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Design, Optimization, Simulation, and Defect Detection for Additive Manufacturing

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A special issue of Materials (ISSN 1996-1944). This special issue belongs to the section "Manufacturing Processes and Systems".

Deadline for manuscript submissions: closed (20 February 2024) | Viewed by 23099

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Dr. Jan Akmal

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Guest Editor

Department of Mechanical Engineering, School of Engineering, Aalto University, Espoo, Finland
Interests: additive manufacturing (AM); 3D printing; digital design; topology optimization; embedding; CAE; build-to-model

Dr. Mika Salmi

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Guest Editor

Department of Mechanical Engineering, Aalto University, 02150 Espoo, Finland
Interests: additive manufacturing (AM); 3D printing; design for additive manufacturing; processing materials with AM; medical applications
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Special Issue Information

Dear Colleagues,

Additive manufacturing (AM), colloquially known as 3D printing, is emerging into a general-purpose technology akin to dynamos and computers that power not only our industries, but also our way of living. Today, AM characterizes a group of seven technologies (ISO/ASTM 52900:2021) that deposit, fuse, dispense, bond, and cure a wide selection of feedstocks, composed of polymers, metals, ceramics, elastomers, and hybrid materials, on a layer-by-layer basis.

The layer-by-layer mechanism eliminates product-specific tooling, allowing for unprecedented geometric freedom. It enables economical lot-size-one and allows for mass customization and personalization in a single batch. Owing to these inherent general-purpose characteristics, the revenue generated by AM products and services has been increasing exponentially in the last decade (Wohlers Report 2022). The advent and proliferation of the additive process is triggering Industry 4.0 and is challenging practitioners and academics alike to establish and substantiate new applications, designs, materials, optimization methods, process simulation, data management, in and ex situ defect detection, and modes of creating end-use parts.

Contributing to the emerging stream of research and advances in AM technologies, the overarching mission of this Special Issue is to provide a leading publication channel for engineers, scientists, researchers, and practitioners in academia and virtually in any industry to document their latest achievements and to identify underlying issues and challenges for future investigations that may define, transcend, and steer the contemporary progress in AM technologies and its widespread adoption.

Dr. Jan Akmal
Dr. Mika Salmi
Guest Editors

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Keywords

design for additive manufacturing
optimizing for additive manufacturing

topology optimization
generative design
lattice optimization

defect detection and compensation for additive manufacturing
accuracy of AM parts
AM part identification
material modeling

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Published Papers (13 papers)

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16 pages, 5802 KiB

Open AccessArticle

Influence of Pre- and Post-Contouring Strategies to Downskin Sloped Surfaces in Laser Powder-Bed Fusion (L-PBF) Additive Manufacturing

by Nismath Valiyakath Vadakkan Habeeb, Rabiul Islam and Kevin Chou

Materials 2024, 17(11), 2639; https://doi.org/10.3390/ma17112639 - 30 May 2024

Viewed by 842

Abstract

Among various metal additive manufacturing (AM) technologies, L-PBF is known for fabricating intricate components. However, due to step edges and powder particle attachments, attaining a good surface finish is challenging, especially on downskin surfaces. Contour scanning has potential to improve surface quality because such scanning may dominate the surface formation of sloped features. This study evaluates the effects of pre- and post-contouring strategies on the sloped downskin surfaces fabricated using a commercial L-PBF system with Ti6Al4V powder. L-PBF parts printed at inclination angles 30°, 45° and 60° were investigated. A double-contouring approach with varying processing conditions was employed and surface characteristics were analyzed using data acquired by white light interferometry. The average surface roughness, S_a, surface skewness, S_sk, and percentage area of powder particles attached onto surfaces were statistically evaluated. The lowest S_a obtained for pre- and post-contoured samples is 14.08 µm and 18.88 µm, respectively. For both strategies, the combination of a low laser power and a high scan speed on the interface of downskin surface and underneath powder results in smoother surfaces. However, while comparing both strategies, pre-contouring gives better surface finish for samples built at similar processing conditions, with a difference of nearly 5 µm in S_a. Full article

(This article belongs to the Special Issue Design, Optimization, Simulation, and Defect Detection for Additive Manufacturing)

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20 pages, 6144 KiB

Open AccessArticle

In Situ Microstructure Modification Using a Layerwise Surface-Preheating Laser Scan of Ti-6Al-4V during Laser Powder Bed Fusion

by Ahmet Alptug Tanrikulu, Behzad Farhang, Aditya Ganesh-Ram, Hamidreza Hekmatjou, Sadman Hafiz Durlov and Amirhesam Amerinatanzi

Materials 2024, 17(8), 1929; https://doi.org/10.3390/ma17081929 - 22 Apr 2024

Cited by 1 | Viewed by 1108

Abstract

An innovative in situ thermal approach in the domain of LPBF for Ti-6Al-4V fabrication has been carried out with results directing towards an improved fatigue life without the need for post-processing. The thermal process involves an additional laser scan with different process parameters to preheat the selected regions of each layer of the powder bed prior to their full melting. This preheating step influences the cooling rate, which in turn affects surface characteristics and subsurface microstructure, both of which are directly correlated with fatigue properties. A thorough analysis has been conducted by comparing the preheated samples with reference samples with no preheating. Without any additional thermal processing, the preheated samples showed a significant improvement over their reference counterparts. The optimized preheated sample showed an improved prior β-grain distribution with a circular morphology and thicker α laths within the even finer prior β-grain boundaries. Also, an overall increment of the c/a ratio of the HCP α has been observed, which yielded lattice strain relaxation in the localized grain structure. Furthermore, a less-profound surface roughness was observed in the preheated sample. The obtained microstructure with all these factors delivered a 10% improvement in its fatigue life with better mechanical strength overall. Full article

(This article belongs to the Special Issue Design, Optimization, Simulation, and Defect Detection for Additive Manufacturing)

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21 pages, 16801 KiB

Open AccessArticle

Non-Conventional Wing Structure Design with Lattice Infilled through Design for Additive Manufacturing

by Numan Khan, Valerio Acanfora and Aniello Riccio

Materials 2024, 17(7), 1470; https://doi.org/10.3390/ma17071470 - 23 Mar 2024

Cited by 5 | Viewed by 2159

Abstract

Lightweight structures with a high stiffness-to-weight ratio always play a significant role in weight reduction in the aerospace sector. The exploration of non-conventional structures for aerospace applications has been a point of interest over the past few decades. The adaptation of lattice structure and additive manufacturing in the design can lead to improvement in mechanical properties and significant weight reduction. The practicality of the non-conventional wing structure with lattices infilled as a replacement for the conventional spar–ribs wing is determined through finite element analysis. The optimal lattice-infilled wing structures are obtained via an automated iterative method using the commercial implicit modeling tool nTop and an ANSYS workbench. Among five different types of optimized lattice-infilled structures, the Kelvin lattice structure is considered the best choice for current applications, with comparatively minimal wing-tip deflection, weight, and stress. Furthermore, the stress distribution dependency on the lattice-unit cell type and arrangement is also established. Conclusively, the lattice-infilled structures have shown an alternative innovative design approach for lightweight wing structures. Full article

(This article belongs to the Special Issue Design, Optimization, Simulation, and Defect Detection for Additive Manufacturing)

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20 pages, 4403 KiB

Open AccessArticle

Metal Laser-Based Powder Bed Fusion Process Development Using Optical Tomography

by Roy Björkstrand, Jan Akmal and Mika Salmi

Materials 2024, 17(7), 1461; https://doi.org/10.3390/ma17071461 - 22 Mar 2024

Viewed by 1255

Abstract

In this study, a set of 316 L stainless steel test specimens was additively manufactured by laser-based Powder Bed Fusion. The process parameters were varied for each specimen in terms of laser scan speed and laser power. The objective was to use a narrow band of parameters well inside the process window, demonstrating detailed parameter engineering for specialized additive manufacturing cases. The process variation was monitored using Optical Tomography to capture light emissions from the layer surfaces. Process emission values were stored in a statistical form. Micrographs were prepared and analyzed for defects using optical microscopy and image manipulation. The results of two data sources were compared to find correlations between lack of fusion, porosity, and layer-based energy emissions. A data comparison of Optical Tomography data and micrograph analyses shows that Optical Tomography can partially be used independently to develop new process parameters. The data show that the number of critical defects increases when the average Optical Tomography grey value passes a certain threshold. This finding can contribute to accelerating manufacturing parameter development and help meet the industrial need for agile component-specific parameter development. Full article

(This article belongs to the Special Issue Design, Optimization, Simulation, and Defect Detection for Additive Manufacturing)

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14 pages, 7841 KiB

Open AccessArticle

Micro-Scale Deformation Aspects of Additively Fabricated Stainless Steel 316L under Compression

by Abdulaziz Kurdi, Ahmed Degnah, Thamer Tabbakh, Husain Alnaser and Animesh Kumar Basak

Materials 2024, 17(2), 439; https://doi.org/10.3390/ma17020439 - 17 Jan 2024

Cited by 1 | Viewed by 1242

Abstract

The deformation aspects associated with the micro-mechanical properties of the powder laser bed fusion (P-LBF) additively manufactured stainless steel 316L were investigated in the present work. Toward that, micro-pillars were fabricated on different planes of the stainless steel 316L specimen with respect to build direction, and an in situ compression was carried out inside the chamber of the scanning electron microscope (SEM). The results were compared against the compositionally similar stainless steel 316L, which was fabricated by a conventional method, that is, casting. The post-deformed micro-pillars on the both materials were examined by electron microscopy. The P-LBF processed steel exhibits equiaxed as well as elongated grains of different orientation with the characteristics of the melt-pool type arrangements. In contrast, the cast alloy shows typical circular-type grains in the presence of micro-twins. The yield stress and ultimate compressive stress of P-LBF fabricated steel were about 431.02 ± 15.51 − 474.44 ± 23.49 MPa and 547.78 ± 29.58 − 682.59 ± 21.59 MPa, respectively. Whereas for the cast alloy, it was about 322.38 ± 19.78 MPa and 477.11 ± 25.31 MPa, respectively. Thus, the outcome of this study signifies that the AM-processed samples possess higher mechanical properties than conventionally processed alloy of similar composition. Irrespective of the processing method, both specimens exhibit ductile-type deformation, which is typical for metallic alloys. Full article

(This article belongs to the Special Issue Design, Optimization, Simulation, and Defect Detection for Additive Manufacturing)

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19 pages, 19698 KiB

Open AccessArticle

Machine Learning Algorithms for Predicting Mechanical Stiffness of Lattice Structure-Based Polymer Foam

by Mohammad Javad Hooshmand, Chowdhury Sakib-Uz-Zaman and Mohammad Abu Hasan Khondoker

Materials 2023, 16(22), 7173; https://doi.org/10.3390/ma16227173 - 15 Nov 2023

Cited by 5 | Viewed by 1716

Abstract

Polymer foams are extensively utilized because of their superior mechanical and energy-absorbing capabilities; however, foam materials of consistent geometry are difficult to produce because of their random microstructure and stochastic nature. Alternatively, lattice structures provide greater design freedom to achieve desired material properties by replicating mesoscale unit cells. Such complex lattice structures can only be manufactured effectively by additive manufacturing or 3D printing. The mechanical properties of lattice parts are greatly influenced by the lattice parameters that define the lattice geometries. To study the effect of lattice parameters on the mechanical stiffness of lattice parts, 360 lattice parts were designed by varying five lattice parameters, namely, lattice type, cell length along the X, Y, and Z axes, and cell wall thickness. Computational analyses were performed by applying the same loading condition on these lattice parts and recording corresponding strain deformations. To effectively capture the correlation between these lattice parameters and parts’ stiffness, five machine learning (ML) algorithms were compared. These are Linear Regression (LR), Polynomial Regression (PR), Decision Tree (DT), Random Forest (RF), and Artificial Neural Network (ANN). Using evaluation metrics such as mean squared error (MSE), root mean squared error (RMSE), and mean absolute error (MAE), all ML algorithms exhibited significantly low prediction errors during the training and testing phases; however, the Taylor diagram demonstrated that ANN surpassed other algorithms, with a correlation coefficient of 0.93. That finding was further supported by the relative error box plot and by comparing actual vs. predicted values plots. This study revealed the accurate prediction of the mechanical stiffness of lattice parts for the desired set of lattice parameters. Full article

(This article belongs to the Special Issue Design, Optimization, Simulation, and Defect Detection for Additive Manufacturing)

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13 pages, 8015 KiB

Open AccessArticle

Functionality and Mechanical Performance of Miniaturized Non-Assembly Pin-Joints Fabricated in Ti6Al4V by Laser Powder Bed Fusion

by Florian Gutmann, Klaus Hoschke, Georg Ganzenmüller and Stefan Hiermaier

Materials 2023, 16(21), 6992; https://doi.org/10.3390/ma16216992 - 31 Oct 2023

Viewed by 1101

Abstract

In this work, additively manufactured pin-joint specimens are analyzed for their mechanical performance and functionality. The functionality of a pin-joint is its ability to freely rotate. The specimens were produced using laser powder bed fusion technology with the titanium alloy Ti6Al4V. The pin-joints were manufactured using previously optimized process parameters to successfully print miniaturized joints with an angle to the build plate. The focus of this work lies in the influence of joint clearance, and therefore all specimens were manufactured with a variety of clearance values, from 0 µm up to 150 µm, in 10 µm steps. The functionality and performance were analyzed using torsion testing and tensile testing. Furthermore, a metallographic section was conducted to visually inspect the clearances of the additively manufactured pin-joints with different joint clearance values. The results of the torsion and tensile tests complement each other and emphasize a correlation between the joint clearance and the maximal particle size of the powder utilized for manufacturing and the mechanical behavior and functionality of the pin-joints. Non-assembly multibody pin-joints with good functionality were obtained reliably using a joint clearance of 90 µm or higher. Our findings show how and with which properties miniaturized pin-joints that can be integrated into lattice structures can be successfully manufactured on standard laser powder bed fusion machines. The results also indicate the potential and limitations of further miniaturization. Full article

(This article belongs to the Special Issue Design, Optimization, Simulation, and Defect Detection for Additive Manufacturing)

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17 pages, 8404 KiB

Open AccessArticle

Microstructure and Strength of Ti-6Al-4V Samples Additively Manufactured with TiC Heterogeneous Nucleation Site Particles

by Yoshimi Watanabe, Shintaro Yamada, Tadachika Chiba, Hisashi Sato, Seiji Miura, Kenshiro Abe and Tomotsugu Kato

Materials 2023, 16(17), 5974; https://doi.org/10.3390/ma16175974 - 31 Aug 2023

Cited by 3 | Viewed by 1768

Abstract

Our research aims to investigate the fabrication of additively manufactured (AMed) Ti-6Al-4V samples under reduced power with the addition of TiC heterogeneous nucleation site particles. For this aim, Ti-6Al-4V samples are fabricated with and without TiC heterogeneous nucleation site particles using an EOS M 290 machine under optimal parameters and reduced power conditions. The microstructure and tensile behavior of the produced samples were studied. In addition, a single-track test was performed to obtain a good understanding of the suppression of gas pores and balling formation with the addition of TiC heterogeneous nucleation site particles. It was found that the formation of gas pores and balling was suppressed with the addition of heterogeneous nucleation site particles within the metallic powder. Full article

(This article belongs to the Special Issue Design, Optimization, Simulation, and Defect Detection for Additive Manufacturing)

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20 pages, 7681 KiB

Open AccessArticle

Anisotropy in Additively Manufactured Concrete Specimens under Compressive Loading—Quantification of the Effects of Layer Height and Fiber Reinforcement

by Sahil Surehali, Avinaya Tripathi and Narayanan Neithalath

Materials 2023, 16(15), 5488; https://doi.org/10.3390/ma16155488 - 6 Aug 2023

Cited by 3 | Viewed by 2150

Abstract

This paper analyzes the effect of print layer heights and loading direction on the compressive response of plain and fiber-reinforced (steel or basalt fiber) 3D printed concrete. Slabs with three different layer heights (6, 13, and 20 mm) are printed, and extracted cubes are subjected to compression (i) along the direction of printing, (ii) along the direction of layer build-up, and (iii) perpendicular to the above two directions. Digital image correlation (DIC) is used as a non-contact means to acquire the strain profiles. While the 3D printed specimens show lower strengths, as compared to cast specimens, when tested in all three directions, this effect can be reduced through the use of fiber reinforcement. Peak stress and peak strain-based anisotropy coefficients, which are linearly related, are used to characterize and quantify the directional dependence of peak stress and strain. Interface-parallel cracking is found to be the major failure mechanism, and anisotropy coefficients increase with an increase in layer height, which is attributable to the increasing significance of interfacial defects. Thus, orienting the weaker interfaces appropriately, through changes in printing direction, or strengthening them through material modifications (such as fiber reinforcement) or process changes (lower layer height, enables attainment of near-isotropy in 3D printed concrete elements. Full article

(This article belongs to the Special Issue Design, Optimization, Simulation, and Defect Detection for Additive Manufacturing)

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17 pages, 4886 KiB

Open AccessArticle

Influence of Homogenization on Phase Transformations during Isothermal Aging of Inconel 718 Superalloys Fabricated by Additive Manufacturing and Suction Casting

by Yunhao Zhao and Wei Xiong

Materials 2023, 16(14), 4968; https://doi.org/10.3390/ma16144968 - 12 Jul 2023

Cited by 3 | Viewed by 1351

Abstract

The attainment of the desired strength of the Inconel 718 superalloy heavily relies on the isothermal aging process, which plays a critical role in achieving the anticipated hardening effect. Surprisingly, there remains a dearth of dedicated studies investigating the influence of homogenization on phase transformations during the isothermal aging process, leaving a gap in the knowledge required to guide the design of post-heat treatment strategies. Addressing this gap, our work investigates the impact of homogenization time on phase transformations during isothermal aging at 730 °C in Inconel 718 alloys produced via additive manufacturing (AM) and suction casting (SC) methods. Intriguingly, we observe contrasting behaviors in the particle size of γ″ and γ′ in aged samples, depending on the homogenization time and the alloy processing method. Specifically, in AM alloys, extended homogenization time leads to an increase in the particle size of γ″ and γ′, whereas the opposite trend is observed in SC alloys. Furthermore, despite undergoing the same heat treatment, the AM alloys exhibit smaller particle sizes but higher precipitate number densities compared to the SC alloys, resulting in superior hardness. Notably, pronounced grain refinement during aging is evident in 1 h homogenized SC samples under 1180 °C, warranting further investigations into the underlying mechanisms. This study elucidates the crucial role of homogenization in attaining the desired microstructure following subsequent aging processes. Moreover, it offers novel insights for developing post-heat treatment strategies for superalloys. Full article

(This article belongs to the Special Issue Design, Optimization, Simulation, and Defect Detection for Additive Manufacturing)

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26 pages, 31552 KiB

Open AccessArticle

Design Optimization of Additive Manufactured Edgeless Simple Cubic Lattice Structures under Compression

by Kwang-Min Park and Young-Sook Roh

Materials 2023, 16(7), 2870; https://doi.org/10.3390/ma16072870 - 4 Apr 2023

Cited by 3 | Viewed by 1896

Abstract

This study proposed an optimization framework and methodologies to design edgeless lattice structures featuring fillet and multipipe functions. Conventional lattice structures typically experience stress concentration at the sharp edges of strut joints, resulting in reduced mechanical performance and premature failure. The proposed approach aimed to improve the compression behavior of lattice structures by introducing edgeless features. Through finite element analysis, the optimized fillet edgeless simple cubic unit cell with a fillet radius to strut radius ratio of 0.753 showed a 12.1% improvement in yield stress and a 144% reduction in stress concentration. To validate the finite element analysis, experimental compressive tests were conducted, confirming that the introduction of edgeless functions improved the compressive strength of lattice structures manufactured through additive manufacturing. The optimized fillet edgeless simple cubic lattice structure exhibited the most effective improvement. This approach has promising potential for lattice structure applications. Full article

(This article belongs to the Special Issue Design, Optimization, Simulation, and Defect Detection for Additive Manufacturing)

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18 pages, 10085 KiB

Open AccessArticle

Thermomechanical Process Simulation and Experimental Verification for Laser Additive Manufacturing of Inconel^®718

by Muhammad Qasim Zafar, Jinnan Wang, Zhenlin Zhang, Chaochao Wu, Haiyan Zhao, Ghulam Hussain and Ninshu Ma

Materials 2023, 16(7), 2595; https://doi.org/10.3390/ma16072595 - 24 Mar 2023

Cited by 1 | Viewed by 2635

Abstract

Laser cladding has emerged as a promising technique for custom-built fabrications, remanufacturing, and repair of metallic components. However, frequent melting and solidification in the process cause inevitable residual stresses that often lead to geometric discrepancies and deterioration of the end product. The accurate physical interpretation of the powder consolidation process remains challenging. Thermomechanical process simulation has the potential to comprehend the layer-by-layer additive process and subsequent part-scale implications. Nevertheless, computational accuracy and efficacy have been serious concerns so far; therefore, a hybrid FEM scheme is adopted for efficient prediction of the temperature field, residual stress, and distortion in multilayer powder-fed laser cladding of Inconel^®718. A transient material deposition with powder material modeling is schematized to replicate the fabrication process. Moreover, simulation results for residual stress and distortion are verified with in-house experiments, where residual stress is measured with XRD (X-Ray Diffraction) and geometric distortion is evaluated with CMM (Coordinate Measuring Machine). A maximum tensile residual stress of 373 ± 5 MPa is found in the vicinity of the layer right in the middle of the substrate and predicted results are precisely validated with experiments. Similarly, a 0.68 ± 0.01 mm distortion is observed with numerical simulation and showed a precise agreement with experimental data for the same geometry and processing conditions. Conclusively, the implemented hybrid FEM approach demonstrated a robust and accurate prediction of transient temperature field, residual stresses, and geometric distortion in the multilayer laser cladding of Inconel^®718. Full article

(This article belongs to the Special Issue Design, Optimization, Simulation, and Defect Detection for Additive Manufacturing)

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Review

Jump to: Research

26 pages, 6460 KiB

Open AccessReview

Experimental, Computational, and Machine Learning Methods for Prediction of Residual Stresses in Laser Additive Manufacturing: A Critical Review

by Sung-Heng Wu, Usman Tariq, Ranjit Joy, Todd Sparks, Aaron Flood and Frank Liou

Materials 2024, 17(7), 1498; https://doi.org/10.3390/ma17071498 - 26 Mar 2024

Cited by 5 | Viewed by 1896

Abstract

In recent decades, laser additive manufacturing has seen rapid development and has been applied to various fields, including the aerospace, automotive, and biomedical industries. However, the residual stresses that form during the manufacturing process can lead to defects in the printed parts, such as distortion and cracking. Therefore, accurately predicting residual stresses is crucial for preventing part failure and ensuring product quality. This critical review covers the fundamental aspects and formation mechanisms of residual stresses. It also extensively discusses the prediction of residual stresses utilizing experimental, computational, and machine learning methods. Finally, the review addresses the challenges and future directions in predicting residual stresses in laser additive manufacturing. Full article

(This article belongs to the Special Issue Design, Optimization, Simulation, and Defect Detection for Additive Manufacturing)

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