Modeling Additive Manufacturing Process Research Articles

Additive Manufacturing of Linear Continuous Permittivity Profiles and Their Application to Cylindrical Dielectric Resonator Antennas

The utilization of additive manufacturing (AM) to engineer the permittivity profile of dielectric resonator antennas (DRAs) is considered. For the first time, the capabilities of AM are exploited to create continuously swept permittivity profiles and applied to cylindrical DRAs. The spatial variant lattices (SVL) synthesis algorithm is implemented to create the desired permittivity profiles from a single material, and resulting geometries are manufactured using a high-permittivity material in a fused deposition modeling AM process. Three individual antennas for global navigation satellite system bands are designed and manufactured, two inhomogeneous DRAs with continuous permittivity profiles along the radial and vertical axis, and one homogeneous DRA for comparison. The manufactured antennas are characterized by impedance, realized gain, and axial ratio. Experimental results agree well with simulations and show increased impedance-, gain-, and axial-ratio bandwidths for both inhomogeneous antennas compared to the homogeneous one.

Integration of Processing and Microstructure Models for Non-Equilibrium Solidification in Additive Manufacturing

Integration of models that capture the complex physics of solidification on the macro and microstructural scale with the flexibility to consider multicomponent materials systems is a significant challenge in modeling additive manufacturing processes. This work aims to link process variables, such as energy density, with non-equilibrium solidification by integrating additive manufacturing process simulations with solidification models that consider thermodynamics and diffusion. Temperature histories are generated using a semi-analytic laser powder bed fusion process model and feed into a CALPHAD-based ICME (CALPHAD: Calculation of Phase Diagrams, ICME: Integrated Computational Materials Engineering) framework to model non-equilibrium solidification as a function of both composition and processing parameters. Solidification cracking susceptibility is modeled as a function of composition, cooling rate, and energy density in Al-Cu Alloys and stainless steel 316L (SS316L). Trends in solidification cracking susceptibility predicted by the model are validated by experimental solidification cracking measurements of Al-Cu alloys. Non-equilibrium solidification in additively manufactured SS316L is investigated to determine if this approach can be applied to commercial materials. Modeling results show a linear relationship between energy density and solidification cracking susceptibility in additively manufactured SS316L. This work shows that integration of process and microstructure models is essential for modeling solidification during additive manufacturing.

Call for papers on special issue “Advances in additive manufacturing: modeling, design, and application”

Aim & Scope: Additive Manufacturing (AM) is revolutionizing the manufacturing industry. Building parts layer by layer makes fabrication of geometries which were impossible otherwise. Freedom of fabrication, rapid and low-cost prototyping, and reduction in material waste are only a few of advantages that AM offers to many industries from biomedical to aeronautics. Hence, AM is getting lots of interest over the past few years. These combined with lower cost of 3d printers is making this pace even faster. To keep up with the advancements in AM, this special issue aims to publish high quality research articles in the field of additive manufacturing and its related topics. This includes but not limited to alloy design for AM, new AM technologies and process optimization, process-microstructure-property, characterization of AM parts, modeling AM processes, topology optimization, fatigue, fracture, and failure analysis, tailoring properties, and functionally graded materials through AM. New applications are welcome, as well. We kindly invite you to submit a manuscript(s) for this Special Issue. Full papers, communications, and reviews are all welcome.

A manufacturing cost analysis framework to evaluate machining and fused filament fabrication additive manufacturing approaches

The goal of this research is to develop a costing framework and explore opportunities for fabricating components using additive manufacturing (AM) and machining approaches. The examples target plastic machining, and the fused deposition modeling AM process, but the general model structure is applicable for other AM processes as process knowledge is developed. The question “when is machining more cost-effective than AM” has not been comprehensively addressed. The purpose of this work is to develop a costing framework to provide insight on whether to use machining or AM. An estimation model which considers the process planning, setup, and fabrication time-cost elements is developed in a structured manner. This is challenging due to the machining process planning complexity, the decision-making, and the skill set required, especially for complex surface finish machining. This framework can be readily adapted to suit specific environments. The estimation time models are linked to a cost model, and comparisons are drawn, based on the form complexity and manufacturing quantity. An effective combination of AM and machining technologies could bring about a new hybrid manufacturing approach that meets the requirements of the next generation of production systems, especially for short-run production. A cost-benefit analysis is performed to illustrate solution approaches for designing additive, subtractive, or hybrid operation sets for a variety of components to highlight the merits of the presented approach. Exploring a larger solution space of processing options and their processing time and costs will allow designers to generate more cost-competitive solutions.

Study of the relationship between dimensional performance and manufacturing cost in fused deposition modeling

PurposeQuantifying and controlling the quality characteristics of parts produced by additive manufacturing (AM) processes has attracted significant interest in the research community. However, to increase the sustainability of AM processes, such quality characteristics need to be assessed together with life cycle performance of AM processes such as energy and material consumption and manufacturing cost. Although a few studies have been performed for several quality characteristics, i.e. surface roughness and tensile strength, the relationship between dimensional performance and manufacturing cost is still not well known for AM processes.Design/methodology/approachIn this paper, a comprehensive study of the dimensional performance and manufacturing cost of fused deposition modeling AM process is performed. Design of experiment technique is used, and the correlation of different cost components and the dimensional accuracy of parts are statistically studied.FindingsThe optimum process parameters for simultaneously optimizing the dimensional performance and manufacturing cost are identified. The analysis shows that as opposed to traditional manufacturing processes, obtaining a better dimensional performance is not necessarily associated with higher cost in the AM processes.Originality/valueAlmost no study and analysis for the combined dimensional performance and manufacturing cost has been performed for AM processes in the literature. It is known that within the context of traditional manufacturing processes, a natural trade-off governs the pursuit of higher dimensional performance and the manufacturing cost. However, as the AM process has a different nature compared with traditional manufacturing processes, the relationship between manufacturing cost and dimensional performance of parts has to be studied. Understanding this relationship will also help to establish a cost-optimal and sustainable tolerance allocation strategy in assemblies with AM components.

Metal additive-manufacturing process and residual stress modeling

Additive manufacturing (AM), widely known as 3D printing, is a direct digital manufacturing process, where a component can be produced layer by layer from 3D digital data with no or minimal use of machining, molding, or casting. AM has developed rapidly in the last 10 years and has demonstrated significant potential in cost reduction of performance-critical components. This can be realized through improved design freedom, reduced material waste, and reduced post processing steps. Modeling AM processes not only provides important insight in competing physical phenomena that lead to final material properties and product quality but also provides the means to exploit the design space towards functional products and materials. The length- and timescales required to model AM processes and to predict the final workpiece characteristics are very challenging. Models must span length scales resolving powder particle diameters, the build chamber dimensions, and several hundreds or thousands of meters of heat source trajectories. Depending on the scan speed, the heat source interaction time with feedstock can be as short as a few microseconds, whereas the build time can span several hours or days depending on the size of the workpiece and the AM process used. Models also have to deal with multiple physical aspects such as heat transfer and phase changes as well as the evolution of the material properties and residual stresses throughout the build time. The modeling task is therefore a multi-scale, multi-physics endeavor calling for a complex interaction of multiple algorithms. This paper discusses models required to span the scope of AM processes with a particular focus towards predicting as-built material characteristics and residual stresses of the final build. Verification and validation examples are presented, the over-spanning goal is to provide an overview of currently available modeling tools and how they can contribute to maturing additive manufacturing.