Laser metal deposition (LMD) is an advanced technology of additive manufacturing which involves sophisticated processes. However, it is associated with high risks of failure due to the possible generation of cracks and bubbles. If not identified in time, such defects can cause substantial losses. In this paper, real-time monitoring of LMD samples and online detection of cracks by an infrared monochrome pyrometer (IMP) could mitigate this risk. An experimental platform for crack detection in LMD samples was developed, and the identification of four simulated cracks in a 316L austenitic stainless-steel LMD sample was conducted. Data at temperatures higher than 150 °C were collected by an IMP, and the results indicated that crack depth is an important factor affecting the peak temperature. Based on this factor, the locations of cracks in LMD-316L austenitic stainless-steel samples can be determined. The proposed technique can provide real-time detection of cracks through layers of cladding during large-scale manufacturing, which suggests its relevance for optimizing the technological process and parameters, as well as reducing the possibility of cracks in the LMD process.

Unmanned aerial vehicles (UAVs) often encounter complex ground conditions during takeoff and landing, especially on unpaved surfaces such as snow, sand, grass, and slopes, as well as under extreme conditions like strong winds and dense fog. In these scenarios, the landing gear may experience significant impact loads and vibrations. If the structure fails to absorb energy effectively and rebound promptly, it may compromise airframe stability, onboard system reliability, and operational safety. To optimize the energy absorption–rebound performance of UAV landing gear, this study employed thermoplastic polyurethane (TPU 98 A) to design five homogeneous and gradient lattice structures with varying cell parameters, fabricated via fused deposition modeling (FDM). Quasi-static compression tests were conducted to investigate load–displacement behavior, energy absorption, and rebound performance. A multidimensional evaluation system was established based on total energy absorption (EA), specific energy absorption (SEA), hysteresis loop area (HLA), energy recovery ratio (ERR), residual displacement ratio (RDR), and stiffness degradation ratio (SDR), enabling an integrated assessment of energy absorption and rebound. Results demonstrate that TPU lattice structures achieve high energy absorption while maintaining excellent rebound performance and structural stability.

Extrusion-based bioprinting is one of the most common biomanufacturing methods. The bioink composed of biomaterials and living cells is extruded into cylindrical filaments. The filaments are deposited on the substrate and stacked layer by layer to form a three-dimensional structure. During the extrusion process, the ink tends to accumulate at the nozzle, which clogs the nozzle and increases extrusion pressure, resulting in the decrease of cell survival rate. Here, we propose a method of using ultrasound to manipulate cells to assist the bioprinting process, which can alleviate nozzle clogging. The ceramic piezoelectric plate(PZT) is used to drive the nozzle to generate structural resonance, and the ultrasonic standing wave generated by the vibration make the cells/particles in the ink gather at the center of the nozzle, thereby reducing the risk of clogging of the nozzle. In this paper, we first analyze the mechanism of the standing wave generated in the cylindrical elastic nozzle and drive the cells to move under the PZT drive, and then use the finite element software to simulate the standing wave drive process. The results show that this method can be solved by a simple and low-cost device. The results indicate that this method has the possibility of using simple and low-cost equipment to solve the problem of nozzle clogging in bioprinting.

Extrusion-based printing technology has a promising development in the field of tissue engineering scaffold. Researchers package cells/particles in biomaterials and then extrude them through a nozzle and solidify to get a scaffold. This method can achieve uniform distribution of cells/particles in biomaterials or the addition of particles in biomaterials to enhance the mechanical properties of the scaffold. Sodium alginate is a kind of polysaccharide biomaterial which has a wide range of applications in the field of bioprinting. However, the diameter of the nozzle determines the accuracy of the cells/particles position in the alginate scaffold. A method of ultrasonic-assisted 3D bioprinting a composite of alginate and particles is proposed. The acoustic pressure can concentrate cells/particles to the center of the nozzle, which can achieve a more precise positioning than the diameter of the nozzle, and facilitate the purpose of depositing specific cells/particles to the determined location of the biomaterial.

Slicing is one of the core parts of the additive manufacturing software system, which completes the function of transforming the 3D model into a 2D profile. The adaptive slicing algorithm uses different layer thicknesses for layering in different areas according to the changes in the geometry of the mesh model. Where the model is more complex and the curvature changes a lot, a smaller layer thickness is used to approximate the model. In areas of large curvature of the model, maximum layer thickness is used to improve printing efficiency. With the development of additive manufacturing technology, grid model files such as STL have become larger and larger, and the amount of data needed to be processed by slicing software has increased dramatically. Existing slicing software is limited by computer hardware and cannot process massive data model. It greatly limits the development of additive manufacturing technology, so it is urgent to propose a new method to solve the rapid stratification of mass data model. In this paper, we proposed an adaptive slicing approach for processing STL massive data model in batches based on layer merging. At the same time, it is compared with the fixed-layer thickness slicing method, which shows that the algorithm can improve printing efficiency under the premise of ensuring accuracy.

The technology of arranging particles by ultrasound has matured. In recent years, this technology has been used as a basis for arranging particles in a photocurable resin for stereolithography (SL). In order to process the resin doped with particles to obtain a variety of particle arrangement patterns, most of the previous work chose to use different polygonal containers to obtain single-layer fiber angles. In this adjustment mode, the selectivity of the fiber angle is very poor, usually 45°, 90° and other common angles. In this work, we designed and manufactured a new ultrasound-assisted 3D printing platform that can flexibly adjust the thickness of the sandwich and the rotation angle of the sandwich. We will introduce the basic working principle and matching usage of the device, and show some basic print samples.