Review of internal and external surface finishing technologies for additively manufactured metallic alloys components and new frontiers

Demisse, Wondwosen; Xu, Jiajun; Rice, Lucas; Tyagi, Pawan

doi:10.1007/s40964-023-00412-z

Cited by 8 publications

(5 citation statements)

References 89 publications

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“…[6,[65][66][67] However, often in industrial and academic use simple two-electrode cells for ECP, omitting the RE, are deployed. [20,21,28,68,69] Among the distinguishing features of the ECP process are its contactless nature, use of electrical energy for accelerating the chemical reactions, and material removal irrespective of the hardness of the XCT Lattice [35,36,38] Areal measurement Non-contact method Optical profilometry Internal cavity, Lattice [19,48] Laser confocal microscopy Internal hole, lattice [13,20,46,49] Focus variation microscopy Internal hole [40,47] 2D/3D qualitative imaging Non-contact method Optical microscopy Internal hole [27] SEM Lattice [24,36,38,80,81,85] XCT Lattice [92] workpiece. [70] Electrochemical surface treatment methods can treat both internal and external surfaces in a complex structure, since fluid electrolytes can flow into internal parts and reach hidden surfaces.…”

Section: Electrochemical Polishing (Ecp)mentioning

confidence: 99%

On the Post‐Processing of Complex Additive Manufactured Metallic Parts: A Review

Pourrahimi,

Hof

2024

Adv Eng Mater

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Additive manufacturing (AM) is gaining more attention due to its capability to produce customized and complex geometries. However, one significant drawback of AM is the rough surface finish of the as‐built parts, necessitating post‐processing for achieving the desired surface quality that meets application requirements. Post‐processing of complex geometries, such as parts with internal holes, lattice structures, and free‐form surfaces, poses unique challenges compared to other components. This review classifies various post‐processing methods employed for complex AM parts, presenting the experimental conditions for each treatment alongside the resulting improvement in surface roughness as a success criterion. The post‐processing methods are categorized into four groups: electrochemical polishing (ECP), chemical polishing (CP), mechanical polishing, and hybrid methods. Notably, mechanical methods exhibit the highest roughness improvement at 69.9%, followed by ECP (59.9%), hybrid methods (47.4%), and CP (49.5%). Nevertheless, mechanical post‐processing techniques are less frequently utilized for lattice parts, making chemical or electrochemical methods more promising alternatives. In summary, all four categories of post‐processing methods can improve the internal surfaces quality of AM holes. While mechanical methods offer the most substantial roughness improvement overall, chemical and electrochemical methods show particular potential for addressing the challenges associated with complex geometries.This article is protected by copyright. All rights reserved.

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Section: Electrochemical Polishing (Ecp)mentioning

confidence: 99%

On the Post‐Processing of Complex Additive Manufactured Metallic Parts: A Review

Pourrahimi,

Hof

2024

Adv Eng Mater

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“…Additive manufacturing (AM) technologies are catalyzing an industrial revolution by impacting the innovation and manufacturing processes in critical fields such as the aerospace, biomedical, and automotive industries [1][2][3][4][5][6]. AM components can produced by utilizing a vast list of materials, including metals, polymers, and composites, with a high degree of geometric complexity [7,8]. AM is hence producing designs and functionalities that go beyond the imagination of innovators and technology leaders [9].…”

Section: Introductionmentioning

confidence: 99%

Surface Finishing and Coating Parameters Impact on Additively Manufactured Binder-Jetted Steel–Bronze Composites

Grizzle,

Elliott,

Klein

et al. 2024

Materials

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In this paper, electroless nickel plating is explored for the protection of binder-jetting-based additively manufactured (AM) composite materials. Electroless nickel plating was attempted on binder-jetted composites composed of stainless steel and bronze, resulting in differences in the physicochemical properties. We investigated the impact of surface finishing, plating solution chemistry, and plating parameters to attain a wide range of surface morphologies and roughness levels. We employed the Keyence microscope to quantitatively evaluate dramatically different surface properties before and after the coating of AM composites. Scanning electron microscopy revealed a wide range of microstructural properties in relation to each combination of surface finishing and coating parameters. We studied chempolishing, plasma cleaning, and organic cleaning as the surface preparation methods prior to coating. We found that surface preparation dictated the surface roughness. Taguchi statistical analysis was performed to investigate the relative strength of experimental factors and interconnectedness among process parameters to attain optimum coating qualities. The quantitative impacts of phosphorous level, temperature, surface preparation, and time factor on the roughness of the nickel-plated surface were 17.95%, 8.2%, 50.02%, and 13.21%, respectively. On the other hand, the quantitative impacts of phosphorous level, temperature, surface preparation, and time factor on the thickness of nickel plating were 35.12%, 41.40%, 3.87%, and 18.24%, respectively. The optimum combination of the factors’ level projected the lowest roughness of Ra at 7.76 µm. The optimum combination of the factors’ level projected the maximum achievable thickness of ~149 µm. This paper provides insights into coating process for overcoming the sensitivity of AM composites in hazardous application spaces via robust coating.

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“…There are several forms of additive manufacturing, such as binder-jetting-based metal additive manufacturing (BJAM). In this study, we focused on stainless-steel and bronze composite samples that were manufactured using the binder-jetted method [ 9 ]. Binder jetting is a 3D printing process that involves the deposition of an adhesive binding agent onto thin layers of powdered material.…”

Section: Introductionmentioning

confidence: 99%

“…Often, the operator adds an infiltrating substance to improve the mechanical properties of the parts. The infiltrate substance is usually bronze in the case of metal 3D prints [ 9 , 10 ]. The BJAM process has a significant scope of improvement with the application of ML and deep learning [ 11 , 12 ].…”

Section: Introductionmentioning

confidence: 99%

“…While BJAM and other additive manufacturing processes have been widely used for rapid prototyping [ 13 , 14 ], some of its constraints revolve around reliability and control [ 15 , 16 ]. Compared to subtractive manufacturing procedures, AM creates objects with poor surface smoothness [ 9 , 17 ]. As produced, surface quality has a negative effect on the tribological behavior of printed parts.…”

Section: Introductionmentioning

confidence: 99%

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Machine Learning-Enabled Quantitative Analysis of Optically Obscure Scratches on Nickel-Plated Additively Manufactured (AM) Samples

Mengesha,

Grizzle,

Demisse

et al. 2023

Materials

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Additively manufactured metal components often have rough and uneven surfaces, necessitating post-processing and surface polishing. Hardness is a critical characteristic that affects overall component properties, including wear. This study employed K-means unsupervised machine learning to explore the relationship between the relative surface hardness and scratch width of electroless nickel plating on additively manufactured composite components. The Taguchi design of experiment (TDOE) L9 orthogonal array facilitated experimentation with various factors and levels. Initially, a digital light microscope was used for 3D surface mapping and scratch width quantification. However, the microscope struggled with the reflections from the shiny Ni-plating and scatter from small scratches. To overcome this, a scanning electron microscope (SEM) generated grayscale images and 3D height maps of the scratched Ni-plating, thus enabling the precise characterization of scratch widths. Optical identification of the scratch regions and quantification were accomplished using Python code with a K-means machine-learning clustering algorithm. The TDOE yielded distinct Ni-plating hardness levels for the nine samples, while an increased scratch force showed a non-linear impact on scratch widths. The enhanced surface quality resulting from Ni coatings will have significant implications in various industrial applications, and it will play a pivotal role in future metal and alloy surface engineering.

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Review of internal and external surface finishing technologies for additively manufactured metallic alloys components and new frontiers

Cited by 8 publications

References 89 publications

On the Post‐Processing of Complex Additive Manufactured Metallic Parts: A Review

On the Post‐Processing of Complex Additive Manufactured Metallic Parts: A Review

Surface Finishing and Coating Parameters Impact on Additively Manufactured Binder-Jetted Steel–Bronze Composites

Machine Learning-Enabled Quantitative Analysis of Optically Obscure Scratches on Nickel-Plated Additively Manufactured (AM) Samples

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