Structural and Dimensional Analysis by Computed Tomography of a Multi Geometric Template Manufactured by Fused Deposition Modeling

As a consequence of the development of AM, strategies have been developed to optimize the printing process, which focuses on reducing manufacturing time, such as using genetic algorithms (GAs), among others. The effect caused by the modification of path patterns is an effect of interest in two aspects: dimensional assurance focused on the compliance of the dimensions of the components in comparison with the digital design of the components, and the structural composition and resistance that the printing process itself can generate. This paper aims to present the effect of optimizing the path of fused filament fabrication (FFF) equipment on the dimensional finish and structural quality of a multi-geometric component using computed tomography. For this purpose, a template composed of 23 geometric elements, printed using FFF technology and PLA as the base material, is used. The results show an 11% reduction in the total process time required to print the component. The effect on the dimensional precision of different geometric elements was identified. In addition, it was possible to ensure that the structural quality of the multi-geometric component was not affected by the modification of the path required by the printing process.

An Overview of the Latest Progress in Internal Surface Finishing of the Additively Manufactured Metallic Components

Fast progress in near-net-shape production of parts has attracted vast interest in internal surface finishing. Interest in designing a modern finishing machine to cover the different shapes of workpieces with different materials has risen recently, and the current state of technology cannot satisfy the high requirements for finishing internal channels in metal-additive-manufactured parts. Therefore, in this work, an effort has been made to close the current gaps. This literature review aims to trace the development of different non-traditional internal surface finishing methods. For this reason, attention is focused on the working principles, capabilities, and limitations of the most applicable processes, such as internal magnetic abrasive finishing, abrasive flow machining, fluidized bed machining, cavitation abrasive finishing, and electrochemical machining. Thereafter, a comparison is presented based on which models were surveyed in detail, with particular attention to their specifications and methods. The assessment is measured by seven key features, with two selected methods deciding their value for a proper hybrid machine.

Improving the Performance of Steel Machining Processes through Cutting by Vibration Control

Machining processes through cutting are accompanied by dynamic phenomena that influence the quality of the processed surfaces. Thus, this research aimed to design, make, and use a tool with optimal functional geometry, which allowed a reduction of the dynamic phenomena that occur in the cutting process. In order to carry out the research, the process of cutting by front turning with transversal advance was taken into account. Additionally, semi-finished products with a diameter of Ø = 150 mm made of C45 steel were chosen for processing (1.0503). The manufacturing processes were performed with the help of two tools: a cutting tool, the classic construction version, and another that was the improved construction version. In the first stage of the research, an analysis was made of the vibrations that appear in the cutting process when using the two types of tools. Vibration analysis considered the following: use of the Fast Fourier Transform (FFT) method, application of the Short-Time Fourier-Transformation (STFT) method, and observation of the acceleration of vibrations recorded during processing. After the vibration analysis, the roughness of the surfaces was measured and the parameter Ra was taken into account, but a series of diagrams were also drawn regarding the curved profiles, filtered profiles, and Abbott–Firestone curve. The research showed that use of the tool that is the improved constructive variant allows accentuated reduction of vibrations correlated with an improvement of the quality of the processed surfaces.

X-ray Computed Tomography Procedures to Quantitatively Characterize the Morphological Features of Triply Periodic Minimal Surface Structures

Additively manufactured (AM) metallic sheet-based Triply Periodic Minimal Surface Structures (TPMSS) meet several requirements in both bio-medical and engineering fields: Tunable mechanical properties, low sensitivity to manufacturing defects, mechanical stability, and high energy absorption. However, they also present some challenges related to quality control, which can prevent their successful application. In fact, the optimization of the AM process is impossible without considering structural characteristics as manufacturing accuracy, internal defects, as well as surface topography and roughness. In this study, the quantitative non-destructive analysis of TPMSS manufactured from Ti-6Al-4V alloy by electron beam melting was performed by means of X-ray computed tomography (XCT). Several advanced image analysis workflows are presented to evaluate the effect of build orientation on wall thicknesses distribution, wall degradation, and surface roughness reduction due to the chemical etching of TPMSS. It is shown that the manufacturing accuracy differs for the structural elements printed parallel and orthogonal to the manufactured layers. Different strategies for chemical etching show different powder removal capabilities and both lead to the loss of material and hence the gradient of the wall thickness. This affects the mechanical performance under compression by reduction of the yield stress. The positive effect of the chemical etching is the reduction of the surface roughness, which can potentially improve the fatigue properties of the components. Finally, XCT was used to correlate the amount of retained powder with the pore size of the functionally graded TPMSS, which can further improve the manufacturing process.

Effects of Thermal Annealing on Femtosecond Laser Micromachined Glass Surfaces

Femtosecond laser micromachining (FLM) of fused silica allows for the realization of three-dimensional embedded optical elements and microchannels with micrometric feature size. The performances of these components are strongly affected by the machined surface quality and residual roughness. The polishing of 3D buried structures in glass was demonstrated using different thermal annealing processes, but precise control of the residual roughness obtained with this technique is still missing. In this work, we investigate how the FLM irradiation parameters affect surface roughness and we characterize the improvement of surface quality after thermal annealing. As a result, we achieved a strong roughness reduction, from an average value of 49 nm down to 19 nm. As a proof of concept, we studied the imaging performances of embedded mirrors before and after thermal polishing, showing the capacity to preserve a minimum feature size of the reflected image lower than μ5μm. These results allow for us to push forward the capabilities of this enabling fabrication technology, and they can be used as a starting point to improve the performances of more complex optical elements, such as hollow waveguides or micro-lenses.

A Multiscale Topographical Analysis Based on Morphological Information: The HEVC Multiscale Decomposition

In this paper, we evaluate the effect of scale analysis as well as the filtering process on the performances of an original compressed-domain classifier in the field of material surface topographies classification. Each surface profile is multiscale analyzed by using a Gaussian Filter analyzing method to be decomposed into three multiscale filtered image types: Low-pass (LP), Band-pass (BP), and High-pass (HP) filtered versions, respectively. The complete set of filtered image data constitutes the collected database. First, the images are lossless compressed using the state-of-the art High-efficiency video coding (HEVC) video coding standard. Then, the Intra-Prediction Modes Histogram (IPHM) feature descriptor is computed directly in the compressed domain from each HEVC compressed image. Finally, we apply the IPHM feature descriptors as an input of a Support Vector Machine (SVM) classifier. SVM is introduced here to strengthen the performances of the proposed classification system thanks to the powerful properties of machine learning tools. We evaluate the proposed solution we called "HEVC Multiscale Decomposition" (HEVC-MD) on a huge database of nearly 42,000 multiscale topographic images. A simple preliminary version of the algorithm reaches an accuracy of 52%. We increase this accuracy to 70% by using the multiscale analysis of the high-frequency range HP filtered image data sets. Finally, we verify that considering only the highest-scale analysis of low-frequency range LP was more appropriate for classifying our six surface topographies with an accuracy of up to 81%. To compare these new topographical descriptors to those conventionally used, SVM is applied on a set of 34 roughness parameters defined on the International Standard GPS ISO 25178 (Geometrical Product Specification), and one obtains accuracies of 38%, 52%, 65%, and 57% respectively for Sa, multiscale Sa, 34 roughness parameters, and multiscale ones. Compared to conventional roughness descriptors, the HEVC-MD descriptors increase surfaces discrimination from 65% to 81%.

Using Wavelet Packet Transform for Surface Roughness Evaluation and Texture Extraction

Surface characterization plays a significant role in evaluating surface functional performance. In this paper, we introduce wavelet packet transform for surface roughness characterization and surface texture extraction. Surface topography is acquired by a confocal laser scanning microscope. Smooth border padding and de-noise process are implemented to generate a roughness surface precisely. By analyzing the high frequency components of a simulated profile, surface textures are separated by using wavelet packet transform, and the reconstructed roughness and waviness coincide well with the original ones. Wavelet packet transform is then used as a smooth filter for texture extraction. A roughness specimen and three real engineering surfaces are also analyzed in detail. Profile and areal roughness parameters are calculated to quantify the characterization results and compared with those measured by a profile meter. Most obtained roughness parameters agree well with the measurement results, and the largest deviation occurs in the skewness. The relations between the roughness parameters and noise are analyzed by simulation for explaining the relatively large deviations. The extracted textures reflect the surface structure and indicate the manufacturing conditions well, which is helpful for further feature recognition and matching. By using wavelet packet transform, engineering surfaces are comprehensively characterized including evaluating surface roughness and extracting surface texture.