Deposition Manufacturing Process Research Articles

Multiconstraint quality–probability graph for quality monitoring of laser directed energy deposition manufacturing process

Quality monitoring of the laser directed energy deposition (LDED) manufacturing process by machine vision is essential to improve the reliability and economy of the LDED manufactured parts. For monitoring algorithms, graph-based semi-supervised learning can effectively learn supervised information from labelled data without the requirement of large amounts of manually labelled data. However, traditional graph algorithm for LDED quality monitoring is limited by insufficient use of label supervised information, inadequate consideration of the imbalance data, and lack of physically meaningful explanations and constraints on the propagation process for different types of defects. In this regard, a multiconstraint quality–probability graph (MCQPG) is proposed to monitor the quality during the LDED manufacturing process. MCQPG converts the extracted multifeatures into probability distributions, finds feature sets with similar distributions to the supervised information based on quality level standards, and uses multiconstraints to satisfy few labelled feature data, imbalance data distribution and physical consistency. For physical consistency, a nonlinear defect model is developed for crack and porosity defects, and a novel defect-guided objective prediction function is proposed, resulting in the construction of a quality level standard guided physical consistency constraint term. Experimental studies on several well-known and commonly used monitoring algorithms demonstrate that the proposed MCQPG algorithm achieves 0.96 on all four evaluation metrics (accuracy, precision, recall and F1 score), validating the effectiveness of MCQPG for LDED quality monitoring.

Ultrasonic induced additive powder deposition manufacturing

The powder deposition manufacturing process involves the discharge of fine metal powders through a nozzle into a crucible at controlled rates at specified locations. The discharge process is assisted by utilizing ultrasonic vibrations acting on the walls of a thin glass capillary tube. Powder deposition is carried out in patterns based on the sliced 3D models. This enables the creation of solid metal parts which require a lesser number of steps in the manufacturing process. Fine metal powders along with a support material of silica sand have been used in this process to accomplish the required 3D geometrical form. This paper discusses the assembly of the powder discharge device and the additive manufacturing process utilizing the discharge device.

A line-based flash heating method for numerical modeling and prediction of directed energy deposition manufacturing process

The part-scale directed energy deposition (DED) process is often accompanied by sizeable thermal stress and deformation. It is of great significance to predict the residual deformation and stress of the large component produced by DED. In this paper, a line-based flash heating (LFH) method was proposed and used as the multi-scale law in the thermo-mechanical model of the DED process. The building parameters of the DED process, such as bead dimensions, overlap, and scanning strategies, can be well considered. A series of experimental validation was carried out. Model sensitives and essential resolution, including length scaling factor and bead scaling factor, were identified and characterized. The whole processes of depositing two part-scale samples with different scanning strategies were simulated. Different scaling strategies, including the hybrid scaling strategy, were used in the simulation for the 60-layer model. The results between the simulation and experiments are in good agreement. The recommended critical values of length scaling factor and bead scaling factor are 312 and 0.2, respectively, when defining the critical value of prediction error as 10%. For the two part-scale models, the prediction error of the maximum residual deformation is less than 10% when using the bead scaling strategy with recommended scaling factors. Compared with the layer scaling technique, the hybrid scaling strategy improves the accuracy of prediction and controls the cost of calculation. This work provides a flexible multi-resolution framework for modeling the DED process and an important tool for further understanding the complex thermo-mechanical behaviors in the large DED component.

Research on Automated Defect Classification Based on Visual Sensing and Convolutional Neural Network-Support Vector Machine for GTA-Assisted Droplet Deposition Manufacturing Process

This paper proposes a novel metal additive manufacturing process, which is a composition of gas tungsten arc (GTA) and droplet deposition manufacturing (DDM). Due to complex physical metallurgical processes involved, such as droplet impact, spreading, surface pre-melting, etc., defects, including lack of fusion, overflow and discontinuity of deposited layers always occur. To assure the quality of GTA-assisted DDM-ed parts, online monitoring based on visual sensing has been implemented. The current study also focuses on automated defect classification to avoid low efficiency and bias of manual recognition by the way of convolutional neural network-support vector machine (CNN-SVM). The best accuracy of 98.9%, with an execution time of about 12 milliseconds to handle an image, proved our model can be enough to use in real-time feedback control of the process.

Low-temperature deposition manufacturing: A novel and promising rapid prototyping technology for the fabrication of tissue-engineered scaffold

Developed in recent years, low-temperature deposition manufacturing (LDM) represents one of the most promising rapid prototyping technologies. It is not only based on rapid deposition manufacturing process but also combined with phase separation process. Besides the controlled macropore size, tissue-engineered scaffold fabricated by LDM has inter-connected micropores in the deposited lines. More importantly, it is a green manufacturing process that involves non-heating liquefying of materials. It has been employed to fabricate tissue-engineered scaffolds for bone, cartilage, blood vessel and nerve tissue regenerations. It is a promising technology in the fabrication of tissue-engineered scaffold similar to ideal scaffold and the design of complex organs. In the current paper, this novel LDM technology is introduced, and its control parameters, biomedical applications and challenges are included and discussed as well.

Study on Low-Temperature Deposition Manufacturing Process Parameters of Three-Dimensional Chitosan Scaffold

From the perspective of forming bone scaffold, the technologic parameters of LDM which have important influence on the shape of the deposition material are studied. Through building experimental platform and using chitosan solution as experimental material, the influence of the temperature and the layer height on the lap of every fiber layer are firstly discussed in detail. Besides, the effects of nozzle diameter, the velocity of receiving device, the pressure of feeding device are also discussed. Then the above mentioned process parameters are all optimized, which make the forming mechanism of LDM to be clear. Finally, based on the optimal parameters, the scaffold with self-designed pore size and a high degree of pore interconnectivity, which meeting the requirements of the structure of tissue engineering are fabricated.

A Three-Dimensional Model of Droplet Impinging, Solidification and Suspension on the Substrate

A three-dimensional model was built to study a molten metal droplet impact on an edge of the substrate in droplet deposition manufacturing process for the first time. The whole calculation domain, including the substrate, was described using same fluid conservation equations, which is to say that the remolding and solidification of substrate was considered also. Droplet free surface was tracked by volume-of-fluid (VOF) algorithm. The effect of surface tension on the droplet was taken into consideration by means of considering surface tension to be a component of the body force. The simulated results show that the droplet in liquid phase can keep suspending on the substrate at a role of surface tension. A too high impact velocity would make parts of droplet splash away the substrate which is not allowed in manufacturing process. The offset between edge of droplet and side edge of substrate influences dramatically the impact of the droplet.

Study on Forecast of Forming Temperature of ABS Resin during Fused Deposition Manufacturing by Fuzzy Comprehensive Evaluation

The principle of fused deposition modeling was described, and significant dependence of product quality on nozzle temperature was discussed. The range of forming temperature of ABS resin was investigated by fuzzy comprehensive evaluation, and the optimized theoretical forming temperature was determined to be 216 oC which was very close to the actual value. The progress has important reference value to optimize some other extrusion parameters for technology on FDM machine, thus it underlies fused deposition manufacturing process for functional materials.

Research on Crack Generating in the Process of Hybrid Plasma and Laser Deposition Manufacturing

Crack is the common drawback in deposition manufacturing process with high energy beam, which usually leads to the manufacturing process being given up halfway. So it is important and urgent to investigate the generating principle of crack and establish relative means to prevent crack appearance. In this paper, the principle of crack generating in the process of hybrid plasma and laser manufacturing was studied experimentally and systematically. The influences of power system and shielding atmosphere on crack were researched. The results were summarized as follows: (1) The crack generating in the course of manufacturing is mainly heat crack. (2) Excessive energy density and temperature will result in crack. (3) The best method preventing part being manufactured from oxidation is to put the whole part into the inert gas.

Part decomposing algorithm based on STL solid model used in shape deposition manufacturing process

Shape deposition manufacturing is an innovative rapid prototyping technology combining CNC machining and deposition processes and in which if a surface of the part is visible from the build direction it can be directly shaped into desired geometry on part material; if the part features are undercut or face away from the build direction, these part features will be sculptured into the support material in order to form a negative cavity at first, then the part material is deposited into this negative cavity in order to replicate these features into part material. This process is cyclically repeated until all segments have been built. Finally, the sacrificial material is removed, and the finished part is left. This innovative technology has the benefits of commercial rapid prototyping technology; meanwhile, it inherits the accuracy and high surface quality of traditional machining process. For this process to be realized, it is essential to decompose the CAD solid model into a series of manufacturable segments which have no undercut surfaces at the data pretreatment step. In this paper, a solid decomposing strategy is proposed with a detailed discussion on the classification of the segments based on the value of triangle face normal vector, and then an algorithm for auto-decomposing a CAD solid model in STL data format is developed.

A Flexible Synchronous Powder Feeder for Electromagnetism Compress Digital Manufacturing of FGM Metal Component

Archiving functionally gradient materials (FGM) fabrication via digital manufacturing methods has attracted considerable attention in recent years. In this paper, a new FGM powder feeder and its flexible numerical motors control solution used in electromagnetism compressed plasma deposition manufacturing process was developed. The motors control hardware circuit and its Superior computer control program was introduced and analyzed. The powder feeder unit was based on the timing belt driving and Pneumatic conveying principle. The Superior computer control program was based on lab windows/CVI program developing environment with good man-machine conversation interface. Tests were made with Ni-based alloy powders, Fe-based alloy powders and ceramic powders in the particle average diameter of 15–350 Microns. Results showed that powders mixtures obtained from the device are continuous and stable. The precision of delivering powders mixture can be within 2% error scope comparing to the desired mixture quality and the flexible proportion of mixture can be easy changed in the computer control program by synchronously controlling the powder feeder rotation speed.

Abrasive wear property of laser melting/deposited Ti2Ni/TiNi intermetallic alloy

A wear resistant intermetallic alloy consisting of TiNi primary dendrites and Ti2Ni matrix was fabricated by the laser melting deposition manufacturing process. Wear resistance of Ti2Ni/TiNi alloy was evaluated on an abrasive wear tester at room temperature under the different loads. The results show that the intermetallic alloy suffers more abrasive wear attack under low wear test load of 7, 13 and 25 N than high-chromium cast-iron. However, the intermetallic alloy exhibits better wear resistance under wear test load of 49 N. Abrasive wear of the laser melting deposition Ti2Ni/TiNi alloy is governed by micro-cutting and plowing. Pseudoelasticity of TiNi plays an active role in contributing to abrasive wear resistance.

Microstructure and mechanical properties of laser melting deposited Ti2Ni3Si/NiTi Laves alloys

Two Ti2Ni3Si/NiTi Laves phase alloys with chemical compositions of Ni-39Ti-11Si and Ni-42Ti-8Si (%, mole fraction, the same below), respectively, were fabricated by the laser melting deposition manufacturing process, aiming at studying the effect of Ti, Si contents on microstructure and mechanical properties of the alloys. The Ni-39Ti-11Si alloy consisting of Ti2Ni3Si primary dendrites and Ti2Ni3Si/NiTi eutectic matrix is a conventional hypereutectic Laves phase alloy while the Ni-42Ti-8Si alloy being made up of NiTi primary dendrites uniformly distributed in Ti2Ni3Si/NiTi eutectic is a new hypoeutectic alloy. Mechanical properties of the alloys were investigated by nano-indentation test. The results show that the decrease of Si and the increase of Ti contents change the microstructures of the alloys from hypereutectic to hypoeutectic, which influences the mechanical properties of the alloys remarkably. Corrosion behaviors of the alloys were also evaluated by potentiodynamic anodic polarization curves.

Dry sliding wear property of a laser melting/deposited Ti 2Ni/TiNi intermetallic alloy

A wear resistant intermetallic alloy consisting of TiNi primary dendrite and Ti 2Ni matrix was fabricated by the laser melting deposition manufacturing process. Wear resistance of the Ti 2Ni/TiNi alloy was evaluated on a block-on-wheel dry sliding wear tester at room temperature under the loads of 98 N, 147 N and 196 N. Results indicate that the Ti 2Ni/TiNi intermetallic alloy exhibited high wear resistance due to its good combination of strength and toughness. Cover-layers were formed on the worn surface of the Ti 2Ni/TiNi intermetallic alloy during the dry sliding wear. Transferred layers played an active role in reducing wear mass loss by preventing the surface of Ti 2Ni/TiNi alloy from direct contact with the mating wheel.

Microstructure and corrosion properties of laser-melted deposited Ti2Ni3Si/NiTi intermetallic alloy

Abstract Ti2Ni3Si/NiTi intermetallic alloy consisting of Ti2Ni3Si primary dendrites and Ti2Ni3Si/NiTi eutectic matrix was fabricated by the laser melting deposition manufacturing process. Corrosion behavior of the alloy was investigated under anodic polarization and immersion corrosion test conditions in NaCl, H2SO4 and NaOH solutions. Results showed that alloy has outstanding corrosion-resistance, characterized by its wide passivation region and low passive anodic current density during the anodic polarization and low immersion corrosion rates. The excellent corrosion resistant properties of the alloy is attributed to the formation of a protective passive surface film as well as the high chemical stability and strong inter-atomic bonds inherent to Ti2Ni3Si and NiTi intermetallic.

Experiments and shape prediction of plasma deposit layer using artificial neural network

Plasma surfacing is an important enabling technology in high-performance coating applications. Recently, it is applied to rapid prototyping/tooling to reduce development time and manufacturing cost for the development of new products. However, this technology is in its infancy, it is essential to understand clearly how process variables relate to deposit microstructure and properties for plasma deposition manufacturing process control. In this paper, layer appearance of single surfacing under different parameters such as plasma current, voltage, powder feedrate and travel speed is studied. Back-propagation neural networks are used to associate the depositing process variables with the features of the deposit layer shape. These networks can be effectively implemented to estimate the layer shape. The results indicate that neural networks can yield fairly accurate results and can be used as a practical tool in plasma deposition manufacturing process.