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.

Geometrically accurate and anatomically correct threedimensional geometric models of human bones or bone sections are essential for successful pre-operative planning in orthopedic surgery. For such purposes, 3D polygonal models of bones are usually created based on Computer Tomography (CT) or Magnetic Resonance Imaging (MRI) data. In cases where there is no CT or MRI scan, or part of bone is missing, such three-dimensional polygonal models are difficult to create. In these situations predictive bone models are commonly used. In this paper, the authors describe the developed a software system for creation of Human Bones Customized Polygonal models (HBCP) which is based on the use of the predictive parametric bone model. The software system enables creation of patient-specific polygonal models of bones, by using only a limited number of parameter values. Parameter values can be acquired from volumetric medical imaging methods (CT, MRI), or from two-dimensional imaging methods (i.e. Xray). This paper introduces the new approach to the process of creation of human bones geometrical models which are based on the anatomical landmark points. Testing of the HBCP for the cases of femur bone samples has shown that created bone and bone region models are characterized by a good level of anatomical and morphometric accuracy compared to the results presented in similar researches.

Although external fixation is being widely used by orthopedic surgeons in the treatment of bone fractures, the surgical procedure and recovery are still followed by a number of possible complications which can significantly decrease the treatment’s efficiency (cost) and effectiveness (optimal healing). Inability of the physician to have continuous insight into different data, fracture healing process, patient’s behavior and environmental factors could be considered as a reason for these complications. In this paper, we propose the improvement of a fixation device design, which implements paradigms of aware, sensing, smart and active devices and thus, enables real-time monitoring of bone fracture healing. Such a design is considered as IoT gateway, capable to classify occurrences of events and milestones in patient recovery process, based on the data from different sensors, and report those to the specialists or related Healthcare Information System. The design is implemented in the example of classifying patient’s compliance to the prescribed behavior in the postoperative treatment of bone fractures.