Additive Manufacturing of Machine Components

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Advanced Manufacturing".

Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 11922

Special Issue Editors


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Guest Editor
Department of Mechanical Engineering, Indian Institute of Technology Jammu, Jammu, India
Interests: additive manufacturing; laser materials processing; laser shock peening; laser annealing; wire arc additive manufacturing
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Guest Editor
HiLASE Centre, Institute of Physics, Czech Academy of Sciences, Za Radnicí 828, 25241 Dolní Brežany, Czech Republic
Interests: laser materials processing; surface engineering; laser shock peening; laser annealing; additive manufacturing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Over the years, additive manufacturing (AM) has proven to be the most sought-after processing technique for fabricating metallic alloys due to its capability to fabricate components with high dimensional accuracy. The layer-by-layer deposition adopted during AM provides distinct advantages such as the freedom to produce parts with intricate geometries, reduced material wastage and high production flexibility. Recently, AM has also been explored for fabricating standalone machine components by taking advantage of the characteristic properties possessed by the individual materials. This opens avenues to explore new additively manufactured components with varying properties for site-specific performance. In the quest to increase the realm of machine components that can be processed using AM and employed for different applications with required properties, some possibilities that could be considered are as follows:

  1. Solid free-form fabrication of machine components can be performed using any additive manufacturing technique to design new components and further evaluate their performance.
  2. Process parameters for commercial parts fabrication can be optimized to minimize defects such as solidification cracks and porosity, while residual stress can be evaluated to establish its effect on microstructure evolution and mechanical properties.
  3. Microstructure engineering during AM can be improved with the help of post-processing techniques to achieve the required design targets for enhanced performance

This Special Issue focuses on the latest progress in the field of additively manufactured machine components that are intended for new component design (for or using AM), process optimization for conventional/newly designed components, and microstructure engineering through additive manufacturing (coupled with post-processing routes) using experimental and/or computational techniques. Original contributions related to the above-mentioned aspects are welcome in the form of short-communications, full-length articles, and reviews.

Dr. Shiva Sekar
Dr. Sunil Pathak
Guest Editors

Manuscript Submission Information

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Keywords

  • machine components using AM
  • near net shape machine components
  • mechanical and functional properties
  • process optimization
  • residual stress
  • cracking
  • porosity
  • material characterization
  • phase transformation

Published Papers (6 papers)

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Research

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18 pages, 8917 KiB  
Article
A Deep Learning Approach to Classify and Detect Defects in the Components Manufactured by Laser Directed Energy Deposition Process
by Deepika B. Patil, Akriti Nigam, Subrajeet Mohapatra and Sagar Nikam
Machines 2023, 11(9), 854; https://doi.org/10.3390/machines11090854 - 25 Aug 2023
Cited by 2 | Viewed by 1024
Abstract
This paper presents a deep learning approach to identify and classify various defects in the laser-directed energy manufactured components. It mainly focuses on the Convolutional Neural Network (CNN) architectures, such as VGG16, AlexNet, GoogLeNet and ResNet to perform the automated classification of defects. [...] Read more.
This paper presents a deep learning approach to identify and classify various defects in the laser-directed energy manufactured components. It mainly focuses on the Convolutional Neural Network (CNN) architectures, such as VGG16, AlexNet, GoogLeNet and ResNet to perform the automated classification of defects. The main objectives of this research are to manufacture components using the laser-directed energy deposition process, prepare a dataset of horizontal wall structure, vertical wall structure and cuboid structure with three defective classes such as voids, flash formation, and rough textures, and one non-defective class, use this dataset with a deep learning algorithm to classify the defect and use the efficient algorithm to detect defects. The next objective is to compare the performance parameters of VGG16, AlexNet, GoogLeNet and ResNet used for classifying defects. It has been observed that the best results were obtained when the VGG16 architecture was applied to an augmented dataset. With augmentation, the VGG16 architecture gave a test accuracy of 94.7% and a precision of 80.0%. The recall value is 89.3% and an F1-Score is 89.5%. The VGG16 architecture with augmentation is highly reliable for automating the defect detection process and classifying defects in the laser additive manufactured components. Full article
(This article belongs to the Special Issue Additive Manufacturing of Machine Components)
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15 pages, 4673 KiB  
Article
Thin-Walled Commercially Pure Titanium Structures: Laser Powder Bed Fusion Process Parameter Optimization
by Fatma Nur Depboylu, Evren Yasa, Ozgur Poyraz and Feza Korkusuz
Machines 2023, 11(2), 272; https://doi.org/10.3390/machines11020272 - 11 Feb 2023
Cited by 1 | Viewed by 1790
Abstract
Laser powder bed fusion (L-PBF) process parameters can be changeable depending on the part geometry due to thermal conductivity differences. The number of studies on the process parameter development for commercial pure titanium (Cp-Ti) with the L-PBF process is also quite limited in [...] Read more.
Laser powder bed fusion (L-PBF) process parameters can be changeable depending on the part geometry due to thermal conductivity differences. The number of studies on the process parameter development for commercial pure titanium (Cp-Ti) with the L-PBF process is also quite limited in the literature. The aim of this study is to present a comprehensive process development for the production of Cp-Ti bulk and thin structures with the L-PBF technology. In the first phase, the right process parameters, including scan speed, laser power, hatch distance, and layer thickness, were identified with prismatic specimens with thin walls so that the obtained parameters could be used for both bulky sections and thin features such as lattice structures. The process parameters were varied to change the volumetric energy density from 19 to 208 J/mm3 among 80 different parameter sets. Parameter sets having a Volumetric Energy Density (VED) value between 32 J/mm3 and 47 J/mm3 gave almost fully dense Cp-Ti parts while the laser power was set to 200–250 W and the scan speed was used as 1000–1400 mm/s. Finally, Vickers hardness and tensile tests were applied to highly dense Cp-Ti parts. This study involving investigating the effect of process parameters on a wide range demonstrated that L-PBF is a favorable manufacturing technology for Cp-Ti parts with almost full density and good mechanical properties as well as good dimensional accuracy even on thin geometries. Moreover, the results show that combining parameters into a single one, i.e., VED, is not a proper way to optimize the process parameters since increasing laser power or decreasing the scan speed may alter the results, although VED is increased in both manners. Full article
(This article belongs to the Special Issue Additive Manufacturing of Machine Components)
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19 pages, 6699 KiB  
Article
Laser Directed Energy Deposition-Based Additive Manufacturing of Fe20Cr5.5AlY from Single Tracks to Bulk Structures: Statistical Analysis, Process Optimization, and Characterization
by Jinoop Arackal Narayanan, Farzaneh Kaji, Mark Zimny and Ehsan Toyserkani
Machines 2023, 11(1), 58; https://doi.org/10.3390/machines11010058 - 04 Jan 2023
Cited by 2 | Viewed by 3226
Abstract
Laser directed energy deposition (LDED) can be deployed for depositing high-performance materials for various engineering applications. Alumina-forming steel is a high-performance material that possesses excellent corrosion and oxidation resistance, finding application in the power generation sector. In the present work, LDED using powder [...] Read more.
Laser directed energy deposition (LDED) can be deployed for depositing high-performance materials for various engineering applications. Alumina-forming steel is a high-performance material that possesses excellent corrosion and oxidation resistance, finding application in the power generation sector. In the present work, LDED using powder feeding (LDED-PF) was used to deposit Fe20Cr5.5AlY alloy using single-track, multi-track, and multi-layer deposition on SS 316L substrate. Response surface methodology (RSM)-based optimization was used to optimize the single-track deposition. The relationship between the track geometry parameters and the build rate with the LDED-PF processing parameters was studied. Further, the nonlinear relationship among the major process parameters was developed and an analysis of variance (ANOVA) was utilized to find significant parameters. The multi-track deposition yielded densely clad layers with a columnar grain structure. The presence of complex oxide slag of Y, Al, and Zr on the clad layer was detected. A micro-hardness of 240–285 HV was observed in the clad layer, with a hardness of 1088–1276 HV at the slag layer. The multi-layered structures showed a relative density of 99.7% with columnar growth and an average microhardness of 242 HV. The study paves the way for the deposition of dense alumina-forming steel structures for building components for power generation applications. Full article
(This article belongs to the Special Issue Additive Manufacturing of Machine Components)
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30 pages, 11348 KiB  
Article
Bulk Fabrication of SS410 Material Using Cold Metal Transfer-Based Wire Arc Additive Manufacturing Process at Optimized Parameters: Microstructural and Property Evaluation
by Amritbir Singh, Tameshwer Nath, Satya Gowtam Dommeti and Shiva Sekar
Machines 2022, 10(12), 1136; https://doi.org/10.3390/machines10121136 - 29 Nov 2022
Cited by 5 | Viewed by 1704
Abstract
To make metallic parts for manufacturing industries, additive manufacturing (AM) has acquired considerable significance. However, most efforts have concentrated on powder-based techniques, and there remains a dearth of the experimental evidence on the mechanical characteristics and structural behavior of metallic elements produced using [...] Read more.
To make metallic parts for manufacturing industries, additive manufacturing (AM) has acquired considerable significance. However, most efforts have concentrated on powder-based techniques, and there remains a dearth of the experimental evidence on the mechanical characteristics and structural behavior of metallic elements produced using wire-and-arc additive manufacturing (WAAM). This article examined the optimal parameters to enable bulk fabrication of thick walls made with a SS410 wire. The objective was to assess the optimized variables utilizing response surface methodology (RSM), followed by the microstructural analysis and mechanical property evaluation. During optimization, the influence of wire feed speed, travel speed, and gas flow rate on bead width and height was determined. Further, the optimized variables resulted in the successful formation of thick walls. Secondly, the microstructural analysis mainly featured the martensite and delta ferrite, with the latter’s percentage increasing with build height. The maximum micro-hardness of 452 HV was obtained at the base of the wall. In addition, the remarkable increases in the standard deviation of micro-hardness represent the great extent of anisotropy in the thick wall. Moreover, the maximum UTS (803 ± 8 MPa) and YS (659 ± 10 MPa) are achieved for the OB sample, which is similar to conventional components. However, the current investigation’s percentage elongation of 5% (max) demands more study before the actual use of the WAAM manufactured SS410 material. Therefore, due to the significant degree of anisotropy and poor percentage elongation, the findings conclude that post-processing is required after bulk SS410 manufacturing. Full article
(This article belongs to the Special Issue Additive Manufacturing of Machine Components)
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20 pages, 4363 KiB  
Article
Shape Accuracy Improvement in Selective Laser-Melted Ti6Al4V Cylindrical Parts by Sliding Friction Diamond Burnishing
by Gyula Varga, Gergely Dezső and Ferenc Szigeti
Machines 2022, 10(10), 949; https://doi.org/10.3390/machines10100949 - 19 Oct 2022
Cited by 1 | Viewed by 1154
Abstract
Additively manufactured metallic parts usually need postprocessing in order to achieve required shape accuracy. Cylindrical test specimens were produced by selective laser melting from Ti6Al4V powder material with different processing parameters. The aim of postprocessing was modification of shape accuracy. Sliding friction diamond [...] Read more.
Additively manufactured metallic parts usually need postprocessing in order to achieve required shape accuracy. Cylindrical test specimens were produced by selective laser melting from Ti6Al4V powder material with different processing parameters. The aim of postprocessing was modification of shape accuracy. Sliding friction diamond burnishing was applied as the postprocessing method. A five-factor, two-level full factorial design of experiment was implemented with factors being infill laser power, infill laser scan speed, burnishing speed, feed and force. Improvement ratios of two roundness parameters were defined, calculated from experimental data, and studied by main effect and interaction analysis. It has been demonstrated that burnishing feed has the largest main effect to improvement in roundness total and cylindricity. Additionally, parameters of both selective laser melting and diamond burnishing appear in three largest interaction terms. Empirical functions were fit to measurement data. Results show that improvement in roundness parameters are strongly nonlinear functions of all factors. Full article
(This article belongs to the Special Issue Additive Manufacturing of Machine Components)
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Review

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22 pages, 5536 KiB  
Review
A Review of Additive Manufacturing of Soft Magnetic Materials in Electrical Machines
by Nicola Giannotta, Giada Sala, Claudio Bianchini and Ambra Torreggiani
Machines 2023, 11(7), 702; https://doi.org/10.3390/machines11070702 - 02 Jul 2023
Cited by 2 | Viewed by 1966
Abstract
This paper presents a review of the main advantages and challenges of Additive Manufacturing (AM) applied in the production of soft magnetic components for electrical machines. Firstly, a general introduction about additive manufacturing is made, considering all of its possibilities of application, then [...] Read more.
This paper presents a review of the main advantages and challenges of Additive Manufacturing (AM) applied in the production of soft magnetic components for electrical machines. Firstly, a general introduction about additive manufacturing is made, considering all of its possibilities of application, then the authors focused on the electrical machine application field, in particular the AM of soft ferromagnetic materials. The soft ferromagnetic materials are fundamental for the production of electrical machines, and currently, there are more and more requests for designed ad hoc geometries, which can be difficult to produce with conventional manufacturing technologies. With this purpose, AM can be used to produce the desired geometries. Full article
(This article belongs to the Special Issue Additive Manufacturing of Machine Components)
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