymer laminates additively manufactured through Laminated Object Manufacturing (LOM) technology are simulated using the finite element method in this work. Woven jute fiber reinforcements are used to strengthen bio-thermoplastic PLA polymers in creating highly biodegradable composite structures that can serve as one of the environmentally friendly alternatives for synthetic composites. A LOM 3D printer prototype was designed and built by the authors. All woven jute/PLA biocomposite laminated specimens made using the built prototype in this study had their tensile and flexural properties measured using ASTM test standards. These laminated structures were modeled using the ANSYS Mechanical Composite PrepPost (ACP) module, and then both testing processes were simulated using the experimentally measured input values. The FEA simulation results indicated a close match with experimental results, with a maximum difference of 9.18%. This study served as an exemplary case study using the FEA method to predict the mechanical behaviors of biocomposite laminate materials made through a novel manufacturing process.

A top drive is an essential mechanical device in oil field drilling since it provides the necessary torque for the drilling operations. Manufacturers in the oil and gas industry typically perform in-housing testing and classify the Safe Working Load of top drives. Testing a top drive requires a unique test stand, thus making testing top drives from other manufacturers a difficult challenge. A fixture adapter can be designed using geometric constraints and intuition to make testing apparatus semi-universal, yet they are often bulky and heavy, posing more significant safety concerns. This study aims to first numerically assess the existing fixture adapter and then structurally optimize it for enhancing its structural integrity and efficiency under various severe working environments. Therefore, finite element analysis (FEA) was performed on the existing fixture adapter, and compliance minimization topology optimization was employed. Four load and boundary conditions were used from the three most frequent operation scenarios for the fixture adapters: (i) drilling standby, (ii) staging area, (iii) drilling make-up, and (iv) break-up. The FEA results indicated that no safety factor was compromised with a 50% and 60% mass retention constraint via topology optimization compared to the original fixture adapter. The optimized fixture adapter was also tested under compression using printed 3D prototypes to validate the finite analysis and topology optimization processes.

Fused deposition modeling (FDM) is one of the most widely deployed additive manufacturing methods, and the mechanical performance of FDM-printed parts is governed by a small set of strongly coupled process parameters. Silk PLA, a PLA-based filament engineered to deliver a high-gloss finish with improved mechanical performance, has received far less attention than commodity PLA, and its parameter–property relationships remain incompletely characterized. In this work, the effects of three FDM printing parameters: (i) layer height (0.10, 0.15, and 0.20 mm), (ii) extrusion temperature (200, 210, and 220 °C), and (iii) print speed (100, 120, and 140 mm/s) on the tensile characteristic of Silk PLA were investigated through a full-factorial design consisting of 27 parameter combinations and 135 ASTM D638 Type-I specimens. Tensile tests were performed on an MTS E42 universal testing frame, while Digital Image Correlation (DIC) was employed to obtain full-field longitudinal and transverse strain distributions and to identify the onset and location of necking. Analysis of variance (ANOVA) was used to assess the statistical significance, while an interpretable machine learning (ML) pipeline combining extreme gradient boosting (XGBoost), Shapley additive explanations (SHAP) values, and partial dependence plots (PDPs) was employed to quantify the relative influence of each parameter and elucidate its effect on the tensile response. Both analyses identified extrusion temperature as the dominant factor governing ultimate tensile strength and Young’s modulus. Partial dependence analysis further revealed that strength gains saturate above 210 °C and are maximized at an intermediate print speed of 120 mm/s, providing actionable guidance for process optimization. The highest tensile strength, 40.68 MPa, was achieved at a layer height of 0.20 mm, an extrusion temperature of 220 °C, and a print speed of 120 mm/s. DIC measurements showed that thinner layers (0.10 mm) produced higher breaking strains and necking that initiated at the gauge-section edges, whereas thicker layers (0.20 mm) shifted necking toward the mid-gauge. Together, the experimental, statistical, and ML results provide a consistent, mechanistically interpretable framework for optimizing FDM process parameters for Silk PLA functional parts.

Achieving high-quality products in Fused Deposition Modeling (FDM) 3D printing necessitates proper thermal management in the printing process since it affects the interlayer bonding. The FDM process relies on the adhesion of polymer material layers controlled by various printing parameters, such as nozzle temperature, printing speed, and layer height. These parameters influence the thermal gradient perpendicular to the printing layers (cooling rate), affecting mechanical properties and adhesion between polymeric layers. This study aimed to quantitatively investigate the correlation between these key printing parameters and thermal gradients to measure their impact on mechanical properties. A high-resolution FLIR thermal camera was used to capture temperature gradients, and the printed specimens were subjected to tensile tests by ASTM D638 specifications. A complementary COMSOL-based behavioral simulation was conducted to examine how deposition velocity influences subsurface heat penetration and interlayer re-bonding during layer deposition. The results suggest printing parameter combinations leading to low cooling rate can improve mechanical properties in FDM-printed products.