In the world of manufacturing there are many ways to create the desired product. Historically, conventional machining techniques, such as CNC machining or drill presses, are used because of lower operational cost and quicker production rates than advanced machining processes. However, with the advances in technology, material, metallurgical sciences and process design, advanced machining and manufacturing process are quickly closing the gap between conventional machining and advanced manufacturing. Advanced machining mechanical processes are defined as follows : machines that achieves higher surface finish, machines that address the issue of environmental effects of mechanical machining processes, and machines that focuses on high-speed, cryogenic and precision mechanical machining.
An example of an advanced additive machine that is becoming more common in the recent years is the 3D printing machine. The development of the economical 3D printers that are readily available and easy enough to be used by elementary school students has made this machine conventional. However, there are many forms of 3D printing that are far from conventional such as fused deposition modeling (FDM) , material jetting and 3D metal printing. In this report, we will be focusing on metal 3D printing: how the metal 3D printing process works; common metal types used for metal 3D printing and their properties, recent advances in metal 3D printing, the parameters of metal 3D printing and what are its various applications and uses, process modeling and simulation and the possible environmental and health effects.(Frazier and Performance 2014) Before jumping into metal 3D printing, we will need to define some terminology. The two main terms that comes into mind when discussing metal 3D printing are Selective Laser Melting (SLM) and Direct Metal Laser Sintering (DMLS). Both are metal additive manufacturing processes that belong to the powder bed fusion 3D printing family. Both use laser to scan and fuse the metal powder particles, bonding them together and building the part layer by layer. However the important difference between them is how they produce the parts : SLM produces the parts from a single metal whereas DMLS produces the parts from metal alloys.
Get your 100% original paper on any topic done3D metal printing, as is already known from its name, is a subset of 3D printing with the difference between the two being 3D metal printing uses metal to print 3D structures. Similar to 3D printing, 3D metal printing fuses layers of metals together using a laser. While there are many ways to deposit metals, the general process involves filling a 3D printing chamber with an inert gas to minimize the oxidation of the metal powder then heated to the optimal build temperature; this is followed by depositing a thin layer of metal powder and fusing the particles with a laser. This process is controlled by scanning the structure with the laser, and the process is repeated until the desired structure is complete. (Sames, List et al. 2016). Whatever powder is not used, can be recycled for a later use – typically less than 5% of it is wasted. Figure 1 shows the schematic diagram of a SLM powder-bed process. Figure 1: Schematic diagram of SLM powder-bed process There are numerous exciting latest developments in metal 3D printing and new research is coming out of academia every year where people are using this technology for various printing methods and concepts. One of the recent developments that has come up that is currently being studied is how to use meteorites as a printing material for 3D metal printers.(Lietaert, Thijs et al. 2018)
Typically, the choice of metal is usually aluminum, copper, titanium or other alloys. This idea looks at the prospect of asteroid mining and using this abundant resource to 3D print spare components such as: tools and various microstructures aboard spacecraft during missions, to ensure that any components are optimized for the local microgravity. Researchers have already proven that moon rock can work and another team of researchers have proven the concept of using iron-rich meteorites as a manufacturing material. Although this research needs more work, the team was able to powder the iron meteorites using gas atomization methods and was able to produce a full structural part. The parts did contain some minor defects, but it showcases a new proof of concept that higher density structures could be made in the future. In another different research area, a group of researchers have developed a new 3D metal printing approach with allows nanotwinned copper to be printed for the first time.(Behroozfar, Daryadel et al. 2018)
The approach that this group used was vulnerable ery unique: use a microscale 3D printer at room temperature that uses a localized pulse electrode electro-deposition between two coherent twin boundaries. The nanotwinned copper material printed by the researchers turned out to be fully dense and contained almost no impurities with very little defects. The material also showed no interface between the layers and was found to possess good mechanical such as tensile strength, hardness, and electrical, such as conductivity, properties. The final development that is discussed in the paper is a new method developed my Deshpande and Hsu called acoustoplastic metal direct-wire(Deshpande and Hsu 2018). Here inter and intra layer mass transport which results in metallurgical bonding across tiny voxels were obtained. When the voxels were forming, the temperature rose by 5C from the ambient room temperature of 25C. In addition to the temperature increase, acoustic energy-induced microstructural changes during the process were also observed. This work suggests that feasibility of a metal fusion at room temperature but also the a new micro structural transformation process that is currently being investigated.
In the past few years, metal 3D printing has become increasingly popular and this is due to each metal offering a unique set of practical as well as aesthetic properties in a variety of applications. With it’s rapid growth and simplicity of use, this renowned technology has found several applications. One of the key hot topics and its applications comes in aerospace and defense. From maintenance centers, naval ships and military outposts, 3D metal printing systems are changing everything from fleet management workflow to maintaining huge inventory of quick replacement parts on demand. Rapid 3D metal printing is having a significant effect on battlefield armor, ballistic munitions and weapons. From the aerospace sector, turbine blades, aircraft frames and even jet engines are slowing moving away from traditional methods and looking to be rapidly developed by 3D metal printing. Most of the alloys in the aerospace or defense sectors aluminum based. Another rapidly developing market for 3D metal additive manufacturing comes from medical device applications. Technology has been optimized for biocompatible material powder such as titanium which target specific properties that generate response from neighboring cells and tissues of orthopedic implants such as hip or knee.
Process modeling and simulation, include building plan and operation optimization, are essential for AM system. Under certain performance requirements, it can provide the required parameters, such as temperatures, droplet sizes, shape accuracy etc. There are a variety of approaches for the process modeling of additive manufacturing (AM) of metals. With all of the benefits of additive manufacturing including but not limited to creating extremely complex structures, it is very important to understand how the material will perform in this new state. Another huge benefit of Additive Manufacturing is that it allows you to design the material properties based on things like the microstructure to meet performance requirements (Francois, MM et al. 2017). Meeting these performance requirements will only be doable if the AM of metals has an accurate way of modeling the process. The essential in determining the resulting material properties is the thermal history generated by AM.
The material properties include micro-structure, residual stress, distortion etc. There are two main types of technologies relating to additive metal manufacturing and these are the powder-bed method and the directed energy deposition method. For the powder-bed method, a thin layer of powder is laid down and then melted with a laser; for the directed energy deposition method powder or wire is fed and the laser heat deposits the material immediately. When focusing on a macro scale, the main simulations of solidification processes occur utilizing Computational Fluid Dynamics (CFD) Software. The stresses are computed using Finite-Element Analysis (FEA) Software. The CFD software solves a system of non-linear equations representing motions of fluids and phase changes. The FEA software does thermomechanical modeling to look at heat transfer and deformation (Francois, MM et al. 2017). CFD and FEA need to work together to help predict behavior of the component in application. When simulating the Powder-Bed method, models look at the interaction between the laser and the powder, the vaporization effects, and the effect of the laser energy input. The models look at temperature of the melt pool and can be used to study the part density and surface finish (both of which are important for application). For direct energy deposition, a model of the mass source and the added heat is required. One software used is called Truchas, which is a thermos-mechanical modeling tool used to simulate this process.
Looking at the models created by these methods, you can adjust the machine parameters so that your finished components will meet all the appropriate material properties requirements and better predict how the component will behave under the stresses of its application. The use of a Finite Element heat transfer model can predict the temperature fields used to predict grain growth during the AM process. This information can be used to predict the mechanical behavior and help determine points of fatigue cracking which has a huge use in determining whether the process will be viable for a specific application (Liu, Wing et al. 2018) One method used to model metal AM is kinetic Monte Carlo. For AM of metals, the different heat sources can cause extreme changes in the microstructure. One difficult relationship to determine is that between the grain size and shape of the metal and the temperature profiles. The kinetic Monte Carlo model can be used to predict this three – dimensional grain structure analyzing the molten zones and grain boundaries (Rodgers, Theron et al. 2017).
Another approach comes from modeling using the Multivariate Gaussian Processes (MVGPs). This approach looks at the thermal history of the deposited material and can give a comprehensive understanding of the thermo-physical factors the material deposited is subjected too. The MVGPs can compare parameters of models to experiments to help predict characteristics of the melted material. The MVGPs will allow a limited number of experiments to give the base for modeling and predicting behavior of other scenarios where things like material and material properties are changed. (Mahmoudi, M et al. 2018). Overall, these methods show a small glimpse into the modeling of metal AM. Some companies including 3DSim and Sigma Labs Inc. are working on the software development for metal printing process, however, concurrent process simulation and modeling still need a lot more research. The concise point is that an accurate model is necessary to help predict the future of metal AM and how its uses will change the world of manufacturing. Helping predict the behavior of AM through these modeling examples will prove to show how endless the possibilities of AM truly is.
Metal based additive manufacturing is emerging as the next generation in parts manufacturing. Aerospace, defense and medical devices are looking to develop new conceptual designs and products using metal based additive manufacturing due to its speed and flexibility. However, this process is not without its fault. Variations have been recorded showing inadequate control over dimensional tolerances, surface roughness, porosity, and other defects in built parts. It is possible to control these variables using real-time processes that currently lack adequate process measurement methods. Product quality is one of the most important consideration when producing any product for commercial use. Quality drives customer satisfaction which in turn drives success in a competitive market.
To achieve any of these critical qualities in a product, manufacturing control has to be optimised. Currently, metal based additive layer manufacture has been utilised to produce parts for aerospace, tool making, dental and medical industries. Here, this section will talk about some of the the variation that occur with undertaking of an metal additive manufacturing process using process control parameters. Process variables such as feed stock, thermal conductivity, and material delivery rates are only some of the many process variations /challenges which result in quality issues in not only metal additive manufacturing but also in traditional manufacturing methods such as casting . All of these and more have various effects on dimensional tolerances, porosity and other defects in build parts. (O’Regan, Prickett et al. 2016) Feedstock is established as being vitally important to the quality of a part. Material suppliers provide composition limits, size distribution and spherical measurements, but do not provide information on the stock condition. The size distribution has been found to be a major factor in producing dense parts and that recycling the powder can increase the size of the powder particles. Investigations in powder size distribution have found that with an increase of powder size there is an increase in part porosity.(O’Regan, Prickett et al. 2016)
Thermal conductivity effects the finish on a build. When the build process occurs, and an object is being produced there is a major difference in the thermal coefficients between powder and the consolidated metallic material. The consolidated material acts as a heat sink and is more conductive than the powder surrounding it. A large differential in temperature between the powder and the consolidated metallic material can cause the “edge-effect”. Random-fill scan strategies were found to minimize the high ridges from the surface because heat could be dissipated more evenly across the build surface. (O’Regan, Prickett et al. 2016)
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