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The article presents analysis of mechanical properties of specimens fabricated by fused deposition modeling (FDM). The four of considered materials are the well-known 3D printing filaments i.e., polylactide (PLA), Nylon 12 (PA12), acrylonitrile butadiene styrene (ABS), polyethylene terephthalate glycol (PET-G). The other four of the considered materials are composites with carbon i.e. polylactide with carbon fiber (PLA-CF), Nylon 12 with carbon fiber (PA12-CF), acrylonitrile butadiene styrene with carbon fiber (ABS-CF), polyethylene terephthalate glycol with carbon fiber (PETG-CF). The paper describes how the specimens were designed, printed, subjected to tensile testing, and examined using microscopy. The obtained data will be used to select the optimum material for the rapid manufacture of lower limb orthoses. Carbon composites were found to have better mechanical properties of their base material, but the fabrication of composite samples is much more time consuming, for the reason that the manufacturing process is not stable.

This paper presents the outcomes of investigations conducted on the development procedure of a personalized prosthetic device for an adult patient. The individualization is achieved through 3D scanning, followed by semi-automated design using the AutoMedPrint system, and low-cost fused deposition modelling (FDM) technology for 3D printing. The prosthesis is aimed for use during bicycle riding and other sport activities. During the conducted experiments outlined in this manuscript, the prosthesis is equipped with force and movement sensors. The purpose is to collect data on its functionality across different scenarios and dynamic activities, aiming to assess potential harm, refine the design, and serve as an initial step before activating the prosthesis end effector. This article describes the methodology in detail, including the process of designing, producing, and programming, as well as laboratory and field test results (including testing performed with and without a patient). Overall, the design and prototype are implemented successfully. A discussion about the need for particular improvements in both the mechanical and electrical areas is finally presented.

This paper presents results from experimental studies that assess the utilization of virtual, augmented, and mixed reality (VR, AR, MR) at different stages of developing personalized 3D printed upper limb prostheses for adult patients. The prostheses are designed automatically using the AutoMedPrint system, leveraging 3D scans as described in various prior publications. Various stages of development of the prosthesis are made as applications of different extended reality technologies. An assembly instruction is implemented as an immersive VR application, a configurator is designed as AR application and a configurator and try-on application is prepared and deployed in MR. The applications are tested by an international group of experts during a scheduled experiment. The experts then participate to surveys and comparatively evaluate the potential of all the XR technologies. The paper presents the development of these applications, provides a detailed account of the experimental process, including the rankings of XR technologies for different applications throughout the lifecycle of a prosthetic device.

Patient-specific 3D models of the human mandible are finding increasing utility in medical fields such as oral and maxillofacial surgery, orthodontics, dentistry, and forensic sciences. The efficient creation of personalized 3D bone models poses a key challenge in these applications. Existing solutions often rely on 3D statistical models of human bone, offering advantages in rapid bone geometry adaptation and flexibility by capturing a range of anatomical variations, but also a disadvantage in terms of reduced precision in representing specific shapes. Considering this, the proposed parametric model allows for precise manipulation using morphometric parameters acquired from medical images. This paper highlights the significance of employing the parametric model in the creation of a personalized bone model, exemplified through a case study targeting mandibular prognathism reconstruction. A personalized model is described as 3D point cloud determined through the utilization of series of parametric functions, determined by the application of geometrical morphometrics, morphology properties, and artificial neural networks in the input dataset of human mandible samples. With 95.05% of the personalized model’s surface area displaying deviations within −1.00–1.00 mm relative to the input polygonal model, and a maximum deviation of 2.52 mm, this research accentuates the benefits of the parametric approach, particularly in the preoperative planning of mandibular deformity surgeries.

Osteoporosis constitutes a significant public health concern necessitating proactive prevention, treatment, and monitoring efforts. Timely identification holds paramount importance in averting fractures and alleviating the overall disease burden. The realm of osteoporosis diagnosis has witnessed a surge in interest in machine learning applications. This burgeoning technology excels at recognizing patterns and forecasting the onset of osteoporosis, paving the way for more efficacious preventive and therapeutic interventions. Smart walkers emerge as valuable tools in this context, serving as data acquisition platforms for datasets tailored to machine learning techniques. These datasets, trained to discern patterns indicative of osteoporosis, play a pivotal role in enhancing diagnostic accuracy. In this study, encompassing 40 participants—20 exhibiting robust health and 20 diagnosed with osteoporosis—data from force sensors embedded in the handlebars of conventional walkers were gathered. A windowing action was used to increase the size of the dataset. The data were normalized, and k-fold cross-validation was applied to assess how well our model performs on untrained data. We used multiple machine learning algorithms to create an accurate model for automatic monitoring of users’ gait, with the Random Forest classifier performing the best with 95.40% accuracy. To achieve the best classification accuracy on the validation dataset, the hyperparameters of the Random Forest classifier were further adjusted on the training data. The results suggest that machine learning-based automatic monitoring of gait parameters could lead to accurate, non-laborious, cost-effective, and efficient diagnostic tools for osteoporosis and other musculoskeletal disorders. Further research is needed to validate these findings.

Proper fixation techniques are crucial in orthopedic surgery for the treatment of various medical conditions. Fractures of the distal humerus can occur due to either high-energy trauma with skin rupture or low-energy trauma in osteoporotic bone. The recommended surgical approach for treating these extra-articular distal humerus fractures involves performing an open reduction and internal fixation procedure using plate implants. This surgical intervention plays a crucial role in enhancing patient recovery and minimizing soft tissue complications. Dynamic Compression Plates (DCPs) and Locking Compression Plates (LCPs) are commonly used for bone fixation, with LCP extra-articular distal humerus plates being the preferred choice for extra-articular fractures. These fixation systems have anatomically shaped designs that provide angular stability to the bone. However, depending on the shape and position of the bone fracture, additional plate bending may be required during surgery. This can pose challenges such as increased surgery time and the risk of incorrect plate shaping. To enhance the accuracy of plate placement, the study introduces the Method of Anatomical Features (MAF) in conjunction with the Characteristic Product Features methodology (CPF). The utilization of the MAF enables the development of a parametric model for the contact surface between the plate and the humerus. This model is created using specialized Referential Geometrical Entities (RGEs), Constitutive Geometrical Entities (CGEs), and Regions of Interest (ROI) that are specific to the human humerus bone. By utilizing this anatomically tailored contact surface model, the standard plate model can be customized (bent) to precisely conform to the distinct shape of the patient’s humerus bone during the pre-operative planning phase. Alternatively, the newly designed model can be fabricated using a specific manufacturing technology. This approach aims to improve geometrical accuracy of plate fixation, thus optimizing surgical outcomes and patient recovery.

This study investigates the impact of annealing time, temperature, and layer height on the tensile strength and dimensional change of three 3D printing materials (PLA, PETG, and carbon fiber-reinforced PETG). Samples with varying layer heights (0.1 mm, 0.2 mm, and 0.3 mm) were annealed at temperatures ranging from 60–100 °C for 30, 60, and 90 min. Tensile tests were conducted, and regression models were developed to analyze the effects of these parameters on tensile strength. The models exhibited high accuracy, with a maximum deviation of only 5% from measured validation values. The models showed that layer height has a significantly bigger influence on tensile strength than annealing time and temperature. Optimal combinations of parameters were identified for each material, with PLA performing best at 0.1 mm/60 min/90 °C and PETG and PETGCF achieving optimal tensile strength at 0.1 mm/90 min/60 °C. PETGCF demonstrated smallest dimensional change after annealing and had the best modulus of elasticity of all the materials. The study employed experimental testing and regression models to assess the results across multiple materials under consistent conditions, contributing valuable insights to the ongoing discussion on the influence of annealing in 3D-printed parts.

In the last years, additive manufacturing technologies have been developed, especially direct metal laser sintering, and used in the dental and medical implant domains. Cardiovascular stents have evolved from bioinert, bare metal cages to biomimetic devices that promote tissue regeneration or healing. In this paper, comparisons concerning mechanical properties between Co–Cr alloy and cast 304L stainless steel were realized using FEM analysis, necessary for manufacturing cardiovascular stents by DMLS technology using Co–Cr alloy. The purpose of this paper consists of the evaluation of the contact angle at the interface of the Co–Cr alloy manufactured by DMLS, respectively, cast stainless steel 304L, and thin film deposition realized by the e-gun method (Ta2O5 and ZnO). Scanning electronic microscopy SEM and EDX techniques were employed for morphological investigation of the sintered samples manufactured by the DMLS process. They were also used for semi-quantitative and qualitative chemical and metallographic analyses. The e-gun coating was used to obtain thin films with the nanometer order of Ta2O5 and ZnO with a protective role to improve the corrosion resistance, roughness, and antiseptic role.

The authors wish to make the following correction to their paper [...]

Mechanical behavior and characteristics of two different types of materials: cast iron with lamellar graphite EN-GJL-250 and cast iron with spheroidal graphite EN-GJS-400-15 which were cast in ceramic molds using gravitational casting method has considered in this research. The ceramic molds were obtained by 3D printing method. First, a finite element analysis was developed to determine Tresca and von Mises stresses and the deformations of the ceramic molds under an applied pressure of 25 MPa. Samples were produced by gravitational casting using two types of cast iron materials. Mechanical tests were made using samples produced from these two types of materials and microstructure analysis evaluation of fractured zones was realized by scanning electron microscopy. Obtained results were finally used for designing, developing, and producing of one ‘hydraulic block’ of a railway installation by the Benninger Guss company of Switzerland.

Polyamide 12 (PA 22000) is a well-known material and one of the most biocompatible materials tested and used to manufacture customized medical implants by selective laser sintering technology. To optimize the implants, several research activities were considered, starting with the design and manufacture of test samples made of PA 2200 by selective laser sintering (SLS) technology, with different processing parameters and part orientations. The obtained samples were subjected to compression tests and later to SEM analyses of the fractured zones, in which we determined the microstructural properties of the analyzed samples. Finally, an evaluation of the surface roughness of the material and the possibility of improving the surface roughness of the realized parts using finite element analysis to determine the optimum contact pressure between the component made of PA 2200 by SLS and the component made of TiAl6V4 by SLM was performed.

This paper represents the focus on developing efficient algorithms that reduce the operations required to be employed in order to obtain complex surfaces milling finishing toolpaths for the three axis NC (Numerical Control) machine within the reverse engineering chain of processes. Direct machining is the process of generating efficient toolpaths directly from the digitized data, meaning the point cloud. The entire research is focused on determining the mathematical calculus able to interpret the data collected through the contact/noncontact 3D scanning process. In this direction, two algorithms were developed to generate ball-end mill finishing toolpaths for freeform surfaces using ordered/unordered point clouds. Practical work that validates author’s employed algorithms of obtaining finishing milling toolpaths uses the point cloud stored from the 3D scanning process in matrix found in ASCII files, which makes data interpreting easy.

In recent years in the dental field, new types of materials and techniques for the manufacturing of dental crowns and analog implants have been developed to improve the quality of these products. The objective of this article was to perform the surface characterization and determine the properties of Co-Cr alloy samples fabricated by the direct metal laser sintering (DMLS) process and coated by e-gun technology with thin films of Ta2O5 and ZnO. Both oxides are frequently used for dental products, in pharmacology, cosmetics, and medicine, due to their good anticorrosive, antibacterial, and photo-catalytic properties. Following the deposition of thin oxide films on the Co-Cr samples fabricated by DMLS, a very fine roughness in the order of nanometers was obtained. Thin films deposition was realized to improve the hardness and the roughness of the Co-Cr parts fabricated by the DMLS process. Surface characterization was performed using SEM-EDS, AFM, and XRD. AFM was used to determine the roughness of the samples and the nanoindentation curves were determined to establish the hardness values and modulus of elasticity.