Search Results (768)

Background: Precision medicine refers to the formulation of personalized drug regimens according to the individual characteristics of patients to achieve optimal efficacy and minimize adverse reactions. Additive manufacturing (AM), also known as three-dimensional (3D) printing, has emerged as an optimal solution for precision drug delivery, enabling customizable and the fabrication of multifunctional structures with precise control over morphology and release behavior in pharmaceutics. However, the influence of 3D printing parameters on the printed tablets, especially regarding in vitro and in vivo performance, remains poorly understood, limiting the optimization of manufacturing processes for controlled-release profiles. Objective: To establish the fabrication process of 3D-printed controlled-release tablets via comprehensively understanding the printing parameters using fused deposition modeling (FDM) combined with hot-melt extrusion (HME) technologies. HPMC-AS/HPC-EF was used as the drug delivery matrix and carbamazepine (CBZ) was used as a model drug to investigate the in vitro drug delivery performance of the printed tablets. Methodology: Thermogravimetric analysis (TGA) was employed to assess the thermal compatibility of CBZ with HPMC-AS/HPC-EF excipients up to 230 °C, surpassing typical processing temperatures (160–200 °C). The formation of stable amorphous solid dispersions (ASDs) was validated using differential scanning calorimetry (DSC), hot-stage polarized light microscopy (PLM), and powder X-ray diffraction (PXRD). A 15-group full factorial design was then used to evaluate the effects of the fan speed (20–100%), platform temperature (40–80 °C), and printing speed (20–100 mm/s) on the tablet properties. Response surface modeling (RSM) with inverse square-root transformation was applied to analyze the dissolution kinetics, specifically t_50% (time for 50% drug release) and Q_4h (drug released at 4 h). Results: TGA confirmed the thermal compatibility of CBZ with HPMC-AS/HPC-EF, enabling stable ASD formation validated by DSC, PLM, and PXRD. The full factorial design revealed that printing speed was the dominant parameter governing dissolution behavior, with high speeds accelerating release and low speeds prolonging release through porosity-modulated diffusion control. RSM quadratic models showed optimal fits for t_50% (R² = 0.9936) and Q_4h (R² = 0.9019), highlighting the predictability of release kinetics via process parameter tuning. This work demonstrates the adaptability of polymer composite AM for tailoring drug release profiles, balancing mechanical integrity, release kinetics, and manufacturing scalability to advance multifunctional 3D-printed drug delivery devices in pharmaceutics. Full article

The growing complexity of modern manufacturing has intensified the need for precise control of residual stresses to ensure structural reliability, dimensional stability, and material performance. This study conducts a bibliometric review using data from Scopus and Web of Science, covering publications from 2019 to 2024. Residual stress research in metal manufacturing has gained prominence, particularly in relation to welding, additive manufacturing, and machining—processes that induce significant stress gradients affecting mechanical behavior and service life. Emerging trends focus on simulation-based prediction methods, such as the finite element method, heat treatment optimization, and stress-induced defect prevention. Key thematic clusters include process-induced microstructural changes, mechanical property enhancement, and the integration of modeling with experimental validation. By analyzing the evolution of research output, global collaboration networks, and process-specific contributions, this review provides a comprehensive overview of current challenges and identifies strategic directions for future research in residual stress management in advanced metal manufacturing. Full article

Laser beam powder bed fusion of metals (PBF-LB/M, or simply L-PBF) has emerged as one of the most competitive additive manufacturing technologies for producing complex metallic components with high precision, design freedom, and minimal material waste. Among the various categories of additive manufacturing processes, L-PBF stands out, paving the way for the execution of part designs with geometries previously considered unfeasible. Despite offering several advantages, parts with overhang features require the use of support structures to provide dimensional stability of the part. Support structures achieve this by resisting residual stresses generated during processing and assisting heat dissipation. Although the scientific community acknowledges the role of support structures in the success of L-PBF manufacturing, they have remained relatively underexplored in the literature. In this context, the present work investigated the impact of laser power and scanning speed on the dimensioning, integrity and tensile strength of single-walled block type support structures manufactured in AISI 316L stainless steel. The method proposed in this work is divided in two stages: processing parameter exploration, and mechanical characterization. The results indicated that support structures become more robust and resistant as laser power increases, and the opposite effect is observed with an increment in scanning speed. In addition, defects were detected at the interfaces between the bulk and support regions, which were crucial for the failure of the tensile test specimens. For a layer thickness corresponding to 0.060 mm, it was verified that the combination of laser power and scanning speed of 150 W and 500 mm/s resulted in the highest tensile resistance while respecting the dimensional deviation requirement. Full article

Material extrusion additive manufacturing (MEAM) has emerged as a versatile and widely adopted 3D printing technology due to its cost-effectiveness and ability to process a diverse range of materials. However, achieving consistent part quality and repeatability remains a challenge, mainly due to variations in process parameters and material behavior during fabrication. In-situ monitoring and advanced process control systems have been increasingly integrated into MEAM to address these issues, enabling real-time detection of defects, optimization of printing conditions, reliability of fabricated parts, and enhanced control over mechanical properties. This review examines the state-of-the-art in-situ monitoring techniques, including thermal imaging, vibrational sensing, rheological monitoring, printhead positioning, acoustic sensing, image recognition, and optical scanning, and their integration with process control strategies, such as closed-loop feedback systems and machine learning algorithms. Key challenges, including sensor accuracy, data processing complexity, and scalability, are discussed alongside recent advancements and their implications for industrial applications. By synthesizing current research, this work highlights the critical role of in-situ monitoring and process control in advancing the reliability and precision of MEAM, paving the way for its broader adoption in high-performance manufacturing. Full article

This paper presents a novel design for precise vertical landing of drones based on the detection of three phase shifts in the range of ±180°. The design has three inputs to which the signal transmitted from an oscillator located at the landing point arrives with different delays. The circuit increases the aerial tracking volume relative to that achieved by detectors with theoretical unambiguous detection ranges of ±90°. The phase shift measurement circuit uses an analog phase detector (mixer), detecting a maximum range of ±90°and a double multiplication of the input signals, in phase and phase-shifted, without the need to fulfill the quadrature condition. The calibration procedure, phase detector curve modeling, and calculation of the input signal phase shift are significantly simplified by the use of an automatic gain control on each branch, dwhich keeps input amplitudes to the analog phase detectors constant. A simple program to determine phase shifts and guidance instructions is proposed, which could be integrated into the same flight control platform, thus avoiding the need to add additional processing components. A prototype has been manufactured in C band to explain the details of the procedure design. The circuit uses commercial circuits and microstrip technology, avoiding the crossing of lines by means of switches, which allows the design topology to be extrapolated to much higher frequencies. Calibration and measurements at 5.3 GHz show a dynamic range greater than 50 dB and a non-ambiguous detection range of ±180°. These specifications would allow one to track the drone during the landing maneuver in an inverted cone formed by a surface with an 11 m radius at 10 m high and the landing point, when 4 cm between RF inputs is considered. The errors of the phase shifts used in the landing maneuver are less than ±3°, which translates into 1.7% losses over the detector theoretical range in the worst case. The circuit has a frequency bandwidth of 4.8 GHz to 5.6 GHz, considering a 3 dB variation in the input power when the AGC is limiting the output signal to 0 dBm at the circuit reference point of each branch. In addition, the evolution of phases in the landing maneuver is shown by means of a small simulation program in which the drone trajectory is inside and outside the tracking range of ±180°. Full article

The use of aluminum honeycomb structures is fast expanding in advanced sectors such as the aeronautics, aerospace, marine, and automotive industries. However, processing these structures represents a major challenge for producing parts that meet the strict standards. To address this issue, an innovative manufacturing method using longitudinal ultrasonic vibration-assisted cutting, combined with a CDZ10 hybrid cutting tool, was developed to optimize the efficiency of traditional machining processes. To this end, a 3D numerical model was developed using the finite element method and Abaqus/Explicit 2017 software to simulate the complex interactions among the cutting tool and the thin walls of the structures. This model was validated by experimental tests, allowing the study of the influence of milling conditions such as feed rate, cutting angle, and vibration amplitude. The numerical results revealed that the hybrid technology significantly reduces the cutting force components, with a decrease ranging from 10% to 42%. In addition, it improves cutting quality by reducing plastic deformation and cell wall tearing, which prevents the formation of chips clumps on the tool edges, thus avoiding early wear of the tool. These outcomes offer new insights into optimizing industrial processes, particularly in fields with stringent precision and performance demands, like the aerospace sector. Full article

This study analyses the application of the Friction Stir Welding (FSW) process on polymeric materials manufactured by additive manufacturing (AM), specifically with polylactic acid (PLA). FSW is a solid-state welding process characterized by its low heat input and minimal distortion, which makes it ideal for the assembly of complex or large components made by additive manufacturing. To evaluate its effectiveness, a portable FSW device was developed for the purpose of joining PLA specimens made by AM using different filler densities (15% and 100%). Two tool geometries (a cylindrical and truncated cone) were utilized by varying the parameters of rotational speed, tilt angle, and feed rate. The results revealed two different process stages, transient and steady-state, and showed differences in weld quality depending on the material density, tool type, and material addition. The study confirms the viability of FSW for joining PLA parts made by AM and suggests potential applications in industries that require robust and precise joints in plastic parts, thereby helping hybrid manufacturing to progress. Full article

Manufacturing processes are inherently complex, multi-objective in nature, and highly sensitive to process parameter settings. This paper presents two simple and efficient optimization algorithms—Best–Worst–Random (BWR) and Best–Mean–Random (BMR)—developed to solve both constrained and unconstrained optimization problems of manufacturing processes involving single, multi-, and many-objectives. These algorithms are free from metaphorical inspirations and require no algorithm-specific control parameters, which often complicate other metaheuristics. Extensive testing reveals that BWR and BMR consistently deliver competitive, and often superior, performance compared to established methods. Their multi- and many-objective extensions, named MO-BWR and MO-BMR, respectively, have been successfully applied to tackle 2-, 3-, and 9-objective optimization problems in advanced manufacturing processes such as friction stir processing (FSP), ultra-precision turning (UPT), laser powder bed fusion (LPBF), and wire arc additive manufacturing (WAAM). To aid in decision-making, the proposed BHARAT can be integrated with MO-BWR and MO-BMR to identify the most suitable compromise solution from among a set of Pareto-optimal alternatives. The results demonstrate the strong potential of the proposed algorithms as practical tools for intelligent decision-making in real-world manufacturing applications. Full article

Objective: This article presents a step-by-step digital technique for fabricating a 3D-printed surgical guide to assist in alveoloplasty for immediate denture placement. Methods: The workflow integrates intraoral scanning, virtual tooth extraction, digital soft tissue modeling, and additive manufacturing to produce a customized guide with an occlusal window and buccal slot, along with a verification stent. Results: This method ensures precise ridge recontouring and verification, enhancing surgical predictability and prosthetic fit. Conclusions: Unlike traditional surgical guides based on conventional casts or manual fabrication, this fully digital approach offers a practical and replicable protocol that bridges digital planning and clinical execution. By improving surgical precision, reducing operative time, and ensuring optimal denture fit, this technique represents a significant advancement in guided pre-prosthetic surgery. Full article

Microneedle arrays (MNAs) are becoming increasingly popular due to their ease of use and effectiveness in drug delivery and diagnostic applications. Improvements in three-dimensional (3D) printing techniques have made it possible to fabricate MNAs with high precision, intricate designs, and customizable properties, expanding their potential in medical applications. While most studies have focused on transdermal applications, non-transdermal uses remain relatively underexplored. This review summarizes recent developments in 3D-printed MNAs intended for non-transdermal drug delivery and diagnostic purposes. It includes a literature review of studies published in the past ten years, organized by the target delivery site—such as the brain and central nervous system (CNS), oral cavity, eyes, gastrointestinal (GI) tract, and cardiovascular and reproductive systems, among other emerging areas. The findings show that 3D-printed MNAs are more adaptable than skin-based delivery, opening up exciting new possibilities for use in a variety of organs and systems. To guarantee the effective incorporation of polymeric non-transdermal MNAs into clinical practice, additional research is necessary to address current issues with materials, manufacturing processes, and regulatory approval. Full article

This study analyzes the recent scientific literature on advanced biocompatible materials for triboelectric nanogenerators (TENGs) in biomedical applications. Focusing on materials like synthetic polymers, carbon-based derivatives, and advanced hybrids, the study interprets findings regarding their triboelectric properties and performance influenced by surface texture and additive manufacturing techniques. Major findings reveal that precise control over surface morphology, enabled by additive manufacturing (AM) is promising for optimizing transferred charge density and maximizing TENG efficiency. The analysis highlights the relevance of these material systems and fabrication strategies for developing self-powered wearable and implantable biomedical devices through enabling biocompatible energy-harvesting components that can operate autonomously without external power, underscoring the need for stringent biocompatibility and performance stability. This work synthesizes current progress, identifying critical material and process design parameters for advancing the field of biocompatible TENGs. Full article

The growing consumption of oil and gas resources and the increasing difficulty of extraction have created major challenges for traditional manufacturing and maintenance, particularly in the timely supply of critical components, customized production, and complex structure fabrication. Additive manufacturing (AM) technology, with its high design freedom, precision, and rapid prototyping, provides new approaches to address these issues. However, systematic reviews of related efforts are scarce. This paper reviews the applications and progress of metal and non-metal AM technologies in oil and gas extraction and gathering engineering, focusing on the just-in-time (JIT) manufacturing of failed components, the manufacturing and repair of specialized equipment and tools for oil and gas extraction and gathering, and artificial core and reservoir geological modeling fabrication. AM applications in this field remain exploratory and face challenges with regard to their standards, supply chains, materials, and processes. Future research should emphasize developing materials and processes for extreme conditions, optimizing process parameters, establishing standards and traceability systems, and integrating AM with digital design and reverse engineering to support efficient, safe, and sustainable industry development. This work aims to provide a reference for advancing AM research and engineering applications in the oil and gas sector. Full article

Additive manufacturing is one of the most common technologies used in prototyping and manufacturing usable parts. Currently, industrial robots are also increasingly being used to carry out this process. This is due to a robot’s capability to fabricate components with structural configurations that are unattainable using conventional 3D printers. The number of degrees of freedom of the robot, combined with its working range and precision, allows the construction of parts with greater dimensions and better strength in comparison to conventional 3D printing. However, the implementation of a robot into the 3D printing process requires the development of novel solutions to streamline and facilitate the prototyping and manufacturing processes. This work focuses on the need to develop new slicing methods for robotic additive manufacturing. A solution for alternative control code generation without external slicer utilization is presented. The implementation of the proposed method enables a reduction of over 80% in the time required to generate new G-code, significantly outperforming traditional approaches. The paper presents a novel approach to the slicing process in robotic additive manufacturing that is adopted for the fused granular fabrication process using thermoplastic polymers. Full article

Background/Objectives: Recent breakthroughs in three-dimensional (3D) printing and high-resolution imaging have opened up new possibilities in personalized medicine, surgical planning, and forensic reconstruction. This study breaks new ground by evaluating the integration of high-resolution peripheral quantitative computed tomography (HR-pQCT) with multimodal imaging and additive manufacturing to assess a chronic, infected gunshot injury in the knee joint of a red deer. This unique approach serves as a translational model for complex skeletal trauma. Methods: Multimodal imaging—including clinical CT, MRI, and HR-pQCT—was used to characterise the extent of osseous and soft tissue damage. Histopathological and molecular analyses were performed to confirm the infectious agent. HR-pQCT datasets were segmented and processed for 3D printing using PolyJet, stereolithography (SLA), and fused deposition modelling (FDM). Printed models were quantitatively benchmarked through 3D surface deviation analysis. Results: Imaging revealed comminuted fractures, cortical and trabecular degradation, and soft tissue involvement, consistent with chronic osteomyelitis. Sphingomonas sp., a bacterium that forms biofilms, was identified as the pathogen. Among the printing methods, PolyJet and SLA demonstrated the highest anatomical accuracy, whereas FDM exhibited greater geometric deviation. Conclusions: HR-pQCT-guided 3D printing provides a powerful tool for the anatomical visualisation and quantitative assessment of complex bone pathology. This approach not only enhances diagnostic precision but also supports applications in surgical rehearsal and forensic analysis. It illustrates the potential of digital imaging and additive manufacturing to advance orthopaedic and trauma care, inspiring future research and applications in the field. Full article

The dimensional accuracy of 3D-printed edentulous jaw models is critical for successful prosthetic treatment outcomes. This study investigated the accuracy of 3D-printed working models of a completely edentulous jaw through comparative analysis of digital images generated by three laboratory scanners. A reference plaster model of a mandibular edentulous arch was digitized and used to produce ten resin models via digital light processing (DLP) technology. Each model was scanned using three different laboratory scanners: AutoScan-DS-EX, AutoScan-DS-EX Pro(H), and Optical 3D Scanner Vinyl. Digital comparison was performed using specialized software, evaluating the root mean square (RMS) deviation and percentage of values within an acceptable deviation range ±0.05 mm. All printed models showed significant deviations from the reference model (p < 0.05), with RMS values ranging from 109.2–139.7 µm and acceptable deviation percentages ranging from 29.34 to 32.31%. The mean precision RMS value was 66.37 µm. The mean intraclass correlation coefficient of 0.544 indicated moderate precision. Optical 3D Scanner Vinyl demonstrated the highest consistency, while AutoScan-DS-EX Pro(H) showed maximum variability. No statistically significant differences were found between scanners (p = 0.075). While the investigated scanners demonstrated reliable performance and sufficient accuracy, the additive manufacturing process introduced clinically significant deviations, highlighting the importance of verification between printed models and their digital originals before proceeding with clinical stages. Clinical practice should prioritize scanning systems with advanced software algorithms over those with superior hardware specifications alone. Full article