Progress in Additive Manufacturing

Pei, Eujin

doi: 10.1007/s40964-023-00454-3pmid: 38625220

Kobir, Md. Humaun; Yavari, Reza; Riensche, Alexander R.; Bevans, Benjamin D.; Castro, Leandro; Cole, Kevin D.; Rao, Prahalada

doi: 10.1007/s40964-022-00331-5pmid: N/A

The objective of this work is to predict a type of thermal-induced process failure called recoater crash that occurs frequently during laser powder bed fusion (LPBF) additive manufacturing. Rapid and accurate thermomechanical simulations are valuable for LPBF practitioners to identify and correct potential issues in the part design and processing conditions that may cause recoater crashes. In this work, to predict the likelihood of a recoater crash (recoater contact or impact) we develop and apply a computationally efficient thermomechanical modeling approach based on graph theory. The accuracy and computational efficiency of the approach is demonstrated by comparison with both non-proprietary finite element analysis (Abaqus), and a proprietary LPBF simulation software (Autodesk Netfabb). Based on both numerical (verification) and experimental (validation) studies, the proposed approach is found to be 5 to 6 times faster than the non-proprietary finite element modeling and has the same order of computational time as a commercial simulation software (Netfabb) without sacrificing prediction accuracy.

Laghi, Vittoria; Palermo, Michele; Bruggi, Matteo; Gasparini, Giada; Trombetti, Tomaso

doi: 10.1007/s40964-022-00335-1pmid: N/A

Current manufacturing techniques in the construction sector are slow, expensive and constrained in terms of architectural shapes. In other manufacturing sectors (such as automotive and aerospace) the use of automated construction systems significantly improved the safety, speed, quality and complexity of products. To realize real-scale structural elements for construction applications without ideally any geometrical constraints either in size or shape, the most suitable manufacturing solution for metallic elements is a directed energy deposition (DED) process referred to as wire-and-arc additive manufacturing (WAAM). The main advantage of WAAM relies on the possibility to create new shapes and forms following the breakthrough design tools for modern architecture as algorithm-aided design. At the same time, the printed part ensures high structural performances with reduced material use with respect to the conventional solution. The study presents a new approach called “blended” structural optimization, which blends topology optimization with basic principles of structural design and manufacturing constraints proper of WAAM technology, towards the realization of new efficient structural elements. The approach is applied to the case study of a I-type stainless steel beam on a multi-storey frame building. The approach could pave the way towards an efficient use of WAAM process to produce a new generation of structurally optimized elements for construction, with a more conscious use of the optimization tools and an efficient application of metal 3D printing.

Bhandari, Sunil; Lopez-Anido, Roberto A.

doi: 10.1007/s40964-022-00349-9pmid: N/A

The collapse of deposited thermoplastic composite material under self-weight presents a risk in large-format extrusion-based additive manufacturing. Two critical processing parameters, extrusion temperature and deposition rate, govern whether a deposited layer is stable and bonds properly with the previously deposited layer. Currently, the critical parameters are determined via a trial-and-error approach. This research work uses a simplified physics-based numerical simulation to determine a suitable combination of the parameters that will avoid the collapse of the deposited layer under self-weight. The suitability of the processing parameters is determined based on the maximum plastic viscous strains computed using a sequentially coupled thermo-mechanical numerical model. This computational tool can efficiently check if a combination of temperature and extrusion rate causes layer collapse due to self-weight, and hence minimize the manufacturing risk of large-format 3D-printed parts.

Kanagalingam, Sanjeevan; Dalton, Chris; Champneys, Peter; Boutefnouchet, Tarek; Fernandez-Vicente, Miguel; Shepherd, Duncan E. T.; Wimpenny, David; Thomas-Seale, Lauren E. J.

doi: 10.1007/s40964-022-00342-2pmid: N/A

Integration of advanced technologies have revitalised treatment methods in the current clinical practice. In orthopaedic surgery, patient-specific implants have leveraged the design freedom offered by additive manufacturing (AM) exploiting the capabilities within powder bed fusion processes. Furthermore, generative design (GD), a design exploration tool based on the artificial intelligence, can integrate manufacturing constraints in the concept development phase, consequently bridging the gap between AM design and manufacturing. However, the reproducibility of implant prototypes are severely constrained due to uncomprehensive information on manufacturing and post processing techniques in the detailed design phase. This paper explores the manufacturing feasibility of novel GD concept plate designs for High Tibial Osteotomy (HTO), a joint preserving surgery for a patient diagnosed with osteoarthritis in the knee. A design for AM (DfAM) workflow for a generatively designed HTO plate is presented, including; detailed DfAM of GD concept designs, fabrication of plate prototypes using electron beam powder bed fusion (PBF-EB) of medical grade Ti-6Al-4 V, post processing and inspection. The study established PBF-EB as a suitable manufacturing method for the highly complex GD plate fixations, through evaluating the impact of manufacturing and post processing on the surface finish and geometrical precision of the plate design features.

Fritz, Christian; Fischer, Lukas; Wund, Emmy; Zaeh, Michael Friedrich

doi: 10.1007/s40964-022-00343-1pmid: N/A

Artificial or human test bones are used for the biomechanical testing of implants. Human test bones are rare and not always available. These must, therefore, be substituted with artificial test bones. However, current artificial test bones are only available with specific characteristics (e.g., age groups or disease characteristics). Additionally, their mechanical properties are only comparable to a limited extent to those of a human bone. This paper presents a methodology for designing additively manufactured artificial test bones for biomechanical testing that replicate the mechanical behavior of a human bone. Topology optimization methods are used to generate the artificial test bone's internal structure. The geometric model is based on a computed tomography dataset of a human bone. The input data can be manipulated in advance to reproduce defects or disease patterns. The bone was fixed at the distal diaphysis and loaded with different biomechanical forces for topology optimization. Boundary conditions due to possible additive manufacturing processes were incorporated into the optimization to ensure manufacturability. The optimization result is compared with experimental data from a human bone. A bone-like internal structure and increased compliance of the topology-optimized test bone model compared to the commercial model were observed.

Ponticelli, Gennaro Salvatore; Venettacci, Simone; Giannini, Oliviero; Guarino, Stefano; Horn, Matthias

doi: 10.1007/s40964-022-00337-zpmid: N/A

This study deals with the fuzzy-based process optimization of 316L stainless steel components manufactured by Laser Powder Bed Fusion for high-performance applications. First, a systematic experimental plan was aimed at determining how the process input parameters, i.e., volumetric energy density and building orientation, affect density, ultimate tensile strength, hardness and roughness. Then, a fuzzy-based model, optimized through genetic algorithms, was developed and tested to find the best process window allowing the obtainment of the most performing mechanical properties as output. The use of the genetic algorithms concerned the identification of the optimal support of the fuzzy numbers at each membership level. The experimental results, when compared with a traditional annealed 316L stainless steel alloy, show an improvement of the mechanical properties, except for the roughness. The proposed fuzzy model shows the ability to replicate the experimental data with an increasing precision for increasing membership level, representing a new tool for understanding how much a modification at the input level can affect both the model precision and the process variability.

Hendl, Julius; Marquardt, Axel; Leyens, Christoph

doi: 10.1007/s40964-022-00338-ypmid: N/A

Electron beam powder bed fusion (EB-PBF) is a powder-bed fusion additive manufacturing process, which is suitable for fabricating high-performance parts for a wide range of industrial applications, such as medical and aerospace. Due to its deep curing capabilities, the metastable β-alloy Ti-5Al-5Mo-5V-3Cr (Ti-5553) is currently mostly used in the landing gear of airplanes. However, its great mechanical properties make it also attractive for small, complex, and load-bearing components. In this study, nine melting parameter sets, combining different scanning speeds and beam currents, were used in the EB-PBF ARCAM A2X system. Furthermore, the correlation between the microstructure and the mechanical properties was investigated and analyzed by applying µ-focus computer tomography and microscopic methods (optical, SEM/EDS). A significant influence of the different melting parameters on the microstructure as well as on the mechanical performance was found. In a subsequent step, three melting parameters were selected and the specimens were heat-treated (BASCA, STA) for further investigation. The experimental results of this work indicate that Ti-5553 parts can be manufactured successfully with high quality (ρ > 99.60%), and post-processing heat-treatments can be used to modify the microstructure in such a way that the parts are suitable for a large variety of possible applications.

Galati, Manuela; Giordano, Massimo; Iuliano, Luca

doi: 10.1007/s40964-022-00339-xpmid: N/A

Lattice structures are 3D open topologically ordered geometries that repeat an elementary cell in a predefined 3D space. Struts connected in specific nodes define the cell. Lattice structures are typical geometries that represent the design freedom unlocked by additive manufacturing (AM) and are unachievable with traditional processes. By tuning the morphometric parameters of the cell, its mechanical response can be significantly altered. Because of that, an accurate understanding of the process capabilities is crucial for achieving the nominally designed properties. Considering an electron beam powder bed fusion process, in this work, the same nominal lattice structure is produced under different processing conditions to determine the relationship between the process parameters, the actual cell morphometric parameters, and its mechanical response. Strut dimension, relative density and cross-section are measured using advanced X-ray computed tomography scanning analyses. Uniaxial compressive tests describe the mechanical performance. Inferential and descriptive statistical analyses are applied to investigate the effect of process parameters on the actual strut dimension and infer regression models. The results show that even slight variations of the process parameters significantly affect the morphometric structure parameters that result deviated from the nominal ones. The work demonstrates a strong correlation between all morphometric structure parameters and corresponding mechanical properties. The obtained regression model can predict the strut dimension from the process parameters, which can be then used to estimate the actual relative density and strut size. With this control and without any complex design procedure, a fine-tuning of process parameters allows a precise 3D spatial and localised control of structure properties to produce functionalised structures directly.

Rosa, Francesco; Cazzulani, Gabriele; Quadrelli, Davide Enrico; Casati, Riccardo

doi: 10.1007/s40964-022-00340-4pmid: N/A

Vibration abatement often requires the adoption of peculiar solutions and/or foundations. This paper presents an innovative solution to this problem, consisting in a phononic meta-material realized via Laser Powder Bed Fusion (L-PBF) capable to prevent the propagation of vibrations within specific frequency ranges. The integration of this meta-material within existing supporting structures can, therefore, greatly reduce the needing of foundations capable to stop vibrations. After a description of the design procedure of the meta-material that shows how to satisfy the constraints imposed by L-PBF technology, the manufactured sample is described and analyzed to predict its band-gaps. Finally, the theoretical results are compared with experimental measurements. These results show a good agreement between expected and actual meta-material behavior.