Additive manufacturing (AM) has revolutionized production across industries, yet challenges persist in achieving optimal part quality. This paper studies the enhancement of post-processing techniques to elevate the overall quality of AM-produced components. This study focuses on optimizing various post-processing methodologies to address prevalent issues such as surface roughness, dimensional accuracy, and material properties. Through an extensive review, this article identifies and evaluates a spectrum of post-processing methods, encompassing thermal, chemical, and mechanical treatments. Special attention is given to their effects on different types of additive manufacturing technologies, including selective laser sintering (SLS), fused deposition modeling (FDM), and stereolithography (SLA) and their dedicated raw materials. The findings highlight the significance of tailored post-processing approaches in mitigating inherent defects, optimizing surface finish, and enhancing mechanical properties. Additionally, this study proposes novel post-processing procedures to achieve superior quality while minimizing fabrication time and infrastructure and material costs. The integration of post-processing techniques such as cleaning, surface finishing, heat treatment, support structure removal, surface coating, electropolishing, ultrasonic finishing, and hot isostatic pressing (HIP), as steps directly within the additive manufacturing workflow can immensely contribute toward this direction. The outcomes displayed in this article not only make a valuable contribution to the progression of knowledge regarding post-processing methods but also offer practical implications for manufacturers and researchers who are interested in improving the quality standards of additive manufacturing processes.

Additive manufacturing has been widely used in various industries, including the healthcare sector. Over the last few decades, AM has been playing an important role in the medical field in different areas, including surgical planning, implants, and educational activities. For surgical applications, AM can help surgeons practice and plan an operation until they are confident with the process. This can help to reduce operational risk and time. In addition, it can help to demonstrate the problem to other colleagues. AM has also been used to produce 3D models to teach students and doctors about human anatomy. This paper aims to comprehensively review the diverse applications of additive manufacturing within the domains of surgical planning and medical education. By focusing on the multifaceted roles played by AM in these critical areas, a contribution to the growing body of knowledge that underscores the transformative potential of this technology in shaping the future of healthcare practices is sought to be made.

Most metropolitan areas in the world are facing major solid-waste-disposal problems. The solid-waste problem is considered one of the major environmental problems that countries and environmental organizations are paying increasing attention to at present, not only due to its negative effects on public health and the environment, but also due to the dangers it may cause to the nearby residential communities. One of the visible solutions is to reuse solid waste as a partial replacement of concrete constituents. In this investigation, fine aggregate was replaced with crumb rubber at four different volumetric percentages, ranging from 5 to 20% with a 5% step size. A novel treatment technique based on a combination of chemical and thermal treatments of a crumb rubber surface was adopted. A superplasticizer was added to improve both the workability and the strength of the concrete mixtures. The mixtures were assessed in fresh and hardened phases and compared with a control mix. In the fresh phase, the mixtures were evaluated regarding workability and wet density; and in the hardened phase, compressive strength after 180 days, tensile and flexural strength after 90 days, dry density, and absorption were investigated. Additionally, the mixes were assessed using non-destructive tests, namely, the ultrasonic pulse velocity test, rebound hammer test, and core test. The results showed that the addition of rubber particles to concrete decreased the compressive strength, tensile strength, and flexural strength in comparison with control concrete. An empirical equation based on combined analysis with R² = 0.95 was derived. At the age of 180 days, the compressive strength of rubberized concrete varied from 34 to 42 MPa. From a structural point of view, its strength is regarded as acceptable.

The use of rubberized concrete has become increasingly popular as a means of disposing of waste materials, such as used and end-of-life tires, while also providing an effective solution for construction applications. The strength and durability of rubberized concrete can be negatively affected by temperature fluctuations, but little is known about the performance of this material. Hence, the work presented herein aims to evaluate the performance of rubberized concrete when it is exposed to different temperature levels. In this study, rubberized concrete specimens were prepared by replacing 5–20% of crumb rubber by volume of fine aggregate. The specimens underwent a curing process for 28 days, followed by exposure to temperatures of 200 °C, 400 °C, and 600 °C for a period of 2 h. The residual test and normal cooling method were adapted. Surface characteristics by visual inspection, the residual weight, compressive strength, splitting tensile strength, ultrasonic pulse velocity, and dynamic modulus of elasticity were assessed and compared to unheated specimens. The study’s findings revealed that, when exposed to temperatures between 200 °C and 400 °C, rubberized concrete containing a 5% to 15% rubber content experienced less reduction in compressive strength than conventional concrete, which showed a reduction of 43% to 48.5%. Also, it was observed that the splitting tensile strength was more sensitive to elevated temperatures than the compressive strength.

The main purpose of this paper is to present a comprehensive and systematically organized overview of the current state of vibration monitoring and measurement techniques used in railway stock. It aims to raise awareness of significant technological developments in recent years and their practical applications. The scope of the analysis is strongly informed by established European norms, fundamental research efforts across the continent, and the practical needs of the railway sector. Last but not least, we hope this paper serves as a valuable reference point for engineers, researchers, and decision-makers working within the complex context of railway system design, maintenance, and evolving regulations. For effective monitoring of railway vehicle vibrations, a combination of specialized measurement methods and system architectures is recommended. These approaches are carefully developed to capture the dynamic responses of critical components of the railway vehicle, thereby providing invaluable data. This information is essential for thorough condition monitoring, improved ride comfort, and a deeper structural understanding of vehicle quality throughout its lifecycle.

This paper deals with the speed control of a permanent magnet synchronous generator (PMSG)-based marine current turbine (MCT). Indeed, to increase the generated power and therefore the efficiency of an MCT, a nonlinear controller has been proposed. PMSG has been already considered for similar applications particularly wind turbine systems using mainly PI controllers. However, such kinds of controllers do not adequately handle some of tidal resource characteristics such as turbulence and swell effects. Indeed, these may decrease the MCT performances. Moreover, PMSG parameter variations should be accounted for. Therefore, a robust nonlinear control strategy, namely high-order sliding mode control, is proposed. The proposed control strategy is inserted in a global simulation tool that accounts for the resource and the marine turbine models. Simulations using tidal current data from the Raz de Sein (Brittany, France), and experiments on a 7.5-kW real-time simulator are carried out for validation purposes.