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J. Manuf. Mater. Process., Volume 5, Issue 4 (December 2021) – 39 articles

Cover Story (view full-size image): The fatigue behavior of components made of high-strength steel alloys is of elementary importance, especially for components exposed to high cyclical loads. To a great extent, for machined components, the fatigue strength is influenced by the surface integrity properties generated during the manufacturing process. While the measurement of the mechanical load using dynamometers is well established, in-process temperature measurements are challenging, especially for drilling processes due to the process kinematics and the difficult-to-access cutting zone. To investigate the impact of the thermomechanical load during the single-lip deep hole drilling process on the produced surface integrity, an in-process measurement using a was developed and applied for different cutting parameters. View this paper.
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13 pages, 3753 KiB  
Article
Hybrid Manufacturing of Stiffening Grooves in Additive Deposited Thin Parts
by Valentino A. M. Cristino, João P. M. Pragana, Ivo M. F. Bragança, Carlos M. A. Silva and Paulo A. F. Martins
J. Manuf. Mater. Process. 2021, 5(4), 140; https://doi.org/10.3390/jmmp5040140 - 20 Dec 2021
Cited by 3 | Viewed by 3235
Abstract
This paper is focused on the hybridization of additive manufacturing with single-point incremental forming to produce stiffening grooves in thin metal parts. An analytical model built upon in-plane stretching of a membrane is provided to determine the tool force as a function of [...] Read more.
This paper is focused on the hybridization of additive manufacturing with single-point incremental forming to produce stiffening grooves in thin metal parts. An analytical model built upon in-plane stretching of a membrane is provided to determine the tool force as a function of the required groove depth and to estimate the maximum allowable groove depth that can be formed without tearing. The results for additively deposited stainless-steel sheets show that the proposed analytical model can replicate incremental plastic deformation of the stiffening grooves in good agreement with experimental observations and measurements. Anisotropy and lower formability caused by the dendritic-based microstructure of the additively deposited stainless-steel sheets justifies the reason why the maximum allowable depth of the stiffening grooves is approximately 27% smaller than that obtained for the wrought commercial sheets of the same material that are used for comparison purposes. Full article
(This article belongs to the Topic Additive Manufacturing)
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<p>(<b>a</b>) Fabrication of sheet metal panels by stretching; strengthening of sheet metal panels by (<b>b</b>) longitudinal stringers and by (<b>c</b>) longitudinal stiffening grooves.</p>
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<p>(<b>a</b>) Schematic representation of the hybrid manufacturing route to produce the AISI 316L stainless-steel sheets with stiffening grooves. (<b>b</b>) Photograph showing the additively manufactured and wrought commercial sheets before creating the stiffening grooves.</p>
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<p>Flow stress of the additively deposited and wrought commercial AISI 316L stainless-steel sheets for the parallel (P), inclined (I) and transverse (T) directions with respect to the build or rolling directions, respectively.</p>
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<p>Fracture forming limits of the additively deposited and wrought commercial AISI 316L stainless-steel sheets in principal strain space (data obtained from [<a href="#B14-jmmp-05-00140" class="html-bibr">14</a>]).</p>
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<p>(<b>a</b>) Schematic representation of the stiffening groove with main notation; (<b>b</b>) schematic representation of the area corresponding to the local contact between the tool and the sheet placed immediately ahead (z-direction).</p>
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<p>(<b>a</b>) Principal strain space showing the experimental strains that were measured by circle grid analysis in both additively deposited and wrought commercial sheets with photographs, showing details of the test specimens; (<b>b</b>) microstructures of metallographic samples taken from the (<b>left</b>) additively deposited and (<b>right</b>) wrought commercial AISI 316L stainless-steel sheets.</p>
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<p>Influence of material strain hardening on the evolution of the normalized force per unit of length with the groove depth.</p>
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<p>Evolution of the force per unit of length with the groove depth for the (<b>a</b>) additively deposited and (<b>b</b>) wrought commercial AISI 316L stainless-steel sheets. The dashed horizontal lines in both graphics correspond to the critical values and the intersections provide the maximum allowable predicted depths <math display="inline"><semantics> <mrow> <msub> <mi>H</mi> <mrow> <mi>m</mi> <mi>a</mi> <mi>x</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>Evolution of the tool force with groove depth for the (<b>a</b>) additively deposited and (<b>b</b>) wrought commercial AISI 316L stainless-steel sheets.</p>
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19 pages, 9314 KiB  
Article
Local Shielding Gas Supply in Remote Laser Beam Welding
by Klaus Schricker, Andreas Baumann and Jean Pierre Bergmann
J. Manuf. Mater. Process. 2021, 5(4), 139; https://doi.org/10.3390/jmmp5040139 - 17 Dec 2021
Cited by 1 | Viewed by 3092
Abstract
The use of shielding gases in laser beam welding is of particular interest for materials interacting with ambient oxygen, e.g., copper, titanium or high-alloy steels. These materials are often processed by remote laser beam welding where short welds (e.g., up to 40 mm [...] Read more.
The use of shielding gases in laser beam welding is of particular interest for materials interacting with ambient oxygen, e.g., copper, titanium or high-alloy steels. These materials are often processed by remote laser beam welding where short welds (e.g., up to 40 mm seam length) are commonly used. Such setups prevent gas nozzles from being carried along on the optics due to the scanner application and a small area needs to be served locally with inert gas. The article provides systematic investigations into the interaction of laser beam processes and parameters of inert gas supply based on a modular flat jet nozzle. Based on the characterization of the developed nozzle by means of high-speed Schlieren imaging and constant temperature anemometry, investigations with heat conduction welding and deep penetration welding were performed. Bead-on-plate welds were carried out on stainless steel AISI 304 for this purpose using a disc laser and a remote welding system. Argon was used as shielding gas. The interaction between Reynolds number, geometrical parameters and welding/flow direction was considered. The findings were proved by transferring the results to a complex weld seam geometry (C-shape). Full article
(This article belongs to the Special Issue Advanced Joining Processes and Techniques)
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<p>Model concept of fluid mechanics of shielding gas supply using the example of a flat jet nozzle.</p>
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<p>Schematic cross-sectional view of shielding nozzle.</p>
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<p>(<b>a</b>) magnitude of flow velocity for the sintered material (dimensions in mm); (<b>b</b>) effect of different diffusor designs on harmonization of flow velocity.</p>
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<p>(<b>a</b>) Velocity distribution within the flat jet nozzle for different parabolic flow profiles from tophat (<span class="html-italic">PF</span> = 0%) up to completely parabolic flow (<span class="html-italic">PF</span> = 100%) (calculation according to [<a href="#B22-jmmp-05-00139" class="html-bibr">22</a>]); (<b>b</b>) achievable <span class="html-italic">Re</span> and limits of the adjustable flat jet nozzle.</p>
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<p>(<b>a</b>) Mean velocity of flow depending on distance to orifice (<span class="html-italic">x</span> = 0); (<b>b</b>) turbulence intensity depending on distance to orifice and related Schlieren images for Argon.</p>
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<p>Mean velocity of flow over nozzle width.</p>
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<p>Dependance of laminar flow length on adjustable heights <span class="html-italic">H</span> and ratio <span class="html-italic">l<sub>h</sub>/d<sub>gl</sub></span>.</p>
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<p>Length of laminar flow depending on: (<b>a</b>) <span class="html-italic">l<sub>h</sub>/d<sub>gl</sub></span>; (<b>b</b>) percentage of fully developed parabolic flow; (<b>c</b>) <span class="html-italic">Re</span>.</p>
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<p>Occurrence of annealing colors depending on distance to orifice for deep penetration welding and heat conduction welding.</p>
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<p>Schlieren images at a distance to nozzle of 20 mm for different <span class="html-italic">Re</span> to consider the effect on shielding gas coverage for: (<b>a</b>) heat conduction welding; (<b>b</b>) deep penetration welding.</p>
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<p>(<b>a</b>) Effect of gap height <span class="html-italic">H</span> on shielding gas coverage; (<b>b</b>) Schlieren images in heat conduction welding at different gap heights <span class="html-italic">H</span>.</p>
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<p>Shielding gas coverage of stitch welds perpendicular to flow direction.</p>
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<p>Effect of welding direction on shielding gas coverage and Schlieren images at weld seam center.</p>
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<p>Tarnishing on C-shaped weld seams depending on welding direction: (<b>a</b>) weld direction opposite to flow direction; (<b>b</b>) weld direction perpendicular to flow direction; (<b>c</b>) weld direction equal to flow direction.</p>
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<p>Experimental setup with laser system, Schlieren setup and flat jet nozzle.</p>
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<p>(<b>a</b>) z-type Schlieren setup used during the investigations; (<b>b</b>) schematic depiction of clamping device with flat jet nozzle and specimen.</p>
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12 pages, 3973 KiB  
Article
Residual Stresses Control in Additive Manufacturing
by Xufei Lu, Miguel Cervera, Michele Chiumenti and Xin Lin
J. Manuf. Mater. Process. 2021, 5(4), 138; https://doi.org/10.3390/jmmp5040138 - 16 Dec 2021
Cited by 33 | Viewed by 5687
Abstract
Residual stresses are one of the primary causes for the failure of parts or systems in metal additive manufacturing (AM), since they easily induce crack propagation and structural distortion. Although the formation of residual stresses has been extensively studied, the core factors steering [...] Read more.
Residual stresses are one of the primary causes for the failure of parts or systems in metal additive manufacturing (AM), since they easily induce crack propagation and structural distortion. Although the formation of residual stresses has been extensively studied, the core factors steering their development in AM have not been completely uncovered. To date, several strategies based on reducing the thermal gradients have been developed to mitigate the manifestation of residual stresses in AM; however, how to choose the optimal processing plan is still unclear for AM designers. In this regard, the concept of the yield temperature, related to the thermal deformation and the mechanical constraint, plays a crucial role for controlling the residual stresses, but it has not been duly investigated, and the corresponding approach to control stresses is also yet lacking. To undertake such study, a three-bar model is firstly used to illustrate the formation mechanism of the residual stress and its key causes. Next, an experimentally calibrated thermomechanical finite element model is used to analyze the sensitivity of the residual stresses to the scan pattern, preheating, energy density, and the part geometry and size, as well as the substrate constraints. Based on the numerical results obtained from this analysis, recommendations on how to minimize the residual stresses during the AM process are provided. Full article
(This article belongs to the Topic Additive Manufacturing)
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<p>DED process: (<b>a</b>) in situ experimental set-up; (<b>b</b>) scanning path used; (<b>c</b>) locations of two thermocouples (TC1-TC2) and one displacement sensor (DS) at the bottom surface of the substrate.</p>
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<p>FE mesh models: (<b>a</b>) 40-layer rectangular block; (<b>b</b>) 4-layer rectangular block; (<b>c</b>) 4-layer square block. The lines AB and EF at the build-substrate interface are used to analyze the residual stresses while the lines CD and GH at the deposit top are used to analyze the displacement of DED parts.</p>
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<p>Comparison between simulated and measured thermo-mechanical results of the block.</p>
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<p>The formation of residual stresses in welding and AM processes.</p>
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<p>Rectangular block: (<b>a</b>) scan patterns; (<b>b</b>) temperature and (<b>c</b>) von Mises stress during the deposition of the 2nd layer; (<b>d</b>) residual stresses; (<b>e</b>) final distortions (displacements norm); (<b>f</b>) residual von Mises stresses along the AB line at the baseplate top; (<b>g</b>) final vertical displacements along the CD line at the deposit top.</p>
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<p>Contour-fills of residual von Mises stresses and the vertical displacements for different AM processes: preheating (<b>a</b>) the whole substrate to 500 °C and (<b>b</b>) the deposit region on the substrate surface by laser (transverse scan); increasing the deposit height to (<b>c</b>) 4 mm and (<b>d</b>) 6 mm, respectively; using the (<b>e</b>) lower and (<b>f</b>) higher energy to fabricate AM block, respectively; (<b>g</b>) residual von Mises stresses along the AB line at the substrate top; (<b>h</b>) vertical displacements along the CD line at the deposit top.</p>
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<p>Square block: (<b>a</b>) different substrate designs; (<b>b</b>) von Mises stress field; (<b>c</b>) final distortions (displacements norm); (<b>d</b>) residual von Mises stresses along the EF line at the baseplate top; (<b>e</b>) vertical displacements along the GH line at the deposit top.</p>
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15 pages, 2694 KiB  
Article
A Study of the Convective Cooling of Large Industrial Billets
by Richard Turner
J. Manuf. Mater. Process. 2021, 5(4), 137; https://doi.org/10.3390/jmmp5040137 - 16 Dec 2021
Viewed by 2947
Abstract
The thermodynamic heat-transfer mechanisms, which occur as a heated billet cools in an air environment, are of clear importance in determining the rate at which a heated billet cools. However, in finite element modelling simulations, the convective heat transfer term of the heat [...] Read more.
The thermodynamic heat-transfer mechanisms, which occur as a heated billet cools in an air environment, are of clear importance in determining the rate at which a heated billet cools. However, in finite element modelling simulations, the convective heat transfer term of the heat transfer mechanisms is often reduced to simplified or guessed constants, whereas thermal conductivity and radiative emissivity are entered as detailed temperature dependent functions. As such, in both natural and forced convection environments, the fundamental physical relationships for the Nusselt number, Reynolds number, Raleigh parameter, and Grashof parameter were consulted and combined to form a fundamental relationship for the natural convective heat transfer as a temperature-dependent function. This function was calculated using values for air as found in the literature. These functions were then applied within an FE framework for a simple billet cooling model, compared against FE predictions with constant convective coefficient, and further compared with experimental data for a real steel billet cooling. The modified, temperature-dependent convective transfer coefficient displayed an improved prediction of the cooling curves in the majority of experiments, although on occasion a constant value model also produced very similar predicted cooling curves. Finally, a grain growth kinetics numerical model was implemented in order to predict how different convective models influence grain size and, as such, mechanical properties. The resulting findings could offer improved cooling rate predictions for all types of FE models for metal forming and heat treatment operations. Full article
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<p>Calculated forced convective heat transfer coefficient at range of temperatures.</p>
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<p>Finite element modelling setup.</p>
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<p>Thermo-physical properties for the 35KhN3MFA steel used.</p>
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<p>FE predictions of billet natural cooling after (<b>a</b>) ½ h, (<b>b</b>) 1 h, (<b>c</b>) 2 h, (<b>d</b>) 5 h, and (<b>e</b>) 10 h for (<b>top</b>) constant convection coefficient and (<b>bottom</b>) temperature-dependent convective term.</p>
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<p>Cooling curves for (<b>a</b>) naturally cooled billet and (<b>b</b>) forced cooled billet; and for experiment and FE models with constant and a temperature dependent convective heat transfer term.</p>
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<p>FE prediction of average grain size in natural and forced convective cooled billets.</p>
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14 pages, 3502 KiB  
Article
Laser Welding of AISI 316L Stainless Steel Produced by Additive Manufacturing or by Conventional Processes
by Morgane Mokhtari, Pierrick Pommier, Yannick Balcaen and Joel Alexis
J. Manuf. Mater. Process. 2021, 5(4), 136; https://doi.org/10.3390/jmmp5040136 - 14 Dec 2021
Cited by 21 | Viewed by 5118
Abstract
Among all the additive manufacturing techniques, Laser Powder Bed Fusion (LBPF), also called Selective Laser Melting (SLM), is the most common technique due to its high capability of building complex parts with generally improved mechanical properties. One of the main drawbacks of this [...] Read more.
Among all the additive manufacturing techniques, Laser Powder Bed Fusion (LBPF), also called Selective Laser Melting (SLM), is the most common technique due to its high capability of building complex parts with generally improved mechanical properties. One of the main drawbacks of this technique is the sample size limitation, which depends on elaborating chamber dimensions. In this study, we investigate the viability of obtaining large parts with the laser welding of additive manufactured plates. A comparison of the microstructure and the tensile mechanical properties of SLM-welded plates and cold-rolled welded plates was performed. This paper shows the possibility of obtaining defect-free parts. Even if welding has a low impact on the microstructure of the SLM samples, fractures are located on the fusion zone, and a decrease in ductility of around 30% compared to the base metal is observed. Full article
(This article belongs to the Special Issue Advanced Joining Processes and Techniques)
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<p>(<b>a</b>) Experimental welding setup. (<b>b</b>) Standard geometrical specifications described in EN ISO 6947.</p>
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<p>Radiography of the worst seam parts for the CR sample and SLM samples, respectively.</p>
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<p>Welded cold-rolled sheets: macrography of the weld seam (<b>a</b>); higher magnification of base metal (BM) (<b>b</b>); fusion zone—heat-affected zone (HAZ) boundary (<b>d</b>,<b>e</b>) and fusion zone (FZ) (<b>c</b>); welded SLM sheets: macrography of the weld seam (<b>f</b>); higher magnification of base metal (BM) (<b>g</b>); fusion zone—heat-affected zone (HAZ) boundary (<b>i</b>–<b>k</b>) and fusion zone (FZ) (<b>h</b>). Dashed lines correspond to fusion zone boundaries. Dotted lines correspond to melt pool boundaries. Red dots correspond to SEM-EDX point analysis positions.</p>
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<p>(<b>a</b>) (Left) SEM-EBSD inverse pole figure (IPF) X cross-section map of welded CR; (middle) phase map of the heat-affect area (HAZ) and SEM-EBSD inverse pole figure (IPF) X top map of welded CR (right). (<b>b</b>) SEM-EBSD inverse pole figure (IPF) X maps of cross-section welded SLM (left), base metal SLM (middle), and top welded SLM (right), respectively. Black lines correspond to random grain boundaries and red lines to Σ3 twin grain boundaries (GB).</p>
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<p>Pole figures of the crystallographic planes (001), (011), and (111) for the fusion zone and base metal of a welded cold-rolled sheet (<b>a</b>) and a welded SLM sheet (<b>b</b>), respectively.</p>
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<p>Cross-section hardness evolution of welded samples. Dashed lines correspond to the limit of the fusion zone.</p>
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<p>Stress–strain tensile curves of reference and welded samples. Reference samples corresponds to non-welded samples. (Right) Evolution of axial strain difference between Fusion Zone (FZ) and Base Metal (BM) with the global strain.</p>
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14 pages, 4816 KiB  
Article
Detecting Process Anomalies in the GMAW Process by Acoustic Sensing with a Convolutional Neural Network (CNN) for Classification
by Maximilian Rohe, Benedict Niklas Stoll, Jörg Hildebrand, Jan Reimann and Jean Pierre Bergmann
J. Manuf. Mater. Process. 2021, 5(4), 135; https://doi.org/10.3390/jmmp5040135 - 11 Dec 2021
Cited by 18 | Viewed by 3719
Abstract
Today, the quality of welded seams is often examined off-line with either destructive or non-destructive testing. These test procedures are time-consuming and therefore costly. This is especially true if the welds are not welded accurately due to process anomalies. In manual welding, experienced [...] Read more.
Today, the quality of welded seams is often examined off-line with either destructive or non-destructive testing. These test procedures are time-consuming and therefore costly. This is especially true if the welds are not welded accurately due to process anomalies. In manual welding, experienced welders are able to detect process anomalies by listening to the sound of the welding process. In this paper, an approach to transfer the “hearing” of an experienced welder into an automated testing process is presented. An acoustic measuring device for recording audible sound is installed for this purpose on a fully automated welding fixture. The processing of the sound information by means of machine learning methods enables in-line process control. Existing research results until now show that the arc is the main sound source. However, both the outflow of the shielding gas and the wire feed emit sound information. Other investigations describe welding irregularities by evaluating and assessing existing sound recordings. Descriptive analysis was performed to find a connection between certain sound patterns and welding irregularities. Recent contributions have used machine learning to identify the degree of welding penetration. The basic assumption of the presented investigations is that process anomalies are the cause of welding irregularities. The focus was on detecting deviating shielding gas flow rates based on audio recordings, processed by a convolutional neural network (CNN). After adjusting the hyperparameters of the CNN it was capable of distinguishing between different flow rates of shielding gas. Full article
(This article belongs to the Special Issue Advanced Joining Processes and Techniques)
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<p>Experimental setup for welding experiments.</p>
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<p>Positions of the beads and the microphone: (<b>a</b>) bead positions on the base plate and naming conventions; (<b>b</b>) microphone position relative to the arc with scheme of the GMAW welding torch.</p>
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<p>Comparison between the acquired welding sound, voltage and current in the middle of the weld.</p>
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<p>Ontological model for the acquired data samples.</p>
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<p>Frequencies of the welding fume extraction without welding. The grey marked area represents the lower cut-off frequencies of the first filter stage.</p>
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<p>Spectrograms of the emitted audible sound with different shielding gas flow rates: (<b>a</b>) bead with no shielding gas coverage; (<b>b</b>) bead welded with a shielding gas flow rate of 15 L/min (100%).</p>
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<p>Data pipeline.</p>
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<p>Structure of the chosen CNN with three convolutional layers in line with max-pooling layers and at least a dense neural network for classification.</p>
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<p>Scheme of 10-fold cross-validation used in this research.</p>
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<p>Top view of the welded beads with different shielding gas flow rates: (<b>a</b>) photo taken right after welding the bead; (<b>b</b>) radiographs of the welded beads with weld irregularities (marked in red) and their dimensions.</p>
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<p>Confusion matrix for the prediction of shielding gas flow rates with the mean accuracy after 10-fold cross-validation. Type I errors are shown in the red rectangle.</p>
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<p>Prediction accuracies over Leave-Out frequency bands with a bandwidth of 750 Hz.</p>
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14 pages, 8848 KiB  
Article
Development of a Multidirectional Wire Arc Additive Manufacturing (WAAM) Process with Pure Object Manipulation: Process Introduction and First Prototypes
by Khushal Parmar, Lukas Oster, Samuel Mann, Rahul Sharma, Uwe Reisgen, Markus Schmitz, Thomas Nowicki, Jan Wiartalla, Mathias Hüsing and Burkhard Corves
J. Manuf. Mater. Process. 2021, 5(4), 134; https://doi.org/10.3390/jmmp5040134 - 10 Dec 2021
Cited by 9 | Viewed by 4482
Abstract
Wire Arc Additive Manufacturing (WAAM) with eccentric wire feed requires defined operating conditions due to the possibility of varying shapes of the deposited and solidified material depending on the welding torch orientation. In consequence, the produced component can contain significant errors because single [...] Read more.
Wire Arc Additive Manufacturing (WAAM) with eccentric wire feed requires defined operating conditions due to the possibility of varying shapes of the deposited and solidified material depending on the welding torch orientation. In consequence, the produced component can contain significant errors because single bead geometrical errors are cumulatively added to the next layer during a building process. In order to minimise such inaccuracies caused by torch manipulation, this article illustrates the concept and testing of object-manipulated WAAM by incorporating robotic and welding technologies. As the first step towards this target, robotic hardware and software interfaces were developed to control the robot. Alongside, a fixture for holding the substrate plate was designed and fabricated. After establishing the robotic setup, in order to complete the whole WAAM process setup, a Gas Metal Arc Welding (GMAW) process was built and integrated into the system. Later, an experimental plan was prepared to perform single and multilayer welding experiments as well as for different trajectories. According to this plan, several welding experiments were performed to decide the parametric working range for the further WAAM experiments. In the end, the results of the first multilayer depositions over intricate trajectories are shown. Further performance and quality optimization strategies are also discussed at the end of this article. Full article
(This article belongs to the Special Issue Advanced Joining Processes and Techniques)
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<p>Preliminary tests carried out at the Welding and Joining Institute of RWTH Aachen University to demonstrate direction-dependent weld bead formation with a moving welding torch with eccentric filler wire feeding. Figure (<b>a</b>,<b>c</b>) show asymmetric weld seam cross sectional geometry. Figure (<b>b</b>) shows an optimal desired geometry using forward feed of the filler wire, whereas figure (<b>d</b>) indicates again a geometrical error caused by the backward feed of the filler wire. The red-coloured vector has two point: (P1) is the arc root and (P2) indicates the the filler wire point from where it is supplied into the arc.</p>
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<p>Concept of smoothing and stretching of welding path presented by [<a href="#B10-jmmp-05-00134" class="html-bibr">10</a>].</p>
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<p>Influence of different smoothing and stretching parameters on the robot joint values along the execution (here, the 6th joint of Kuka KR6).</p>
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<p>Design of Experiment results of different smoothing parameters.</p>
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<p>Hardware Interface of the Multidirectional Additive Manufacturing.</p>
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<p>Robotic setup constructed at the IGMR Institute.</p>
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<p>End effector used in the context of this work.</p>
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<p>GMAW based WAAM process with pure object manipulation.</p>
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<p>GMA-Welding Parameter Range and Experimental plan.</p>
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<p>Experimental cases (paths) for OM-MDAM.</p>
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<p>Single- and Multiilayer trajectories built using WAAM With Pure Object Manipulation.</p>
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<p>Macrographic images to assess consistency of multilayer deposition.</p>
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<p>Resulting Cartesian Path Speed after trajectory optimization.</p>
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<p>Change in joint velocity of 6th axis before (<b>top</b>) and after (<b>bottom</b>) trajectory optimization.</p>
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3 pages, 176 KiB  
Editorial
Impulse-Based Manufacturing Technologies
by Verena Psyk
J. Manuf. Mater. Process. 2021, 5(4), 133; https://doi.org/10.3390/jmmp5040133 - 9 Dec 2021
Viewed by 2082
Abstract
Modern manufacturing faces extensive technological and economic challenges to remain competitive under the current political and social conditions [...] Full article
(This article belongs to the Special Issue Impulse-Based Manufacturing Technologies)
23 pages, 5299 KiB  
Article
Overmolding of Hybrid Long and Short Carbon Fiber Polypropylene Composite: Optimizing Processing Parameters
by Cahyo Budiyantoro, Heru S. B. Rochardjo and Gesang Nugroho
J. Manuf. Mater. Process. 2021, 5(4), 132; https://doi.org/10.3390/jmmp5040132 - 8 Dec 2021
Cited by 4 | Viewed by 3662
Abstract
Injection overmolding was used to produce hybrid unidirectional continuous-short carbon fiber reinforced polypropylene. Polypropylene pellets containing short carbon fibers were melted and overmolded on unidirectional carbon fibers, which act as the core of the composite structure. Four factors were varied in this study: [...] Read more.
Injection overmolding was used to produce hybrid unidirectional continuous-short carbon fiber reinforced polypropylene. Polypropylene pellets containing short carbon fibers were melted and overmolded on unidirectional carbon fibers, which act as the core of the composite structure. Four factors were varied in this study: fiber pretension applied to unidirectional fibers, injection pressure, melting temperature, and backpressure used for melting and injecting the composite pellet. This study aimed to evaluate the effect of these factors on fiber volume fraction, flexural strength, and impact strength of the hybrid composite. The relationship between factors and responses was analyzed using Box–Behnken Response Surface Methodology (RSM) and analysis of variance (ANOVA). Each aspect was divided into three levels. There were 27 experimental runs carried out, with three replicated center points. The results showed that the injection molding process parameters had no significant effect on the fiber’s volume fraction. On the other hand, melting temperature and fiber pretension significantly affected impact strength and flexural strength. Full article
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<p>Schematic illustration of the fiber pretension condition.</p>
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<p>Production steps of hybrid fiber overmolded composite.</p>
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<p>Overmolding device.</p>
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<p>The four bending test setups with an asymmetric UD fiber position.</p>
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<p>Impact test configuration.</p>
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<p>Overmolding product.</p>
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<p>Fiber orientation tensor.</p>
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<p>Experimental results: (<b>a</b>) fiber volume fraction; (<b>b</b>) impact strenght; and (<b>c</b>) flexural strength.</p>
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<p>Experimental results: (<b>a</b>) fiber volume fraction; (<b>b</b>) impact strenght; and (<b>c</b>) flexural strength.</p>
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<p>Effect of all factors on fiber volume fraction: (<b>A</b>) melt temperature; (<b>B</b>) injection pressure; (<b>C</b>) backpressure; and (<b>D</b>) fiber pretension.</p>
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<p>Diagnostic plots for impact strength response: (<b>a</b>) normal probability; (<b>b</b>) residuals vs run.</p>
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<p>Influence of individual factor on the impact strength: (<b>A</b>) melt temperature; (<b>B</b>) injection pressure; (<b>C</b>) backpressure; and (<b>D</b>) fiber pretension.</p>
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<p>Diagnostic plots for flexural strength response: (<b>a</b>) normal probability; (<b>b</b>) residuals vs. run.</p>
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<p>Influence of individual factor on the flexural strength: (<b>A</b>) melt temperature; (<b>B</b>) injection pressure; (<b>C</b>) backpressure; and (<b>D</b>) fiber pretension.</p>
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<p>Influence of individual factor on the flexural strength: (<b>A</b>) melt temperature; (<b>B</b>) injection pressure; (<b>C</b>) backpressure; and (<b>D</b>) fiber pretension.</p>
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<p>Desirability function.</p>
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<p>Optimized responses prediction: (<b>a</b>) desirability; (<b>b</b>) fiber volume fraction; (<b>c</b>) impact strength; and (<b>d</b>) flexural strength.</p>
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<p>Longitudinal cross section of (<b>a</b>) non-pre tensioned fiber at skin layer; (<b>b</b>) non-pre tensioned fiber at the core; (<b>c</b>) pre-tensioned fiber at skin layer; and (<b>d</b>) pre-tensioned fiber at the core.</p>
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<p>Micrograph of pretensioned fiber composite.</p>
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<p>Micrograph of the longitudinal cross-section after bending: (<b>a</b>) low flexural strength; (<b>b</b>) high flexural strength.</p>
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13 pages, 3501 KiB  
Communication
Prediction and Compensation of Color Deviation by Response Surface Methodology for PolyJet 3D Printing
by Xingjian Wei, Abhinav Bhardwaj, Li Zeng and Zhijian Pei
J. Manuf. Mater. Process. 2021, 5(4), 131; https://doi.org/10.3390/jmmp5040131 - 4 Dec 2021
Cited by 8 | Viewed by 3762
Abstract
PolyJet 3D printing can produce any color by mixing multiple materials. However, there are often large deviations between the measured color of printed samples and the target color (when the target color is used as the specified color in the printer software). Therefore, [...] Read more.
PolyJet 3D printing can produce any color by mixing multiple materials. However, there are often large deviations between the measured color of printed samples and the target color (when the target color is used as the specified color in the printer software). Therefore, to achieve a target color on a printed sample, the specified color in the printer software should not be the same as the target color. This study applies response surface methodology (RSM) to determine the optimal color specification to compensate for color deviations of the measured color of printed samples from the target color in PolyJet 3D printing. The RSM has three steps. First, a set of experiments are designed for a target color according to central composite design. Second, the experimental data are used to develop a second-order multivariate multiple regression model to predict the deviation between the measured color and the target color. Third, the optimal color specification (often different from the target color) is determined by using the developed predictive model and the desirability function. When the optimal color specification is used as the specified color in the printer software, the deviation between the predicted color of the printed sample and the target color is minimized. The proposed method is applied to four target colors to demonstrate its effectiveness. The results show that the proposed method performs better than the conventional color specification method without compensation in achieving the four target colors by 33% on average. Full article
(This article belongs to the Topic Additive Manufacturing)
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<p>PolyJet 3D printing. (<b>a</b>) Illustration of the PolyJet printing process, and (<b>b</b>) picture of the Stratasys J750 PolyJet printer.</p>
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<p>Illustration of a central composite design for coded RGB values.</p>
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<p>The Nix Pro colorimeter and printed samples for four cases.</p>
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<p>Plots of response surfaces for Case 3 based on the coefficient estimates (raw data are provided in <a href="#jmmp-05-00131-t0A5" class="html-table">Table A5</a>).</p>
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<p>Deviations of measured RGB values from target RGB values when using the proposed method versus the conventional specification method without compensation.</p>
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16 pages, 6074 KiB  
Article
Investigation of Gyroscopic Effect on the Stability of High Speed Micromilling via Bifurcation Analysis
by Rinku K. Mittal and Ramesh K. Singh
J. Manuf. Mater. Process. 2021, 5(4), 130; https://doi.org/10.3390/jmmp5040130 - 2 Dec 2021
Cited by 3 | Viewed by 2638
Abstract
Catastrophic tool failure due to the low flexural stiffness of the micro-tool is a major concern for micromanufacturing industries. This issue can be addressed using high rotational speed, but the gyroscopic couple becomes prominent at high rotational speeds for micro-tools affecting the dynamic [...] Read more.
Catastrophic tool failure due to the low flexural stiffness of the micro-tool is a major concern for micromanufacturing industries. This issue can be addressed using high rotational speed, but the gyroscopic couple becomes prominent at high rotational speeds for micro-tools affecting the dynamic stability of the process. This study uses the multiple degrees of freedom (MDOF) model of the cutting tool to investigate the gyroscopic effect in machining. Hopf bifurcation theory is used to understand the long-term dynamic behavior of the system. A numerical scheme based on the linear multistep method is used to solve the time-periodic delay differential equations. The stability limits have been predicted as a function of the spindle speed. Higher tool deflections occur at higher spindle speeds. Stability lobe diagram shows the conservative limits at high rotational speeds for the MDOF model. The predicted stability limits show good agreement with the experimental limits, especially at high rotational speeds. Full article
(This article belongs to the Special Issue Advances in Modelling of Machining Operations)
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<p>Micro end mill as a rotor with flexible bearing supports.</p>
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<p>Schematic of milling process.</p>
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<p>Schematic diagram to generate stability plots.</p>
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<p>High-speed micromachining center.</p>
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<p>Bifurcation diagram for a spindle speed of 120,000 rpm.</p>
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<p>Waveform plots: (<b>a</b>) XG vs. time; (<b>b</b>) YG vs. time; (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mi>θ</mi> <mi>x</mi> </msub> </mrow> </semantics></math> vs. time; (<b>d</b>) <math display="inline"><semantics> <mrow> <msub> <mi>θ</mi> <mi>y</mi> </msub> </mrow> </semantics></math> vs. time, orbital map: (<b>e</b>) YG vs. XG and Poincare map: (<b>f</b>) <math display="inline"><semantics> <mrow> <mover> <mrow> <msub> <mi>X</mi> <mrow> <mi>G</mi> <mn>1</mn> </mrow> </msub> </mrow> <mo>˙</mo> </mover> </mrow> </semantics></math> vs. XG for pre bifurcation motion (depth of cut ap = 4.1 µm and spindle speed of 120,000 rpm).</p>
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<p>Waveform plots: (<b>a</b>) XG vs. time; (<b>b</b>) YG vs. time; (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mi>θ</mi> <mi>x</mi> </msub> </mrow> </semantics></math> vs. time; (<b>d</b>) <math display="inline"><semantics> <mrow> <msub> <mi>θ</mi> <mi>y</mi> </msub> </mrow> </semantics></math> vs. time, orbital map: (<b>e</b>) YG vs. XG and Poincare map: (<b>f</b>) <math display="inline"><semantics> <mrow> <mover> <mrow> <msub> <mi>X</mi> <mi>G</mi> </msub> </mrow> <mo>˙</mo> </mover> </mrow> </semantics></math> vs. XG for post bifurcation motion (depth of cut ap = 4.6 µm and spindle speed of 120,000 rpm).</p>
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<p>Poincare maps for pre-bifurcation (depth of cut <span class="html-italic">a<sub>p</sub></span> = 4.1 µm), bifurcation point (depth of cut <span class="html-italic">a<sub>p</sub></span> = 4.4 µm), and post-bifurcation motion (depth of cut <span class="html-italic">a<sub>p</sub></span> = 4.6 µm) (<b>a</b>) <math display="inline"><semantics> <mrow> <mover> <mrow> <msub> <mi>X</mi> <mi>G</mi> </msub> </mrow> <mo>˙</mo> </mover> </mrow> </semantics></math> vs. X<sub>G</sub> and (<b>b</b>) <math display="inline"><semantics> <mrow> <mover> <mrow> <msub> <mi>Y</mi> <mi>G</mi> </msub> </mrow> <mo>˙</mo> </mover> </mrow> </semantics></math> vs. Y<sub>G</sub>.</p>
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<p>Orbital maps at a depth of cut <span class="html-italic">a<sub>p</sub></span> = 4.1 µm for spindle speeds of 60,000 and 120,000 rpm.</p>
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<p>Comparison of waveform plots (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mi>θ</mi> <mi>x</mi> </msub> </mrow> </semantics></math> vs. time; (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mi>θ</mi> <mi>y</mi> </msub> </mrow> </semantics></math> vs. time at a depth of cut <span class="html-italic">a<sub>p</sub></span> = 4.1 µm for spindle speeds of 60,000 and 120,000 rpm.</p>
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<p>Comparison of waveform plots (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mi>θ</mi> <mi>x</mi> </msub> </mrow> </semantics></math> vs. time; (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mi>θ</mi> <mi>y</mi> </msub> </mrow> </semantics></math> vs. time at a depth of cut <span class="html-italic">a<sub>p</sub></span> = 4.1 µm for spindle speeds of 60,000 and 120,000 rpm.</p>
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<p>Stability lobe diagram for 2DOF and MDOF stability models.</p>
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<p>FFT spectrum of the velocity data.</p>
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<p>Validation of stability lobe diagram.</p>
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22 pages, 1252 KiB  
Article
Development of a Cost Model for Vertical Milling Machines to Assess Impact of Lightweighting
by Matthew J. Triebe, Fu Zhao and John W. Sutherland
J. Manuf. Mater. Process. 2021, 5(4), 129; https://doi.org/10.3390/jmmp5040129 - 1 Dec 2021
Viewed by 3760
Abstract
Lightweighting is a design strategy to reduce energy consumption through the reduction of mass of a product. Lightweighting can be applied to machine tools to reduce the amount of energy consumed during the use phase. Thus, the energy cost of machine operation will [...] Read more.
Lightweighting is a design strategy to reduce energy consumption through the reduction of mass of a product. Lightweighting can be applied to machine tools to reduce the amount of energy consumed during the use phase. Thus, the energy cost of machine operation will be reduced. One might also hypothesize that since a lighter-weight machine tool requires less material to build, the cost to produce such a machine will be less. However, it may also be the case that lightweighting a machine tool increases its complexity, which will likely drive up the cost to manufacture the machine. To explore the cost drivers associated with building a machine tool, data on the features associated with a wide variety of vertical milling machine tools are collected. Then, empirical cost models are fit to this data. The results from the cost models show that the machine tool mass is a significant cost driver; other key drivers are the number of axes and spindle power. The models are used to predict the cost benefits of lightweighting in terms of mass, which are compared to potential increased manufacturing costs associated with complexities introduced due to lightweighting. Full article
(This article belongs to the Special Issue Advances in Multi-Axis Machining)
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<p>(<b>a</b>) Cost of materials based on mass (data taken from Ashby [<a href="#B35-jmmp-05-00129" class="html-bibr">35</a>]). (<b>b</b>) Embodied energy and carbon footprint of various metals (data taken from Ashby [<a href="#B35-jmmp-05-00129" class="html-bibr">35</a>]).</p>
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<p>Flow chart of the procedure for stepwise regression.</p>
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<p>Sandwich panel table with a core of square cells, adapted from Triebe et al. [<a href="#B33-jmmp-05-00129" class="html-bibr">33</a>].</p>
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<p>(<b>a</b>) Standard solid table design having a mass of 1370 kg. (<b>b</b>) Lightweight table design having a mass of 687 kg.</p>
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14 pages, 4776 KiB  
Article
A Multiaxis Tool Path Generation Approach for Thin Wall Structures Made with WAAM
by Matthieu Rauch, Jean-Yves Hascoet and Vincent Querard
J. Manuf. Mater. Process. 2021, 5(4), 128; https://doi.org/10.3390/jmmp5040128 - 30 Nov 2021
Cited by 17 | Viewed by 5040
Abstract
Wire Arc Additive Manufacturing (WAAM) has emerged over the last decade and is dedicated to the realization of high-dimensional parts in various metallic materials. The usual process implementation consists in associating a high-performance welding generator as heat source, a NC controlled 6 or [...] Read more.
Wire Arc Additive Manufacturing (WAAM) has emerged over the last decade and is dedicated to the realization of high-dimensional parts in various metallic materials. The usual process implementation consists in associating a high-performance welding generator as heat source, a NC controlled 6 or 8 degrees (for example) of freedom robotic arm as motion system and welding wire as feedstock. WAAM toolpath generation methods, although process specific, can be based on similar approaches developed for other processes, such as machining, to integrate the process data into a consistent technical data environment. This paper proposes a generic multiaxis tool path generation approach for thin wall structures made with WAAM. At first, the current technological and scientific challenges associated to CAD/CAM/CNC data chains for WAAM applications are introduced. The focus is on process planning aspects such as non-planar non-parallel slicing approaches and part orientation into the working space, and these are integrated in the proposed method. The interest of variable torch orientation control for complex shapes is proposed, and then, a new intersection crossing tool path method based on Design For Additive Manufacturing considerations is detailed. Eventually, two industrial use cases are introduced to highlight the interest of this approach for realizing large components. Full article
(This article belongs to the Special Issue Advances in Multi-Axis Machining)
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<p>WAAM robotic cell of the laboratory.</p>
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<p>From CAD model to manufactured part with AM.</p>
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<p>Example of manufacturing direction selection.</p>
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<p>Several slicing strategies for a single geometry.</p>
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<p>Manufacturing of an inclined thin wall by using torch axis orientation.</p>
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<p>Tool path generation with guide curves to orient two axes: (<b>a</b>) 15° cone and (<b>b</b>) variable inclination wall.</p>
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<p>WAAM torch position to manufacture horizontal walls.</p>
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<p>Examples of intersection crossing (adapted from [<a href="#B23-jmmp-05-00128" class="html-bibr">23</a>]).</p>
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<p>Roundabout-type intersection for two walls crossing: (<b>a</b>) manufacturing paths and (<b>b</b>) manufactured intersection.</p>
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<p>Multiple track intersection crossing with the proposed method.</p>
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<p>Numerical data chain for the propeller use case.</p>
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<p>One-meter diameter cruise ship propeller made with WAAM in the laboratory.</p>
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<p>Structural panel demonstrator after DFAM.</p>
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<p>Structural panel: (<b>a</b>) during the manufacturing process and (<b>b</b>) finished.</p>
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13 pages, 4513 KiB  
Article
High-Precision Adjustment of Welding Depth during Laser Micro Welding of Copper Using Superpositioned Spatial and Temporal Power Modulation
by Marc Hummel, André Häusler and Arnold Gillner
J. Manuf. Mater. Process. 2021, 5(4), 127; https://doi.org/10.3390/jmmp5040127 - 25 Nov 2021
Cited by 8 | Viewed by 3728
Abstract
For joining metallic materials for battery applications such as copper and stainless steel, laser beam micro welding with beam sources in the near-infrared range has become established in recent years. In laser beam micro welding, spatial power modulation describes the superposition of the [...] Read more.
For joining metallic materials for battery applications such as copper and stainless steel, laser beam micro welding with beam sources in the near-infrared range has become established in recent years. In laser beam micro welding, spatial power modulation describes the superposition of the linear feed motion with an oscillating motion. This modulation method serves to widen the cross-section of the weld seam as well as to increase the process stability. Temporal power modulation refers to the controlled modulation of the laser power over time during the welding process. In this paper, the superposition of both temporal and spatial power modulation methods is presented, which enables a variable control of the weld penetration depth. Three weld geometries transverse to the feed direction are part of this investigation: the compensation of the weld penetration depth due to the asymmetric path movement during spatial power modulation only, a W-shaped weld profile, and a V-shaped. The weld geometries are investigated by the bed on plate weld tests with CuSn6. Furthermore, the use of combined power modulation for welding tests in butt joint configuration between CuSn6 and stainless steel 1.4301 with different material properties is investigated. The study shows the possibility of precise control of the welding depth by this methodology. Depending on the material combination, the desired regions with maximum and minimum welding depth can be achieved by the control of local and temporal power modulation on the material surface. Full article
(This article belongs to the Special Issue Advanced Joining Processes and Techniques)
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<p>Illustration of process regimes (heat conduction and deep penetration welding) after [<a href="#B20-jmmp-05-00127" class="html-bibr">20</a>].</p>
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<p>Illustration of spatial power modulation for laser beam micro welding.</p>
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<p>Schematic representation of the weld-in profiles to be investigated in transverse section. Initial situation (<b>left</b>); compensation and targeted profiles with combined power modulation (<b>right</b>).</p>
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<p>Schematic representation of the weld penetration profile of a weld in the butt joint of dissimilar joining partners and the compensated target situation using combined power modulation.</p>
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<p>Qualitative representation of the position of the maximum and minimum laser power; red—maximum power; blue—minimum power.</p>
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<p>Schematic experimental setup for synchronizing temporal and spatial power modulation (<b>left</b>); measured signals to determine the phase shift tz (<b>right</b>).</p>
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<p><b>Left</b>: Laser weld with only spatial power modulation. <b>Right</b>: Laser weld with combined spatial and temporal power modulation (compensation).</p>
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<p>Laser weld with combined spatial and temporal power modulation <b>Left</b>: W-shape; <b>Right</b>: V-shape.</p>
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<p>Comparison of two welds in butt joint. <b>Left</b>: with local PM; <b>right</b>: with combined PM with local amplitude A<sub>s</sub> = 0.2 mm.</p>
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<p>Comparison of two weld seams in the butt joint. <b>Left</b>: with local PM; <b>right</b>: with combined PM with an amplitude of A<sub>s</sub> = 0.3 mm.</p>
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<p>Temporal course of the coupling degrees for bed on plate welds on CuSn6. <b>Left</b>: spatial PM only and combined PM (compensation); <b>Right</b>: W- and V- profile.</p>
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18 pages, 6913 KiB  
Article
FE-Simulation Based Design of Wear-Optimized Cutting Edge Roundings
by Benjamin Bergmann, Berend Denkena, Sascha Beblein and Tobias Picker
J. Manuf. Mater. Process. 2021, 5(4), 126; https://doi.org/10.3390/jmmp5040126 - 25 Nov 2021
Cited by 6 | Viewed by 3277
Abstract
The performance of cutting tools can be significantly enhanced by matching the cutting edge rounding to the process and material properties. However, the conventional cutting edge rounding design is characterized by a significant number of experimental machining studies, which involve considerable cost, time, [...] Read more.
The performance of cutting tools can be significantly enhanced by matching the cutting edge rounding to the process and material properties. However, the conventional cutting edge rounding design is characterized by a significant number of experimental machining studies, which involve considerable cost, time, and resources. In this study, a novel approach to cutting edge rounding design using FEM-based chip formation simulations is presented. Based on a parameterized simulation model, tool temperatures, stresses and relative velocities can be calculated as a function of tool microgeometry. It can be shown that the external tool loads can be simulated with high agreement. With the help of these loads and the use of wear models, the resulting tool wear and the optimum cutting edge rounding can be determined. The final experimental investigations show a qualitatively high agreement to the simulation, which will enable a reduced effort design of the cutting edge in the future. Full article
(This article belongs to the Topic Modern Technologies and Manufacturing Systems)
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<p>Characterization of the cutting edge microgeometry [<a href="#B2-jmmp-05-00126" class="html-bibr">2</a>].</p>
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<p>Experimental setup for planing investigations.</p>
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<p>Experimental setup for turning investigations.</p>
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<p>Material-based modelling of the load stresses on the rake face.</p>
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<p>Parameterization of the wear rate model.</p>
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<p>Simulated tool load during machining of AISI4140.</p>
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<p>Validation of the simulated maximum normal stresses as a function of the workpiece properties.</p>
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<p>Simulated material specific normal stress distribution.</p>
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<p>Phases of segmented chip formation and corresponding normal stress distribution during machining of TiAl6V4.</p>
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<p>Simulated normal stress distribution depending on the cutting edge rounding during machining of AISI4140.</p>
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<p>Effect of asymmetric rounded cutting edges on the thermomechanical and kinematic load during machining of AISI4140.</p>
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<p>Thermal and kinematic load maps as a function of cutting edge segments S<sub>α</sub> and S<sub>γ</sub> during machining of AISI4140.</p>
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<p>Procedure for simulating the tool life time.</p>
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<p>Comparison between simulated and experimental tool life time.</p>
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18 pages, 8276 KiB  
Article
Micro-Milling Process of Metals: A Comparison between Femtosecond Laser and EDM Techniques
by Luigi Calabrese, Martina Azzolini, Federico Bassi, Enrico Gallus, Sara Bocchi, Giancarlo Maccarini, Giuseppe Pellegrini and Chiara Ravasio
J. Manuf. Mater. Process. 2021, 5(4), 125; https://doi.org/10.3390/jmmp5040125 - 22 Nov 2021
Cited by 9 | Viewed by 3624
Abstract
Nowadays, micro-machining techniques are commonly used in several industrial fields, such as automotive, aerospace and medical. Different technologies are available, and the choice must be made considering many factors, such as the type of machining, the number of lots and the required accuracy [...] Read more.
Nowadays, micro-machining techniques are commonly used in several industrial fields, such as automotive, aerospace and medical. Different technologies are available, and the choice must be made considering many factors, such as the type of machining, the number of lots and the required accuracy specifications in terms of geometrical tolerances and surface finish. Lasers and electric discharge machining (EDM) are widely used to produce micro-components and are similarly unconventional thermal technologies. In general, a laser is particularly appreciated by the industry for the excellent machining speeds and for the possibility to machine essentially any type of materials. EDM, on the other hand, has a poor material removal rate (MRR) but can produce microparts on only electrically conductive workpieces, reaching high geometrical accuracy and realizing steep walls. The most common micro-application for both the technologies is drilling but they can make also milling operations. In this work, a comparison of femto-laser and EDM technologies was made focusing on micro-milling. Two features were selected to make the comparison: micro-channels and micro-pillars. The depth was varied on two levels for both features. As workpiece material, aluminum, stainless steel and titanium alloy were tested. Data regarding the process performance and the geometrical characteristics of the features were analyzed. The results obtained with the two technologies were compared. This work improves the knowledge of the micro-manufacturing processes and can help in the characterization of their capabilities. Full article
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<p>Schematic representation of the femtosecond laser micro-machining setup: the laser beam is directed with a mirror (M) on a polarizer waveplate (λ/4) and expanded with a beam expander (BE). A galvanometric scanner (G) and a F-Theta (<span class="html-italic">f</span>-θ) lens are used to scan the laser beam on the work piece.</p>
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<p>Representation of EDM milling operation.</p>
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<p>Parameters involved into the EDM process.</p>
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<p>Schematic representation of the geometries designed for the comparison between the femtosecond laser and the EDM technology: (<b>a</b>) micro-channel; (<b>b</b>) micro-pillar.</p>
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<p>Schematic representation of the geometries designed for the comparison between the femtosecond laser and the EDM technology with the effect of the taper angle on (<b>a</b>) micro-channel and (<b>b</b>) micro-pillar.</p>
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<p>Top (<b>a</b>) and bottom (<b>b</b>) optical microscopy images of the channels on aluminum, stainless steel and titanium alloys obtained with femto-laser.</p>
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<p>Three-dimensional reconstruction of the aluminum channel realized with laser milling.</p>
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<p>Profiles acquired with the white light interferometer of the channels realized with laser milling on (<b>a</b>) Al5754-H111, (<b>b</b>) AISI316L and (<b>c</b>) Ti6Al4V.</p>
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<p>SEM images of the femto-laser pillars on stainless steel (<b>a</b>,<b>b</b>) and titanium alloys (<b>c</b>,<b>d</b>), depth 50 µm (<b>a</b>,<b>c</b>) and 100 µm (<b>b</b>,<b>d</b>).</p>
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<p>Three-dimensional reconstruction of pillars on AISI 316L, with a depth of about (<b>a</b>) ∆ = 50 µm and (<b>b</b>) ∆ = 100 µm, obtained using a femto-laser.</p>
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<p>Top (<b>a</b>) and bottom (<b>b</b>) optical microscopy images of the channels on aluminum, stainless steel and titanium alloys for 100 µm depth obtained with EDM.</p>
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<p>Example of a 3D reconstruction of a channel on aluminum at 100 µm as depth.</p>
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<p>Reconstructed profile of the channels machined with EDM technology (<b>a</b>) Al5754-H111, (<b>b</b>) AISI316L and (<b>c</b>) Ti6Al4V.</p>
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<p>SEM images of the EDM pillars on stainless steel (<b>a</b>,<b>b</b>) and titanium alloy (<b>c</b>,<b>d</b>), depth 50 µm (<b>a</b>,<b>c</b>) and 100 µm (<b>b</b>,<b>d</b>).</p>
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<p>3D reconstruction of pillars on Ti6Al4V with a depth of about (<b>a</b>) ∆ = 50 µm and (<b>b</b>) ∆ = 100 µm obtained using EDM.</p>
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<p>Comparison between the MRR of the channel obtained with a femto-laser and EDM.</p>
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<p>Comparison between the taper of the channel obtained with a femto-laser and EDM.</p>
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<p>Comparison between the Ra of the channel obtained with z femto-laser and EDM.</p>
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<p>Comparison between the MRR of the pillars obtained with a femto-laser and EDM.</p>
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<p>Comparison between the taper of the pillars obtained with a femto-laser and EDM.</p>
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13 pages, 4201 KiB  
Communication
Evaluating Temperature Control in Friction Stir Welding for Industrial Applications
by Arnold Wright, Troy R. Munro and Yuri Hovanski
J. Manuf. Mater. Process. 2021, 5(4), 124; https://doi.org/10.3390/jmmp5040124 - 19 Nov 2021
Cited by 11 | Viewed by 3582
Abstract
Reports in the literature indicate that temperature control in Friction Stir Welding (FSW) enables better weld properties and easier weld process development. However, although methods of temperature control have existed for almost two decades, industry adoption remains limited. This work examines single-loop Proportional-Integral-Derivative [...] Read more.
Reports in the literature indicate that temperature control in Friction Stir Welding (FSW) enables better weld properties and easier weld process development. However, although methods of temperature control have existed for almost two decades, industry adoption remains limited. This work examines single-loop Proportional-Integral-Derivative (PID) control on spindle speed as a comparatively simple and cost-effective method of adding temperature control to existing FSW machines. Implementation of PID-based temperature control compared to uncontrolled FSW in AA6111 at linear weld speeds of 1–2 m per minute showed improved mechanical properties and greater consistency in properties along the length of the weld under temperature control. Additionally, results indicate that a minimum spindle rpm may exist, above which tensile specimens do not fracture within the weld centerline, regardless of temperature. This work demonstrates that a straightforward, PID-based implementation of temperature control at high weld rates can produce high quality welds. Full article
(This article belongs to the Special Issue Advanced Joining Processes and Techniques)
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<p>Diagram of the friction stir welding processing showing a rotating tool translating down the interface of two abutting plates.</p>
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<p>Schematic of thermocouple placement in tool (<b>left</b>) and actual tool (<b>right</b>).</p>
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<p>Graphical representation of the PID control implementation.</p>
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<p>Typical tuning weld using the auto-tuner. A stable state was reached at around 450 mm, and roughly 20 cycles of +/− 10% rpm were able to be completed, far exceeding the minimum of 5 cycles.</p>
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<p>(<b>a</b>) Image of weld setup, showing weldpiece and clamping, etc. (<b>b</b>) Dimensions of tensile specimen. (<b>c</b>) Illustration of tensile specimen locations in relation to the weld. First tensile specimen is centered at 85 mm into the weld, with each subsequent specimen spaced 150 mm from the previous.</p>
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<p>Examples of the three classes of fracture modes. At the top is a Weld Centerline (CL) break, showing an incomplete weld; in the center is a HAZ break, revealing a complete weld; and at the bottom is the “best” fracture mode: a break outside the weld. This same designation is used throughout this work.</p>
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<p>Plot depicting the variation of rotational velocity (blue) to achieve a temperature (red) of 425 °C. Threshold for rotational velocity to achieve acceptable fracture is shown with a dashed line at 1300 RPM.</p>
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<p>Plot depicting the variation of rotational velocity (blue) to achieve a temperature (red) of 450 °C. Threshold for rotational velocity to achieve acceptable fracture is shown with a dashed line at 1300 RPM.</p>
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<p>Temperature-controlled response for each weld at 1000 mmpm (<b>left</b>) and 2000 mmpm (<b>right</b>). The welds are labeled according to the control method: either the set-point temperature for the temperature-controlled welds, or the value of the fixed rpm for the uncontrolled welds. Markers are for convenience in curve identification, the true sampling rate was 64 Hz.</p>
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<p>Effect of weld position, spindle rpm, and weld temperature for the 1000 mmpm welds. (<b>a</b>) Weld strengths as a function of tensile specimen location, as shown in <a href="#jmmp-05-00124-f005" class="html-fig">Figure 5</a>. The distinguishing parameters of each weld (temperature-controlled or fixed-rpm) are listed along the top. (<b>b</b>) Weld strengths as a function of the tool temperature experienced by the tensile specimen location during welding. (<b>c</b>) Weld strengths as a function of the spindle rpm at the tensile specimen location. For all, marker types are as given in <a href="#jmmp-05-00124-f006" class="html-fig">Figure 6</a>: circle—CL, triangle—HAZ, star—OW. Experimental error for tensile values is ±2.0 MPa.</p>
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<p>Effect of weld position, spindle rpm, and weld temperature for the 2000 mmpm welds. (<b>a</b>) Weld strengths as a function of tensile specimen location, as shown in <a href="#jmmp-05-00124-f005" class="html-fig">Figure 5</a>. The distinguishing parameters of each weld (temperature-controlled or fixed-rpm) are listed along the top. (<b>b</b>) Weld strengths as a function of the tool temperature experienced by the tensile specimen location during welding. (<b>c</b>) Weld strengths as a function of the spindle rpm at the tensile specimen location. For all, marker types are as given in <a href="#jmmp-05-00124-f006" class="html-fig">Figure 6</a>: circle—CL, triangle—HAZ, star—OW. Experimental error for tensile values is ±2.0 MPa.</p>
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28 pages, 8532 KiB  
Article
Multi-Objective Variable Neighborhood Strategy Adaptive Search for Tuning Optimal Parameters of SSM-ADC12 Aluminum Friction Stir Welding
by Suppachai Chainarong, Rapeepan Pitakaso, Worapot Sirirak, Thanatkij Srichok, Surajet Khonjun, Kanchana Sethanan and Thai Sangthean
J. Manuf. Mater. Process. 2021, 5(4), 123; https://doi.org/10.3390/jmmp5040123 - 16 Nov 2021
Cited by 11 | Viewed by 3314
Abstract
This research presents a novel algorithm for finding the most promising parameters of friction stir welding to maximize the ultimate tensile strength (UTS) and maximum bending strength (MBS) of a butt joint made of the semi-solid material (SSM) ADC12 aluminum. The relevant welding [...] Read more.
This research presents a novel algorithm for finding the most promising parameters of friction stir welding to maximize the ultimate tensile strength (UTS) and maximum bending strength (MBS) of a butt joint made of the semi-solid material (SSM) ADC12 aluminum. The relevant welding parameters are rotational speed, welding speed, tool tilt, tool pin profile, and rotation. We used the multi-objective variable neighborhood strategy adaptive search (MOVaNSAS) to find the optimal parameters. We employed the D-optimal to find the regression model to predict for both objectives subjected to the given range of parameters. Afterward, we used MOVaNSAS to find the Pareto front of the objective functions, and TOPSIS to find the most promising set of parameters. The computational results show that the UTS and MBS of MOVaNSAS generate a 2.13% to 10.27% better solution than those of the genetic algorithm (GA), differential evolution algorithm (DE), and D-optimal solution. The optimal parameters obtained from MOVaNSAS were a rotation speed of 1469.44 rpm, a welding speed of 80.35 mm/min, a tool tilt of 1.01°, a cylindrical tool pin profile, and a clockwise rotational direction. Full article
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Graphical abstract

Graphical abstract
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<p>An example of the prepared specimens.</p>
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<p>UTS and MBS test machine.</p>
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<p>(<b>a</b>) Predicted conditions of UTS, (<b>b</b>) predicted conditions of MBS.</p>
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<p>Pareto front of GA.</p>
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<p>Pareto front of DE.</p>
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<p>Pareto front of MOVaNSAS.</p>
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<p>Quality of the weld line based on the relationship between tensile strength and elongation percentage.</p>
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<p>Weld seam of MOVaNSAS: (<b>a</b>) weld seam surface suggestion; (<b>b</b>) grain size comparison with base material and weld zone.</p>
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<p>The microstructure photography evaluation by OM of optimal welding conditions of MOVaNSAS: (<b>a</b>,<b>f</b>) BM, (<b>b</b>,<b>c</b>) SZ, (<b>e</b>) TMAZ-AS, and (<b>d</b>) TMAZ-RS.</p>
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<p>The microstructure photography evaluation by OM of optimal welding conditions of D-optimal: (<b>a</b>,<b>f</b>) BM, (<b>b</b>,<b>c</b>) SZ, (<b>e</b>) TMAZ-AS, and (<b>d</b>) TMAZ-RS.</p>
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<p>The microstructure photography evaluation by OM of optimal welding conditions of initial experiment: (<b>a</b>,<b>f</b>) BM, (<b>b</b>,<b>c</b>) SZ, (<b>e</b>) TMAZ-AS, and (<b>d</b>) TMAZ-RS.</p>
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<p>The characteristics of the Al<sub>5</sub>FeSi intermetallic compound evaluation by SEM (6000×) of the optimal welding conditions of MOVaNSAS: (<b>a</b>,<b>f</b>) BM, (<b>b</b>,<b>c</b>) SZ, (<b>e</b>) TMAZ-AS, and (<b>d</b>) TMAZ-RS.</p>
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<p>The characteristics of the Al<sub>5</sub>FeSi intermetallic compound evaluation by SEM (6000×) of the optimal welding conditions of D-optimal: (<b>a</b>,<b>f</b>) BM, (<b>b</b>,<b>c</b>) SZ, (<b>e</b>) TMAZ-AS, and (<b>d</b>) TMAZ-RS.</p>
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<p>The characteristics of the Al<sub>5</sub>FeSi intermetallic compound evaluation by SEM (6000×) of the best initial experiment: (<b>a</b>,<b>f</b>) BM, (<b>b</b>,<b>c</b>) SZ, (<b>e</b>) TMAZ-AS, and (<b>d</b>) TMAZ-RS.</p>
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<p>The EDX-ray spectroscopy of alloying elements at rotation speed 1469.44 rpm, welding speed 80.35 mm/min, tilt angle 1.01°, cylindrical tool, and clockwise direction.</p>
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16 pages, 9893 KiB  
Article
Accuracy and Sheet Thinning Improvement of Deep Titanium Alloy Part with Warm Incremental Sheet-Forming Process
by Badreddine Saidi, Laurence Giraud Moreau, Abel Cherouat and Rachid Nasri
J. Manuf. Mater. Process. 2021, 5(4), 122; https://doi.org/10.3390/jmmp5040122 - 15 Nov 2021
Cited by 2 | Viewed by 2900
Abstract
Incremental forming is a recent forming process that allows a sheet to be locally deformed with a hemispherical tool in order to gradually shape it. Despite good lubrication between the sheet and the tip of the smooth hemisphere tool, ductility often occurs, limiting [...] Read more.
Incremental forming is a recent forming process that allows a sheet to be locally deformed with a hemispherical tool in order to gradually shape it. Despite good lubrication between the sheet and the tip of the smooth hemisphere tool, ductility often occurs, limiting the formability of titanium alloys due to the geometrical inaccuracy of the parts and the inability to form parts with a large depth and wall angle. Several technical solutions are proposed in the literature to increase the working temperature, allowing improvement in the titanium alloys’ formability and reducing the sheet thinning, plastic instability, and failure localization. An experimental procedure and numerical simulation were performed in this study to improve the warm single-point incremental sheet forming of a deep truncated cone in Ti-6Al-4V titanium alloy based on the use of heating cartridges. The effect of the depth part (two experiments with a truncated cone having a depth of 40 and 60 mm) at hot temperature (440 °C) on the thickness distribution and sheet shape accuracy are performed. Results show that the formability is significantly improved with the heating to produce a deep part. Small errors are observed between experimental and theoretical profiles. Moreover, errors between experimental and numerical displacements are less than 6%, which shows that the Finite Element (FE) model gives accurate predictions for titanium alloy deep truncated cones. Full article
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<p>Warm incremental sheet-forming setup with cartridge heaters.</p>
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<p>Warm incremental sheet-forming setup (WSPIF).</p>
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<p>The shape CAD of the truncated cone used to create a punch toolpath.</p>
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<p>Truncated cones with a wall angle of 45° formed at different temperature.</p>
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<p>Scan truncated cone (<b>a</b>) with three-dimensional measuring machine (MMT) (<b>b</b>).</p>
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<p>The 3D CAD model, FE meshing, and partition of initial blank.</p>
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<p>Experimental deformed truncated cone for α = 50°, h = 40 mm, and h = 60 mm.</p>
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<p>Scan of two truncated cone sides according to four cutting planes.</p>
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<p>Experimental thicknesses (tf) according to the four cutting planes for h = 40 mm.</p>
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<p>Experimental profiles shape according to the four cutting planes for h = 40 mm.</p>
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<p>Relative profile error compared to the profile along to the plane 1 for h = 40 mm.</p>
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<p>Four cutting planes measurement of FE simulation truncated cone.</p>
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<p>Four cutting planes measurement of FE simulation truncated cone.</p>
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<p>Predicted thicknesses distribution (tf) according to the four cutting planes for h = 40 mm.</p>
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<p>Experimental and FE numerical thickness distributions for depth h = 40 mm.</p>
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<p>Experimental and FE numerical thickness distributions for depth h = 60 mm.</p>
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<p>Experimental and FE numerical profile shapes for h = 60 m.</p>
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<p>Relative error, U<sub>exp</sub>/U<sub>theo</sub> and U<sub>num</sub>/U<sub>theo</sub>, for the case of (h = 60 mm, α = 50°).</p>
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29 pages, 8830 KiB  
Article
Modelling and Analysis of Topographic Surface Properties of Grinding Wheels
by Praveen Sridhar, Daniel Mannherz and Kristin M. de Payrebrune
J. Manuf. Mater. Process. 2021, 5(4), 121; https://doi.org/10.3390/jmmp5040121 - 10 Nov 2021
Cited by 2 | Viewed by 3439
Abstract
Grinding is one of the effective manufacturing processes with which to produce highly accurate parts with an ultra-fine surface finish. The tool used to remove materials in grinding is called the grinding wheel. Abrasive grains made of extremely hard materials (alumina, silica, cubic [...] Read more.
Grinding is one of the effective manufacturing processes with which to produce highly accurate parts with an ultra-fine surface finish. The tool used to remove materials in grinding is called the grinding wheel. Abrasive grains made of extremely hard materials (alumina, silica, cubic boron nitride, and diamond) having a definite grit size but a random shape are bonded on the circumferential surface of the grinding wheel. The fabrication process is controlled so that the wheel exhibits a prescribed structure (in the scale of soft to hard). At the same time, the distribution of grains must follow a prescribed grade (in the scale of dense to open). After the fabrication, the wheel is dressed to make sure of its material removal effectiveness, which itself depends on the surface topography. The topography is quantified by the distribution and density of active abrasive grains located on the circumferential surface, the grains’ protrusion heights, and their pore volume ratio. The prediction of the surface topography mentioned above requires a model that considers the entire manufacturing process and the influences on the grinding wheel properties. This study fills this gap in modelling the grinding wheel by presenting a surface topography model and simulation framework for the effect of the grinding wheel fabrication process on the surface topography. The simulation results have been verified by conducting experiments. This study will thus help grinding wheel manufacturers in developing more effective grinding wheels. Full article
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<p>Visualisation of the grinding process, adapted from [<a href="#B2-jmmp-05-00121" class="html-bibr">2</a>].</p>
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<p>Example manufacturer coding for grinding wheel C30LV and explanations.</p>
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<p>Grinding wheel cut-out used for simulation.</p>
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<p>Simulation process in comparison to manufacturing process; adapted based on [<a href="#B16-jmmp-05-00121" class="html-bibr">16</a>].</p>
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<p>Input parameters and output properties of simulation; partly adapted based on [<a href="#B18-jmmp-05-00121" class="html-bibr">18</a>].</p>
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<p>Visualisation of particle mixing and packing in LIGGGHTS.</p>
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<p>Visualisation of bond layer and abrasive grain; adapted from [<a href="#B16-jmmp-05-00121" class="html-bibr">16</a>].</p>
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<p>Compression of particles.</p>
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<p>Development of particle connections and neck radius for compression and firing; adapted from [<a href="#B16-jmmp-05-00121" class="html-bibr">16</a>].</p>
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<p>Visualisation of new radius calculation.</p>
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<p>Visualisation of dressing process.</p>
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<p>Visualisation of (<b>a</b>) static grain count and (<b>b</b>) protrusion height; partly adapted from [<a href="#B19-jmmp-05-00121" class="html-bibr">19</a>].</p>
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<p>Visualisation of effective pore volume; partly adapted from [<a href="#B16-jmmp-05-00121" class="html-bibr">16</a>].</p>
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<p>Visualisation of simulated grinding wheel surface.</p>
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<p>Visualisation of the simulation steps.</p>
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<p>Distribution of grain size for grit 46.</p>
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<p>Compression force for different percentages of compression.</p>
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<p>Average bonding strength of particles for different percentages of compression.</p>
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<p>Average bonding strength depending on compression for different grit sizes; literature values from [<a href="#B38-jmmp-05-00121" class="html-bibr">38</a>] (p. 116).</p>
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<p>Alternative static grain count dependent on different percentages of compression.</p>
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<p>Alternative static grain count dependent on different percentages of maximum feasible average bonding strength.</p>
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<p>Alternative average protrusion height dependent on different percentages of compression.</p>
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<p>Alternative average protrusion height in comparison to the percentage of maximum feasible average bonding strength.</p>
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<p>Alternative average effective pore volume in comparison to different percentages of compression.</p>
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<p>Alternative average effective pore volume in comparison to the percentage of maximum feasible average bonding strength.</p>
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<p>Grinding wheel topography detection platform.</p>
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<p>Detected 2D surface topography.</p>
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<p>Detected 3D surface topography.</p>
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<p>Comparison of simulated static grain count values with measured values from experiments and the literature [<a href="#B23-jmmp-05-00121" class="html-bibr">23</a>].</p>
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<p>Comparison of simulated protrusion height values with measured values from experiments and the literature [<a href="#B23-jmmp-05-00121" class="html-bibr">23</a>].</p>
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<p>Potential maximum of bonding strength dependent on the percentual dressing depth.</p>
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<p>Potential maximum of alternative static grain count dependent on the percentual dressing depth.</p>
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<p>Potential maximum of alternative static grain count dependent on the grit sizes for a fixed dressing depth of 0.1 mm.</p>
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<p>Potential maximum of alternative protrusion height dependent on the percentual dressing depth.</p>
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<p>Potential maximum of alternative protrusion height dependent on the grit sizes for a fixed dressing depth of 0.1 mm.</p>
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<p>Potential maximum of alternative pore volume dependent on the percentual dressing depth.</p>
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<p>Potential maximum of alternative pore volume dependent on the grit sizes for a fixed dressing depth of 0.1 mm.</p>
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<p>Grit 20 <math display="inline"><semantics> <mrow> <mo>(</mo> <msub> <mi mathvariant="normal">d</mi> <mi>mean</mi> </msub> <mo>=</mo> <mn>0.85</mn> </mrow> </semantics></math> mm) surface topography with alternative protrusion height at 0%, 50%, and 100% maximum compression.</p>
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<p>Grit 80 <math display="inline"><semantics> <mrow> <mo>(</mo> <msub> <mi mathvariant="normal">d</mi> <mi>mean</mi> </msub> <mo>=</mo> <mn>0.165</mn> </mrow> </semantics></math> mm) surface topography with alternative protrusion height at 0%, 50%, and 100% maximum compression.</p>
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<p>Grit 20 surface topography with bonding force at 0%, 50%, and 100% maximum compression.</p>
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<p>Grit 80 surface topography with bonding force at 0%, 50%, and 100% maximum compression.</p>
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<p>Dressing effects on surface topography for 10%, 30%, and 60% percentual dressing of grit 20.</p>
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<p>Grit 20 surface topography comparsion for (<b>a</b>) protrusion height and (<b>b</b>) alternative protrusion height.</p>
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<p>Radar chart optimised for maximum bonding strength and alternative static grain count at maximum compression; values in % of the maximum possible value.</p>
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13 pages, 3176 KiB  
Article
Thermomechanical Impact of the Single-Lip Deep Hole Drilling on the Surface Integrity on the Example of Steel Components
by Jan Nickel, Nikolas Baak, Pascal Volke, Frank Walther and Dirk Biermann
J. Manuf. Mater. Process. 2021, 5(4), 120; https://doi.org/10.3390/jmmp5040120 - 9 Nov 2021
Cited by 7 | Viewed by 2889
Abstract
The fatigue behavior of components made of quenched and tempered steel alloys is of elementary importance, especially in the automotive industry. To a great extent, the components’ fatigue strength is influenced by the surface integrity properties. For machined components, the generated surface is [...] Read more.
The fatigue behavior of components made of quenched and tempered steel alloys is of elementary importance, especially in the automotive industry. To a great extent, the components’ fatigue strength is influenced by the surface integrity properties. For machined components, the generated surface is often exposed to the highest thermomechanical loads, potentially resulting in transformations of the subsurface microstructure and hardness as well as the residual stress state. While the measurement of the mechanical load using dynamometers is well established, in-process temperature measurements are challenging, especially for drilling processes due to the process kinematics and the difficult to access cutting zone. To access the impact of the thermomechanical load during the single-lip drilling process on the produced surface integrity, an in-process measurement was developed and applied for different cutting parameters. By using a two-color pyrometer for temperature measurements at the tool’s cutting edge in combination with a dynamometer for measuring the occurring force and torque, the influence of different cutting parameter variations on the thermomechanical impact on the bore surface are evaluated. By correlating force and temperature values with the resultant surface integrity, a range of process parameters can be determined in which the highest dynamic strength of the samples is expected. Thermally induced defects, such as the formation of white etching layers (WEL), can be avoided by the exact identification of critical parameter combinations whereas a mechanically induced microstructure refinement and the induction of residual compressive stresses in the subsurface zone is targeted. Further, eddy-current analysis as a non-destructive method for surface integrity evaluation is used for the characterization of the surface integrity properties. Full article
(This article belongs to the Special Issue Surface Integrity in Machining and Post-processing)
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<p>Tool properties and geometry.</p>
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<p>Details of the sample preparation with cross-bores for applying thermocouples and a pyrometer fiber.</p>
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<p>Sketch of the experimental setup including temperature and force measurement sensors.</p>
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<p>Eddy-current testing device (<b>a</b>); eddy-current sensor on the inside of a specimen (<b>b</b>).</p>
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<p>Average maximum temperatures measured with TC for different cutting velocities and feed rates.</p>
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<p>Exemplary voltage and temperature measurement at different tool cutting-edge positions.</p>
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<p>Maximum temperatures T<sub>PM, max.</sub> for a varying cutting velocities v<sub>c</sub> and feed rates f.</p>
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<p>Exemplary force and torque measurement for the single-lip deep hole drilling process (<b>a</b>); Average feed force F<sub>f</sub> and torque M<sub>D</sub> for different cutting velocities and feed rates (<b>b</b>).</p>
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<p>Micrographs of the bores’ subsurface microstructure for different cutting velocities and feed rates.</p>
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<p>Results of eddy-current measurement at bores drilled with different cutting velocities (<b>a</b>) and different feed rates (<b>b</b>); SEM microstructure analysis of the bores’ subsurface (<b>c</b>).</p>
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13 pages, 4467 KiB  
Article
Effect of Electric Current on SPS Densification of Spherical Copper Powder
by Romaric Collet, Sophie Le Gallet, Frédéric Charlot, Sabine Lay, Jean-Marc Chaix and Frédéric Bernard
J. Manuf. Mater. Process. 2021, 5(4), 119; https://doi.org/10.3390/jmmp5040119 - 5 Nov 2021
Cited by 8 | Viewed by 2652
Abstract
When a current is involved, as in spark plasma sintering, metallic powders are heated by the Joule effect through both tool and specimen. Other mechanisms might occur, but it is difficult to separate the role of the temperature from the role of the [...] Read more.
When a current is involved, as in spark plasma sintering, metallic powders are heated by the Joule effect through both tool and specimen. Other mechanisms might occur, but it is difficult to separate the role of the temperature from the role of the current inside the sample as, in most cases, the two parameters are not controlled independently. In this paper, the consolidation and the densification of a pure copper powder were studied in three configurations for obtaining different electric current paths: (i) current flowing through both the powder and the die, (ii) current forced into the powder and (iii) no current allowed in the powder. Electrical conductivity measurements showed that even low-density samples displayed higher conductivities than graphite by several orders of magnitude. FEM simulations confirmed that these copper specimens were mainly heated by the graphite punches. No modification of the microstructure by the flow of current could be observed. However, the absence of current in the specimen led to a decrease in densification. No significant temperature difference was modeled between the configurations, suggesting that differences are not linked to a thermal cause but rather to a current effect. Full article
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<p>(<b>a</b>) Morphology (SEM observation) and (<b>b</b>) microstructure (FIB-SEM cross section) of TEKMAT Cu-38 copper powder particles.</p>
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<p>The configurations used to control the current flow. The two standard SPS configurations (St) with graphite die differ in the thermocouple position (A or B), in order to ensure relevant comparisons with the cases of forced current (FC, alumina matrix) or no current (NC, alumina platelets) through the sample.</p>
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<p>Comparison of standard SPS configurations (St) with two different positions of the thermocouple used to control the thermal cycle (positions A and B in <a href="#jmmp-05-00119-f002" class="html-fig">Figure 2</a>).</p>
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<p>Densification of the copper powder during sintering for standard SPS conditions (St) and forced current (FC) conditions, with applied pressure 4 MPa and heating rate 50 °C·min<sup>−1</sup> (thermocouple in position A).</p>
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<p>Fracture surfaces observed by SEM on samples after SPS processing in standard (StA) and forced current (FC) conditions, under 4 MPa at 50 °C·min<sup>−1</sup> up to 500 °C, 700 °C and 900 °C.</p>
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<p>Densification of the copper powder during sintering in the cases of no current (NC) and standard SPS (StB), with applied pressure 4 MPa, heating rate 50 °C·min<sup>−1</sup> (thermocouple in position B).</p>
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<p>Densification of the copper powder during sintering in the cases of no current (NC) and standard SPS (StB) when a pressure of 28 MPa is applied. Fracture surfaces observed by SEM in the sample obtained in standard conditions (StB) at 500, 700 and 900 °C.</p>
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<p>Effective electrical conductivity at room temperature of Cu samples sintered by SPS at temperatures between 300 and 1000 °C.</p>
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<p>Evolution of the relative density of a copper sample during SPS experiments at constant heating rate (d<span class="html-italic">T</span>/d<span class="html-italic">t</span> = 50 °C·min<sup>−1</sup>) and effective electrical conductivity of the copper sample calculated from the density and Equations (2) and (3), for two applied pressures: (<b>a</b>) <span class="html-italic">p</span> = 4 MPa and (<b>b</b>) <span class="html-italic">p</span> = 28 MPa. The conductivities of graphite and dense copper are plotted for comparison purposes.</p>
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<p>FEM simulation of heating for the three configurations. Snapshots of current density (<span class="html-italic">i</span>), heat production rate (<span class="html-italic">P)</span> (logarithmic scale) and temperature (<span class="html-italic">T)</span> at <span class="html-italic">t</span> = 600 s (average <span class="html-italic">T</span> around 700 °C inside the specimen). The same temperature–color scale is used for the three configurations in each case.</p>
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<p>FEM simulation of heating for the three configurations. Evolution of the difference between the mean sample temperature (Tm) and the temperature at the thermocouple position (A or B) during the simulated heating at about 50 °C·min<sup>−1</sup>.</p>
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15 pages, 8214 KiB  
Article
Mechanical Properties and Failure Mechanisms of Refill Friction Stir Spot Welds
by Guruvignesh Lakshmi Balasubramaniam, Enkhsaikhan Boldsaikhan, Gratias Fernandez Joseph Rosario, Saravana Prabu Ravichandran, Shintaro Fukada, Mitsuo Fujimoto and Kenichi Kamimuki
J. Manuf. Mater. Process. 2021, 5(4), 118; https://doi.org/10.3390/jmmp5040118 - 1 Nov 2021
Cited by 8 | Viewed by 4475
Abstract
Refill friction stir spot welding (RFSSW) is an innovative solid-state welding technology for aluminum structures. The presented study aimed to evaluate the mechanical properties of refill spot welds and their failure mechanisms with the use of industrial test standards. The mechanical properties of [...] Read more.
Refill friction stir spot welding (RFSSW) is an innovative solid-state welding technology for aluminum structures. The presented study aimed to evaluate the mechanical properties of refill spot welds and their failure mechanisms with the use of industrial test standards. The mechanical properties of refill spot welds were compared with those of rivet joints with comparable joint sizes. Static load tests indicated that RFSSW coupons demonstrate higher ultimate shear strengths but slightly lower ultimate tension strengths than those of rivet coupons. Fatigue test results indicated that both RFSSW coupons and rivet coupons demonstrate comparable performances during low-load-level fatigue lap shear tests but RFSSW coupons outperform rivet coupons during high-load-level fatigue lap shear tests. The failure mechanisms of refill spot welds were characterized in terms of external loading, parent metal properties, and weld properties. Refill spot weld failures included parent metal tensile failures, nugget pullouts, and interfacial failures. A refill spot weld may demonstrate one or a combination of these mechanical failures. Although the mechanical tests of refill spot welds demonstrated promising results with predictable failure mechanisms, the metallurgical evolution involved in RFSSW remains a subject to study. Full article
(This article belongs to the Special Issue Frontiers in Friction Stir Welding and Processing)
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<p>RFSSW process stages.</p>
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<p>Refill friction stir spot welds: (<b>a</b>) a sample with refill spot welds, (<b>b</b>) top view of a refill spot weld, and (<b>c</b>) bottom view of a refill spot weld. All images depict perspective views.</p>
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<p>Lap joint configurations: (<b>a</b>) refill spot weld configuration and (<b>b</b>) rivet joint configuration.</p>
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<p>Two-spot coupon configurations in accordance with NASM-1312-4: (<b>a</b>) 2-refill-spot-weld coupon configuration and (<b>b</b>) 2-rivet-joint coupon configuration. D<sub>w</sub> is the refill spot weld diameter, which is 7 mm.</p>
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<p>Cross-coupon configurations in accordance with ISO-14272: (<b>a</b>) RFSSW cross-coupon configuration and (<b>b</b>) rivet cross-coupon configuration.</p>
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<p>Four-spot coupon configurations in accordance with NASM-1312-21: (<b>a</b>) 4-refill-spot-weld coupon configuration and (<b>b</b>) 4-rivet-joint coupon configuration. D<sub>w</sub> is the refill spot weld diameter, which is 7 mm.</p>
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<p>Mechanical test setups: (<b>a</b>) NASM-1312-4 test setup, (<b>b</b>) ISO-14272 test setup, and (<b>c</b>) NASM-1312-21 test setup.</p>
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<p>Box-whisker plots of static load test results: (<b>a</b>) ultimate shear loads of 2-spot coupons and (<b>b</b>) ultimate tension loads of cross coupons. The 2-spot coupons were tested in accordance with NASM-1312-4, and the cross coupons were tested in accordance with ISO-14272.</p>
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<p>Two-spot coupons before and after static load lap shear tests: (<b>a</b>) 2-refill-spot-weld coupon (<b>left</b>) and nugget pullout failures (<b>right</b>); (<b>b</b>) 2-rivet-joint coupon (<b>left</b>) and rivet shear failures (<b>right</b>). The image of the nugget pullout failures shows the faying surfaces of the stiffener and skin pieces. The image of the rivet shear failures also shows the faying surfaces of the skin and stiffener pieces. The images may have different scaling for clarity.</p>
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<p>Cross coupons before and after static cross-tension load tests: (<b>a</b>) RFSSW cross coupon (<b>left</b>) and nugget pullout failure (<b>right</b>); (<b>b</b>) rivet cross coupon (<b>left</b>) and rivet pullout failure (<b>right</b>). The image of the nugget pullout failure shows the external surface of the stiffener piece and the faying surface of the skin piece. The image of the rivet pullout failure shows the external surface of the skin piece and the external surface of the stiffener pieces.</p>
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<p>Fatigue test results: fatigue tests were carried out in accordance with NASM-1312-21.</p>
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<p>Four-spot coupons before and after fatigue lap shear pull tests: (<b>a</b>) 4-refill-spot-weld coupon (<b>left</b>) and tensile failure of stiffener piece (<b>right</b>); (<b>b</b>) 4-rivet-joint coupon (<b>left</b>) and tensile failure of stiffener piece (<b>right</b>). The images may have different scaling for clarity.</p>
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<p>Refill spot weld regions: (<b>a</b>) refill spot weld cross-section image and (<b>b</b>) refill spot weld cross-section microhardness map. The stiffener piece is a 1.27-mm-thick AA7075-T6 sheet, which has a lighter color in the weld cross-section image. The skin piece is a 1.6-mm-thick AA2024-T3 sheet, which has a darker color in the weld cross-section image. The welding process was performed on the stiffener side. The microhardness measurements are the Vickers hardness values sampled along the midplane lines of the stiffener sheet and the skin sheet of the weld cross-section specimen. The hardness measurement lines are indicated by the perforated lines in the weld cross-section image (<b>a</b>). The nominal Vickers hardness values of AA7075-T6 and AA2024-T3 are ~183 HV and ~135 HV, respectively.</p>
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<p>Mechanical failures of refill spot welds.</p>
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<p>Refill spot weld cross-section schematics with external loading conditions, including pure shear loading, pure tension loading, and shear-and-tension loading.</p>
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<p>Schematics of refill spot weld failures: (<b>a</b>) parent metal tensile failures and an interfacial shear failure caused by pure shear loading and (<b>b</b>) nugget pullouts and an interfacial tension failure caused by pure tension loading. The graphics of each failure include the top view, the cross-section view, and the bottom view. The failure surfaces are highlighted in orange and red.</p>
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<p>Schematics of refill spot weld failures caused by coupled shear-and-tension loading: (<b>a</b>) parent metal tensile failures and (<b>b</b>) nugget pullout failures and an interfacial failure. The graphics of each failure include the top view, the cross-section view, and the bottom view. The failure surfaces are highlighted in orange and red.</p>
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19 pages, 4878 KiB  
Article
Forces Shapes in 3-Axis End-Milling: Classification and Characteristic Equations
by Niccolò Grossi, Lorenzo Morelli, Giuseppe Venturini and Antonio Scippa
J. Manuf. Mater. Process. 2021, 5(4), 117; https://doi.org/10.3390/jmmp5040117 - 29 Oct 2021
Cited by 4 | Viewed by 2875
Abstract
In 3-axis milling, cutting force analysis represents one of the main methods to increase the quality and productivity of the process. In this context, cutting force shape gives information of both monitoring and prediction of the cutting process. However, the cutting force shape [...] Read more.
In 3-axis milling, cutting force analysis represents one of the main methods to increase the quality and productivity of the process. In this context, cutting force shape gives information of both monitoring and prediction of the cutting process. However, the cutting force shape is not unique, and it changes according to the cutting strategy, tool geometry, and cutting parameters. This paper presents a comprehensive approach to predict and classify cutting force shapes in 3-axis milling operations. In detail, the proposed approach starts by classifying the cutting force shapes for a single fluted endmill (i.e., single flute force shape), and, considering how the single flute force shapes may overlap one another, it extends the classification to a general multiple-fluted endmill. Moreover, the method provides, through analytical equations, angles, and magnitude dimensionless parameters of each key point, describing each shape classified. Finally, the proposed approach was experimentally validated through several milling tests in different cutting conditions. Full article
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<p>Schematic diagram of milling parameters: (<b>a</b>) Down-milling (<b>b</b>) Up-milling.</p>
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<p>Schematic diagram of cutting edge’ locations during the cutting process (black dashed lines represent the cutting edge at the different key positions).</p>
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<p>Examples of single flute <span class="html-italic">F</span> shapes in one period (<b>a</b>) Down-milling (<span class="html-italic">ϑ</span><sub>1</sub>; <span class="html-italic">ϑ</span><sub>1</sub> + <span class="html-italic">ϕ<sub>z</sub></span>) (<b>b</b>) Up-milling (<span class="html-italic">ϑ</span><sub>4</sub> − <span class="html-italic">ϕ<sub>z</sub></span>; <span class="html-italic">ϑ</span><sub>4</sub>).</p>
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<p>Example of multiple flutes endmill <span class="html-italic">F</span> shape for both down-milling and up-milling.</p>
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<p>Example of different degrees of overlap for different types of single flute <span class="html-italic">F</span> shape in down-milling.</p>
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<p>(<b>a</b>) experimental set-up (<b>b</b>) tool 1 (<b>c</b>) tool 2.</p>
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<p>Type I normalized <span class="html-italic">F</span> shapes for tool 1 (tests 1 to 4 in down-milling; tests 5 to 8 in up-milling).</p>
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<p>Type I normalized <span class="html-italic">F</span> shapes for tool 2 (tests 7 to 9 in down-milling; tests 10 to 12 in up-milling).</p>
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<p>Type IIa normalized <span class="html-italic">F</span> shapes (tests 13 to 15 in down-milling; tests 16 to 18 in up-milling).</p>
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<p>Type IIb normalized <span class="html-italic">F</span> shapes (tests 19 to 22 in down-milling; tests 23 to 26 in up-milling).</p>
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<p>Type III normalized <span class="html-italic">F</span> shapes (tests 27 to 29 in down-milling; tests 30 to 32 in up-milling).</p>
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<p>Normalized total forces comparison: test 15 vs. 33; test 22 vs. 34.</p>
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16 pages, 8358 KiB  
Article
Influence of Pre-Aging on the Hardness and Formability of a Thread Rolled 6056 Aluminum Alloy after Conventional Extrusion and Artificial Aging
by Lisa Winter, Ralph Jörg Hellmig, Kristin Hockauf and Thomas Lampke
J. Manuf. Mater. Process. 2021, 5(4), 116; https://doi.org/10.3390/jmmp5040116 - 29 Oct 2021
Viewed by 2593
Abstract
For the production of aluminum screws, an effective thermomechanical treatment is necessary for enabling high strength combined with good formability. In this study, the influence of pre-aging as initial heat treatment prior to following processing steps was investigated for the precipitation hardenable 6056 [...] Read more.
For the production of aluminum screws, an effective thermomechanical treatment is necessary for enabling high strength combined with good formability. In this study, the influence of pre-aging as initial heat treatment prior to following processing steps was investigated for the precipitation hardenable 6056 aluminum alloy. The short-term low temperature pre-aged condition was compared to a naturally aged one representing storage time in manufacturing. As reference, a solution-annealed condition was used. After these initial heat treatments, conventional extrusion and artificial aging followed prior to final thread rolling. The distribution of strain introduced by these forming processes was numerically investigated using finite element simulation. The initial heat treatment had a significant influence on the mechanical properties achievable after the complete thermomechanical processing route. After extrusion and artificial aging, the highest hardness was achieved by the pre-aged condition. Despite its high initial hardness, this condition exhibited the best formability indicated by well-formed threads combined with the highest hardness achieved after thread rolling. Therefore, pre-aging seems to be an advantageous heat treatment for integration in the manufacturing process of screws due to its beneficial effect on the mechanical properties. Full article
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<p>Finite element simulation of the (<b>a</b>) strain distribution after extrusion (70% area reduction) and (<b>b</b>) using these results for early stage thread rolling process. The strain introduced by extrusion is highest close to the outer surface and decreases with increasing distance to the surface.</p>
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<p>Finite element simulation of the strain distribution after thread rolling: (<b>a</b>) 3d view and (<b>b</b>) cut through area. The area at the thread root shows the highest introduced strain, whereas the strain introduced is lowest at the thread tip.</p>
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<p>Vickers hardness as a function of the artificial aging time dependent on the processing route. The first and second hardness peak for the investigated maximum aging time is marked for each condition by a larger symbol. By pre-aging prior to linear extrusion, the highest hardness is achieved, when compared to the other processing routes.</p>
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<p>Vickers Hardness across half of the wire section measured for the three different processing routes dependent on the artificial aging time prior to thread rolling as a function of the surface distance: initial heat treatment condition (<b>a</b>) solution-annealed, (<b>b</b>) naturally aged and (<b>c</b>) pre-aged. For all processing routes and artificial aging times, the hardness decreases with the increasing distance from the surface.</p>
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<p>Vickers Hardness achieved for the three different processing routes dependent on the artificial aging time prior to and after thread rolling: (<b>a</b>) comparison between thread root and thread flank for each condition and (<b>b</b>) percentage increase in hardness by thread rolling. The highest hardness and percentage increase after thread rolling is achieved by processing route C.</p>
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<p>Distribution of Martens hardness over the metallographically polished longitudinal section of the differently processed threaded parts after thread rolling. Schematic contours of thread teeth marked with dashed line in pink. Processing route and initial heat treatment: (<b>a</b>,<b>b</b>) processing route A (initially solution-annealed), (<b>c</b>,<b>d</b>) processing route B (initially naturally aged), (<b>e</b>,<b>f</b>) processing route C (initially pre-aged). Artificial aging time: (<b>a</b>–<b>c</b>) local hardness maximum and (<b>d</b>–<b>f</b>) global peak-hardness achieved. In general, the hardness of the thread root is significantly higher than of the thread flank. The highest overall hardness is achieved by processing route C (pre-aging as initial heat treatment).</p>
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<p>Stereo micrographs of the different processed and thread rolled parts. Processing route and initial heat treatment: (<b>a</b>,<b>b</b>) processing route A (initially solution-annealed), (<b>c</b>,<b>d</b>) processing route B (initially naturally aged), (<b>e</b>,<b>f</b>) processing route C (initially pre-aged). Artificial aging time: (<b>a</b>–<b>c</b>) local hardness maximum and (<b>d</b>–<b>f</b>) global peak-hardness achieved. Independent of the processing route, for all threaded parts, the threads are not fully formed and the closing fold near the top of the teeth is still open.</p>
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<p>Stereo micrographs of the different processed and thread rolled parts. Processing route and initial heat treatment: (<b>a</b>,<b>b</b>) processing route A (initially solution-annealed), (<b>c</b>,<b>d</b>) processing route B (initially naturally aged), (<b>e</b>,<b>f</b>) processing route C (initially pre-aged). Artificial aging time: (<b>a</b>–<b>c</b>) local hardness maximum and (<b>d</b>–<b>f</b>) global peak-hardness achieved. All thread rolled studs show scaling at the thread root, but this effect is significantly less pronounced for the studs processed by route C, when compared to the other processing routes.</p>
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<p>Optical micrograph of a longitudinal section of a threaded part processed by route A. The thread teeth are not fully formed and as a result, the closing fold at the tip of the tooth is clearly visible and has a crack-like appearance. Further, the thread root exhibits distinct scaling.</p>
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21 pages, 6504 KiB  
Article
Filament Development for Laser Assisted FFF 3D Printing
by Gabriel Borg, Szabolcs Kiss and Arif Rochman
J. Manuf. Mater. Process. 2021, 5(4), 115; https://doi.org/10.3390/jmmp5040115 - 29 Oct 2021
Cited by 4 | Viewed by 5432
Abstract
The aim of this paper was to develop filaments which can be used for laser assisted fused filament fabrication (FFF) 3D printing in order to increase the inter-layer bonding strength of the printed part. The filaments were developed from the most commonly used [...] Read more.
The aim of this paper was to develop filaments which can be used for laser assisted fused filament fabrication (FFF) 3D printing in order to increase the inter-layer bonding strength of the printed part. The filaments were developed from the most commonly used filament materials, acrylonitrile butadiene styrene (ABS) and polylactic acid (PLA) with the addition of different polymer additives. After performing near infrared (NIR) absorption tests, graphite was selected for further development as it possesses excellent NIR absorption capabilities whilst resulting in consistent filaments’ diameter and being economically viable. A conventional FFF 3D printer was initially used to test the printability of the developed filaments. Afterwards, a fiber couple laser diode was integrated within the printing head to heat up the previously extruded layer. The produced filaments were used to 3D print specimens for shear and tensile testing. With the laser heating, an increase of 14.5% in the elastic modulus and an increase of 27.8% in the tensile strength of the printed parts were noticed. This showed that adding additives into filament materials for localized laser heating is an effective method of increasing the inter-layer bonding, and therefore, the overall strength and durability of FFF 3D printed parts. Full article
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<p>FFF printing using pre-deposition laser heating [<a href="#B7-jmmp-05-00115" class="html-bibr">7</a>].</p>
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<p>Filament Maker—Composer 450 [<a href="#B17-jmmp-05-00115" class="html-bibr">17</a>].</p>
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<p>Filament development of PLA with additives.</p>
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<p>Filament development of ABS with additives.</p>
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<p>DMA result of PLA based filaments.</p>
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<p>DMA results of ABS based Filaments.</p>
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<p>DMA results of ABS and ABS 2% graphite filaments.</p>
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<p>DSC curve of PLA + 2% graphite filament.</p>
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<p>Light transmission of PLA filaments with different additives.</p>
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<p>Light transmission of ABS filaments with different additives.</p>
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<p>Parts printed with ABS + 2% Graphite filament.</p>
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<p>ABS tensile specimen during printing (<b>a</b>) and printed PLA tensile specimen (<b>b</b>), both with 2% graphite and an infill of 80%.</p>
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<p>Setup for the Laser Assisted FFF 3D Printer.</p>
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<p>CAD model of lap shear specimen.</p>
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<p>Shear specimens printed using PLA + 2% graphite.</p>
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<p>Fixed position of laser heating source relative to the nozzle.</p>
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<p>Laser assisted FFF printed tensile specimen.</p>
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<p>Tensile tested specimen: (<b>a</b>) PLA and (<b>b</b>) ABS both with 2% graphite and infill of 80% printed using the PRUSA I3 MK3S printer without laser heating, and (<b>c</b>) PLA + 2% graphite printed using the Wanhoa Duplicator equipped with the laser diode.</p>
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14 pages, 9304 KiB  
Article
Effect of Autoclave Pressure and Temperature on Consolidation of Layers and Mechanical Properties of Additively Manufactured (FDM) Products with PLA
by Yousuf Pasha Shaik, Jens Schuster, Aarif Shaik, Mustafa Mohammed and Harshavardhan Reddy Katherapalli
J. Manuf. Mater. Process. 2021, 5(4), 114; https://doi.org/10.3390/jmmp5040114 - 27 Oct 2021
Cited by 10 | Viewed by 4314
Abstract
In additive manufacturing technologies, fused deposition modelling (FDM) is continuing its advancement from rapid prototyping to rapid manufacturing. However, effective usage of FDM is not performed due to the poor mechanical properties of the 3D-printed components. This drawback restricts their usage in many [...] Read more.
In additive manufacturing technologies, fused deposition modelling (FDM) is continuing its advancement from rapid prototyping to rapid manufacturing. However, effective usage of FDM is not performed due to the poor mechanical properties of the 3D-printed components. This drawback restricts their usage in many applications. Much research, such as reinforcing 3D-printed parts with fibers, changing printing parameters (infill density, infill concentration, extrusion temperature, nozzle diameter, layer thickness, raster angle, etc.) are aimed to increase the mechanical properties of 3D-printed parts. This research paper aims to investigate the effect of pressure and temperature on the mechanical properties and consolidation of layers of 3D-printed PLA (Polylactic Acid). Post-treatment was done using a customized autoclave. Autoclave has the capability to maintain 185 °C and 135 bar pressure. Three-dimensional-printed specimens were manufactured using the FDM process with two patterns. Later, the specimens were subjected to various post-treatment processes, then followed with testing and analysis of mechanical properties. Post-treatment process carried out by placing them in an autoclave at certain pressure and temperature conditions. To investigate the repeatability and tolerances, the test series includes a minimum of four to six test specimens. The results indicate that the concentric pattern yields the most desirable tensile, impact, and flexural strength due to the alignment of deposited rasters and better consolidation of layers with the loading direction. The pressure and temperature of the autoclave has a positive effect on the PLA samples, which helped them to reorganize the structure, hence strength properties were enhanced. The test results also compared with injection-molded samples for better understating. Full article
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<p>A diagrammatic representation showing the working of FDM/FFF 3D printing technology.</p>
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<p>Fabbmatic Mendelmax 1.5 FM Pro Desktop 3D Printer [<a href="#B11-jmmp-05-00114" class="html-bibr">11</a>].</p>
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<p>Autoclave setup in the laboratory.</p>
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<p>ISO 527 Type 1A sample dimensions.</p>
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<p>DIN EN ISO 75 sample dimensions.</p>
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<p>3D-printed samples.</p>
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<p>3D printing of DIN EN ISO 75 samples. (<b>A</b>-while printing, <b>B</b>-Printed Samples).</p>
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<p>Schematic representation of the single screw injection molding machine.</p>
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<p>3D-printed and injection-molded samples autoclave arrangement.</p>
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<p>3D-printed samples annealed in the oven.</p>
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<p>Oven at 60 °C and air pressure at 0 bar.</p>
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<p>The change in modulus and strength after autoclave temperature pressurization.</p>
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<p>Comparison between weight and tensile modulus of PLA 3D-printed samples before and after oven temperature treatment.</p>
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<p>Comparison between weights and flexural modulus of PLA 3D-printed samples before and after oven temperature treatment.</p>
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<p>Comparison between weights and impact strength of PLA 3D-printed samples before and after oven temperature treatment.</p>
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<p>Showing comparison between weights and tensile modulus of PLA 3D-printed samples before and after autoclave pressurization.</p>
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<p>Showing comparison between weights and flexural modulus of PLA 3D-printed samples before and after autoclave pressurization.</p>
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<p>Comparison between weights and impact strength of PLA 3D-printed samples before and after autoclave pressurization.</p>
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16 pages, 2560 KiB  
Article
Transfer and Optimisation of Injection Moulding Manufacture of Medical Devices Using Scientific Moulding Principles
by Aimee Fitzgerald, Paul McDonald, Declan Devine and Evert Fuenmayor
J. Manuf. Mater. Process. 2021, 5(4), 113; https://doi.org/10.3390/jmmp5040113 - 25 Oct 2021
Cited by 2 | Viewed by 4293
Abstract
Scientific moulding, also known as decoupled injection moulding, is a production methodology used to develop and determine robust moulding processes resilient to fluctuations caused by variation in temperature and viscosity. Scientific moulding relies on the meticulous collection of data from the manufacturing process, [...] Read more.
Scientific moulding, also known as decoupled injection moulding, is a production methodology used to develop and determine robust moulding processes resilient to fluctuations caused by variation in temperature and viscosity. Scientific moulding relies on the meticulous collection of data from the manufacturing process, especially inputs of time (fill, pack/hold), temperature (melt, barrel, tool), and pressure (injection, hold, etc.). This publication presents a use case where scientific moulding was used to enable the transfer and optimisation of an injection moulding process from an Arburg 221M injection moulding machine to an Arburg 375 V model. The part was an endovascular aneurysm repair dilator device where a polypropylene hub was moulded over a high-density polyethylene dilator insert. Upon transfer, multiple studies were carried out, including material rheology study during injection, gate freeze study, cavity balance of the moulding tool, and pressure loss analysis. A design of experiments was developed and carried out on the process with a variety of effects and responses. The developed process cycle time was compared to that achieved theoretically using mathematical modelling and the original process cycle time. The studies resulted in the identification of optimum parameters for injection speed, holding time, holding pressure, cooling time, and mould temperature. The process was verified by completing a 32-shot study and recording part weights and dimensional measurements to confirm repeatability and consistency of the process. The output from the study was a reduction in cycle time by 12.05 s from the original process. A cycle time of 47.28 s was theoretically calculated for the process, which is within 6.6% of the practical experiment results (44.15 s). Full article
(This article belongs to the Topic Modern Technologies and Manufacturing Systems)
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<p>CAD drawing of the dilator hub moulded component.</p>
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<p>Rheology study showing the viscosity of the material (PP)) versus the injection speed used for the manufacture of parts. Notice the viscosity plateau once the injection speed reaches 50 mm/s.</p>
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<p>Sample parts obtained by execution of pressure drop study. The injection volume was varied to allow for the filling of different stages (sprue, runners, gates, and full parts, respectively from top to bottom) on the injection moulding tool cavities.</p>
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<p>Gate seal study results presenting holding time versus part weight. The holding time and pressure were increased until the weight of the parts was stabilised.</p>
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<p>Thermal images taken of moulded parts immediately after the mould was opened using a FLIR thermal imaging camera. Cooling times were varied until the optimum time was achieved.</p>
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<p>Process capability analysis completed on tensile data to determine the Ppk and Cpk values for the process.</p>
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<p>Cycle time analysis illustrating differences in timings for each moulding stage between the original moulding process, the theoretically calculated cycle time, and the newly developed moulding process.</p>
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13 pages, 2426 KiB  
Article
3D Printing of Biomass–Fungi Composite Material: Effects of Mixture Composition on Print Quality
by Abhinav Bhardwaj, Al Mazedur Rahman, Xingjian Wei, Zhijian Pei, David Truong, Matt Lucht and Na Zou
J. Manuf. Mater. Process. 2021, 5(4), 112; https://doi.org/10.3390/jmmp5040112 - 18 Oct 2021
Cited by 29 | Viewed by 6643
Abstract
It is known that 3D printing can facilitate greater design flexibility in the printing of custom shapes for packaging and construction applications using biomass–fungi composite materials. The feasibility of this new method was demonstrated by a preliminary experiment, the results of which were [...] Read more.
It is known that 3D printing can facilitate greater design flexibility in the printing of custom shapes for packaging and construction applications using biomass–fungi composite materials. The feasibility of this new method was demonstrated by a preliminary experiment, the results of which were reported in a journal publication in 2020. As a follow-up, this paper reports on an experimental study on the relationship between the mixture composition (i.e., the psyllium husk powder content) and print quality using this new method. Four mixtures were prepared by varying the amounts of psyllium husk powder (in grams) added to 400 mL of water. The ratios (g/mL) of psyllium husk powder weight (wp) over volume of water (vw) for the mixtures were 0, 1:40, 2:40, and 3:40. Each mixture also contained 100 g of biomass–fungi material and 40 g of whole wheat flour. The print quality of the samples was evaluated based on the extrudability and shape stability. The results showed that mixtures without any psyllium husk powder were not extrudable. An increase in the ratio of psyllium husk powder to water from 1:40 to 2:40 resulted in improved print quality; however, when the psyllium husk powder to water ratio was increased to 3:40, the extrudability became worse. This phenomenon was explained by analyzing the rheological properties of the mixtures. Full article
(This article belongs to the Special Issue Anniversary Review and Feature Papers)
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<p>As-received biomass–fungi material in a filter patch bag.</p>
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<p>Experimental procedure.</p>
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<p>Biomass–fungi material after primary colonization: (<b>a</b>) primary colonized material in filter patch bag; (<b>b</b>) scanning electron microscopy (SEM) image of the surface of a sample after colonization. Scale bar is 20 µm.</p>
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<p>Material-extrusion 3D printer: (<b>a</b>) Delta WASP 2040 printer; (<b>b</b>) extruder assembly, including screw extruder and casing with a square cross-section measuring 6 × 6 mm.</p>
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<p>Printed samples used for assessing print quality: (<b>a</b>) extrudability sample; (<b>b</b>) shape stability sample.</p>
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<p>Apparatus used for rheological characterization.</p>
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<p>Printing results for mixture A: (<b>a</b>) only water from the biomass–fungi mixture was deposited during the printing process; (<b>b</b>) non-extrudable, dry biomass–fungi mixture puck left behind.</p>
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<p>Printed samples using three mixtures with different levels of psyllium husk powder: (<b>a</b>) mixture B (wp/vw = 1:40); (<b>b</b>) mixture C (wp/vw = 2:40); (<b>c</b>) mixture D (wp/vw = 3:40).</p>
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<p>Height changes in layer 1 after depositing layer 2.</p>
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<p>Effects of psyllium husk powder content on the rheological behavior of the biomass–fungi mixtures.</p>
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<p>Relationships between elastic modulus (G′) and angular frequency for four biomass–fungi mixtures.</p>
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<p>Relationships between the loss modulus (G″) and angular frequency for four biomass–fungi mixtures.</p>
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<p>Loss tangent values for the mixtures.</p>
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26 pages, 12372 KiB  
Article
Towards the Determination of Machining Allowances and Surface Roughness of 3D-Printed Parts Subjected to Abrasive Flow Machining
by Mykhailo Samoilenko, Greg Lanik and Vladimir Brailovski
J. Manuf. Mater. Process. 2021, 5(4), 111; https://doi.org/10.3390/jmmp5040111 - 17 Oct 2021
Cited by 4 | Viewed by 3083
Abstract
Abrasive flow machining (AFM) is considered as one of the best-suited techniques for surface finishing of laser powder bed fused (LPBF) parts. In order to determine the AFM-related allowances to be applied during the design of LPBF parts, a numerical tool allowing to [...] Read more.
Abrasive flow machining (AFM) is considered as one of the best-suited techniques for surface finishing of laser powder bed fused (LPBF) parts. In order to determine the AFM-related allowances to be applied during the design of LPBF parts, a numerical tool allowing to predict the material removal and the surface roughness of these parts as a function of the AFM conditions is developed. This numerical tool is based on the use of a simplified viscoelastic non-Newtonian medium flow model and calibrated using specially designed artifacts containing four planar surfaces with different surface roughnesses to account for the build orientation dependence of the surface finish of LPBF parts. The model calibration allows the determination of the abrasive medium-polished part slip coefficient, the fluid relaxation time and the abrading (Preston) coefficient, as well as of the surface roughness evolution as a function of the material removal. For model validation, LPBF parts printed from the same material as the calibration artifacts, but having a relatively complex tubular geometry, were polished using the same abrasive medium. The average discrepancy between the calculated and experimental material removal and surface roughness values did not exceed 25%, which is deemed acceptable for real-case applications. A practical application of the numerical tool developed was demonstrated using the predicted AFM allowances for the generation of a compensated computer-aided design (CAD) model of the part to be printed. Full article
(This article belongs to the Special Issue Advanced Surface Finishing Processes)
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Graphical abstract

Graphical abstract
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<p>Shear and normal stresses acting on the viscoelastic element [taken from [<a href="#B27-jmmp-05-00111" class="html-bibr">27</a>]].</p>
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<p>Parts used for the model development: (<b>a</b>) V-Shape (calibration artifact); (<b>b</b>) S-shape (validation specimen); arrows indicate the build directions for the (<b>a</b>) V-shape artifact, and (<b>b</b>) top and bottom halves of the S-shape specimen.</p>
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<p>AFM setups: (<b>a</b>) V-shape laboratory setup; (<b>b</b>) S-shape industrial setup.</p>
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<p>V-shape artifact, <math display="inline"><semantics> <mrow> <mi>M</mi> <mi>R</mi> </mrow> </semantics></math> measurements: (<b>a</b>) Reference plane definition; (<b>b</b>) Void (<math display="inline"><semantics> <mrow> <msub> <mi>V</mi> <mrow> <mi>void</mi> </mrow> </msub> </mrow> </semantics></math>) and solid (<math display="inline"><semantics> <mrow> <msub> <mi>V</mi> <mi mathvariant="normal">s</mi> </msub> </mrow> </semantics></math>) volumes definition.</p>
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<p>S-shape, STL alignment: (<b>a</b>) alignment procedure; (<b>b</b>) STL<sub>AFM</sub> to STL<sub>initial</sub> result.</p>
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<p>V-shape, <math display="inline"><semantics> <mrow> <mi>R</mi> <mi>a</mi> </mrow> </semantics></math> measurements: (<b>a</b>) segments studied on each of the surfaces A, B, C and D; (<b>b</b>) cropped 8 × 8 mm segment with measuring lines.</p>
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<p>S-shape, <math display="inline"><semantics> <mrow> <mi>R</mi> <mi>a</mi> </mrow> </semantics></math> measurements (polishing sequence): (<b>a</b>) setup and ROIs; (<b>b</b>) segment studied.</p>
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<p>S-shape, <math display="inline"><semantics> <mrow> <mi>R</mi> <mi>a</mi> </mrow> </semantics></math> measurements (initial/final): (<b>a</b>) setup and ROI; (<b>b</b>) segment studied.</p>
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<p>CFD simulation setups: (<b>a</b>) V-shape; (<b>b</b>) S-shape.</p>
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<p>The MR model development workflow: (1) calibration using V-shape artifacts: (<b>a</b>) pre-polished, (<b>b</b>) as-built; and (2) validation using S-shape specimens.</p>
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<p>LV-60B (<math display="inline"><semantics> <mrow> <msup> <mi>η</mi> <mo>*</mo> </msup> </mrow> </semantics></math><span class="html-italic">,</span> <math display="inline"><semantics> <mrow> <mi>G</mi> <mo>′</mo> </mrow> </semantics></math><span class="html-italic">,</span> <math display="inline"><semantics> <mrow> <mi>G</mi> <mo>″</mo> </mrow> </semantics></math>), double-log scale; arrow indicates a first approximation of the relaxation time (0.121 s).</p>
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<p><math display="inline"><semantics> <mrow> <mi>M</mi> <mi>R</mi> <mfenced> <mi>t</mi> </mfenced> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>d</mi> <mi>M</mi> <mi>R</mi> <mo>/</mo> <mi>d</mi> <mi>t</mi> <mfenced> <mi>t</mi> </mfenced> </mrow> </semantics></math> for the V-shape artifacts: (a) pre-polished: (a.1) <math display="inline"><semantics> <mrow> <mi>M</mi> <mi>R</mi> <mfenced> <mi>t</mi> </mfenced> </mrow> </semantics></math>; (a.2) <math display="inline"><semantics> <mrow> <mi>d</mi> <mi>M</mi> <mi>R</mi> <mo>/</mo> <mi>d</mi> <mi>t</mi> <mfenced> <mi>t</mi> </mfenced> </mrow> </semantics></math>; (b) As-Built: (b.1) <math display="inline"><semantics> <mrow> <mi>M</mi> <mi>R</mi> <mfenced> <mi>t</mi> </mfenced> </mrow> </semantics></math>; (b.2) <math display="inline"><semantics> <mrow> <mi>d</mi> <mi>M</mi> <mi>R</mi> <mo>/</mo> <mi>d</mi> <mi>t</mi> <mfenced> <mi>t</mi> </mfenced> </mrow> </semantics></math> (average values).</p>
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<p>V-shape artifact <math display="inline"><semantics> <mrow> <mi>M</mi> <mi>R</mi> </mrow> </semantics></math> results (3D microscope): (<b>a</b>) pre-polished; (<b>b</b>) as-built.</p>
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<p>Average <math display="inline"><semantics> <mrow> <mi>M</mi> <mi>R</mi> <mfenced> <mi>t</mi> </mfenced> </mrow> </semantics></math> on surfaces A, B, C, D of the (<b>a</b>) pre-polished and (<b>b</b>) as-built V-shape artifacts (average values).</p>
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<p>Pre-polished V-shape artifact after 950 AFM passes: (<b>a</b>) experimental <math display="inline"><semantics> <mrow> <mi>M</mi> <msub> <mi>R</mi> <mi mathvariant="normal">t</mi> </msub> </mrow> </semantics></math> (<math display="inline"><semantics> <mrow> <mi>M</mi> <msub> <mi>R</mi> <mrow> <mi mathvariant="normal">t</mi> <mo>,</mo> <mi>exp</mi> </mrow> </msub> </mrow> </semantics></math>); (<b>b</b>) calculated <math display="inline"><semantics> <mrow> <mi>M</mi> <msub> <mi>R</mi> <mi mathvariant="normal">t</mi> </msub> </mrow> </semantics></math> (<math display="inline"><semantics> <mrow> <mi>M</mi> <msub> <mi>R</mi> <mrow> <mi mathvariant="normal">t</mi> <mo>,</mo> <mi>mod</mi> </mrow> </msub> </mrow> </semantics></math>); (<b>c</b>) error: <math display="inline"><semantics> <mrow> <mi>M</mi> <msub> <mi>R</mi> <mrow> <mi mathvariant="normal">t</mi> <mo>,</mo> <mi>exp</mi> </mrow> </msub> </mrow> </semantics></math> vs. <math display="inline"><semantics> <mrow> <mi>M</mi> <msub> <mi>R</mi> <mrow> <mi mathvariant="normal">t</mi> <mo>,</mo> <mi>mod</mi> </mrow> </msub> </mrow> </semantics></math>); (<b>d</b>) definition of the optimal <math display="inline"><semantics> <mi>τ</mi> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi>K</mi> <mn>1</mn> </msub> </mrow> </semantics></math> (maximum <math display="inline"><semantics> <mrow> <msup> <mi>R</mi> <mn>2</mn> </msup> </mrow> </semantics></math>).</p>
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<p>Pre-polished V-shape artifact: <math display="inline"><semantics> <mrow> <mi>M</mi> <msub> <mi>R</mi> <mrow> <mi>exp</mi> </mrow> </msub> <mo> </mo> </mrow> </semantics></math> vs. <math display="inline"><semantics> <mrow> <mi>M</mi> <msub> <mi>R</mi> <mrow> <mi>model</mi> </mrow> </msub> </mrow> </semantics></math> comparison for surfaces B, D, A and C (average values).</p>
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<p>Pre-polished V-shape artifact: <math display="inline"><semantics> <mrow> <mi>M</mi> <mi>R</mi> </mrow> </semantics></math> global measurements using (<b>a</b>) scales, (<b>b</b>) 3D microscope, (<b>c</b>) MR model (average values).</p>
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<p>As-built V-shape artifact: (<b>a</b>) <math display="inline"><semantics> <mrow> <mi>R</mi> <msub> <mi>a</mi> <mn>0</mn> </msub> <mfenced> <mi>α</mi> </mfenced> </mrow> </semantics></math>; (<b>b</b>) <math display="inline"><semantics> <mrow> <mi>R</mi> <mi>a</mi> <mfenced> <mrow> <mi>R</mi> <msub> <mi>a</mi> <mn>0</mn> </msub> <mo>,</mo> <mi>M</mi> <msub> <mi>R</mi> <mi mathvariant="normal">t</mi> </msub> </mrow> </mfenced> </mrow> </semantics></math><span class="html-italic">,</span> where points correspond to experimental measurements and dotted lines, to the best-fit curves.</p>
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<p>S-shape specimens detailed AFM analysis as a function of polishing time.</p>
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<p>S-shape <math display="inline"><semantics> <mrow> <mi>M</mi> <msub> <mi>R</mi> <mi mathvariant="normal">t</mi> </msub> </mrow> </semantics></math> fields after 26 AFM passes: (<b>a</b>) experiment; (<b>b</b>) modelling, (<b>c</b>) experiment vs. modelling error.</p>
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<p>S-shape specimen: MR global measurements using (<b>a</b>) scales, (<b>b</b>) 3D microscope, (<b>c</b>) MR model (average values).</p>
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<p>S-shape: (<b>a</b>) initial roughness, <math display="inline"><semantics> <mrow> <mi>R</mi> <msub> <mi>a</mi> <mn>0</mn> </msub> <mfenced> <mi>α</mi> </mfenced> </mrow> </semantics></math>; (<b>b</b>) roughness evolution, <math display="inline"><semantics> <mrow> <mi>R</mi> <mi>a</mi> <mfenced> <mi>t</mi> </mfenced> </mrow> </semantics></math>: experimental (Exp) vs. modelling (Mod).</p>
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<p>S-shape specimen: <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mrow> <mi>slip</mi> </mrow> </msub> </mrow> </semantics></math> vs. <math display="inline"><semantics> <mrow> <mi>R</mi> <mi>a</mi> </mrow> </semantics></math> (average values).</p>
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<p>Compensated 3D CAD model generation.</p>
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<p>MATLAB: V-Shape Pre-Polished <math display="inline"><semantics> <mrow> <mi>M</mi> <msub> <mi>R</mi> <mi mathvariant="normal">t</mi> </msub> </mrow> </semantics></math>: (<b>a</b>) 3D microscope point cloud (6 285 414 points); (<b>b</b>) CFD point cloud assignment (11 616 points).</p>
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<p>V-Shape Pre-Polished fields: (<b>a</b>) Velocity (<math display="inline"><semantics> <mi>v</mi> </semantics></math>), m/s; (<b>b</b>) Viscoelastic component (<math display="inline"><semantics> <mover accent="true"> <mi>χ</mi> <mo>˙</mo> </mover> </semantics></math>), s<sup>−1</sup>; (<b>c</b>) Normal viscosity (<math display="inline"><semantics> <mi>μ</mi> </semantics></math>), Pa·s; (<b>d</b>) Normal stress difference (<math display="inline"><semantics> <mrow> <msub> <mi>N</mi> <mn>1</mn> </msub> </mrow> </semantics></math>), Pa.</p>
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<p>V-Shape As-Built: <math display="inline"><semantics> <mrow> <mi>R</mi> <mi>a</mi> <mfenced> <mi>t</mi> </mfenced> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>M</mi> <msub> <mi>R</mi> <mi mathvariant="normal">t</mi> </msub> <mfenced> <mi>t</mi> </mfenced> </mrow> </semantics></math> [average values].</p>
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<p>S-Shape, compensated 3D CAD generation.</p>
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