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The additive manufacturing (AM) has met a big challenge on account of customized shapes, especially complex and articulated models, designed by traditional approaches. For realizing AM processing, the reuse, matching, and modifications of the existing 3D digitized models are prerequisite to the applications which also avoid designing from start. In this study, a 3D model matching framework for articulated models serves as a solution for the initial digital design and model processing steps of AM. A discriminative shape descriptor is proposed, which is based on a slice-based model representation and combined with the shape feature distribution in the histogram form. Also a multi-scale histogram approach, integrating an improved Earth Mover's Distance (iEMD), is developed for feature matching which overcomes noise and scale perturbations. The experiments show better performances (average up 7.92 %∼15.80 %) than the classical competitors according to the retrieval performances evaluated by five typical measurements on the McGill database.
Xin Lin; Kunpeng Zhu; Min Zhou; Jerry Ying Hsi Fuh; Qing-Guo Wang. Articulated 3D model matching using multi-scale histograms of shape features for customized additive manufacturing. Computers in Industry 2021, 132, 103520 .
AMA StyleXin Lin, Kunpeng Zhu, Min Zhou, Jerry Ying Hsi Fuh, Qing-Guo Wang. Articulated 3D model matching using multi-scale histograms of shape features for customized additive manufacturing. Computers in Industry. 2021; 132 ():103520.
Chicago/Turabian StyleXin Lin; Kunpeng Zhu; Min Zhou; Jerry Ying Hsi Fuh; Qing-Guo Wang. 2021. "Articulated 3D model matching using multi-scale histograms of shape features for customized additive manufacturing." Computers in Industry 132, no. : 103520.
Heat accumulation is a critical problem in continuous multi-layer laser aided additive manufacturing (LAAM) process, resulting in inhomogeneous mechanical properties and non-uniformity in the deposited height which can deteriorate the deposition process. This work presents a new integrated finite element (FE) simulation and machine learning approach to select a multi-layer laser infill toolpath planning strategy for fabricating quadrilateral parts to minimise localised heat accumulation during the deposition process. After one layer deposition simulation, the approach employs a Temperature-Pattern Recurrent Neural Networks (TP-RNN) model to predict the temperature field after the next layer deposition for each of the candidate infill toolpaths, and a process parameters inspired thermal field evaluation method to select the best candidate toolpath. The approach would significantly improve the computational efficiency of the laser infill toolpath planning, which was validated by improving the flatness of the 20-layer cube deposition samples with two dimensions (20 mm × 20 mm and 30 mm × 30 mm).
K. Ren; Y. Chew; N. Liu; Y. F. Zhang; J. Y. H. Fuh; G. J. Bi. Integrated numerical modelling and deep learning for multi-layer cube deposition planning in laser aided additive manufacturing. Virtual and Physical Prototyping 2021, 1 -15.
AMA StyleK. Ren, Y. Chew, N. Liu, Y. F. Zhang, J. Y. H. Fuh, G. J. Bi. Integrated numerical modelling and deep learning for multi-layer cube deposition planning in laser aided additive manufacturing. Virtual and Physical Prototyping. 2021; ():1-15.
Chicago/Turabian StyleK. Ren; Y. Chew; N. Liu; Y. F. Zhang; J. Y. H. Fuh; G. J. Bi. 2021. "Integrated numerical modelling and deep learning for multi-layer cube deposition planning in laser aided additive manufacturing." Virtual and Physical Prototyping , no. : 1-15.
Additive manufacturing enables the fabrication of parts with complex geometries, thereby opening up the design space from part scale to microarchitecture scale. By optimising the structure in the expanded design space, structural performance can be improved. Topology optimisation is commonly used as the tool to optimise the structures according to specific application requirements. However, multiscale topology optimisation can be computationally expensive and with limited choices in microscale structures. Therefore, we propose a surrogate model based on three-dimensional convolutional neural networks (3D-CNN) to model the effective elasticity tensor and its gradients for general voxel-based nonparametric microstructures. The proposed 3D-CNN-based surrogate model greatly extends the flexibility over existing surrogate-based methods which can only be applied in relatively simple parametric microstructures. Given the microscale structure, the proposed 3D-CNN-based model can effectively predict its material properties. Furthermore, being able to estimate the gradient of the material properties with respect to microscale structure changes makes the proposed 3D-CNN-based surrogate readily adaptive to existing multiscale topology optimisation frameworks. Through extensive simulations, by comparing with both SIMP and existing surrogate-based methods, we demonstrate the advantages of the proposed 3D-CNN-based surrogate model.
Guo Yilin; Jerry Fuh Ying Hsi; Lu Wen Feng. Multiscale topology optimisation with nonparametric microstructures using three-dimensional convolutional neural network (3D-CNN) models. Virtual and Physical Prototyping 2021, 1 -12.
AMA StyleGuo Yilin, Jerry Fuh Ying Hsi, Lu Wen Feng. Multiscale topology optimisation with nonparametric microstructures using three-dimensional convolutional neural network (3D-CNN) models. Virtual and Physical Prototyping. 2021; ():1-12.
Chicago/Turabian StyleGuo Yilin; Jerry Fuh Ying Hsi; Lu Wen Feng. 2021. "Multiscale topology optimisation with nonparametric microstructures using three-dimensional convolutional neural network (3D-CNN) models." Virtual and Physical Prototyping , no. : 1-12.
Additive manufacturing (AM) technology has rapidly evolved with research advances related to AM processes, materials, and designs. The advantages of AM over conventional techniques include an augmented capability to produce parts with complex geometries, operational flexibility, and reduced production time. However, AM processes also face critical issues, such as poor surface quality and inadequate mechanical properties. Therefore, several post-processing technologies are applied to improve the surface quality of the additively manufactured parts. This work aims to document post-processing technologies and their applications concerning different AM processes. Various types of post-process treatments are reviewed and their integrations with AM process are discussed.
Xing Peng; Lingbao Kong; Jerry Fuh; Hao Wang. A Review of Post-Processing Technologies in Additive Manufacturing. Journal of Manufacturing and Materials Processing 2021, 5, 38 .
AMA StyleXing Peng, Lingbao Kong, Jerry Fuh, Hao Wang. A Review of Post-Processing Technologies in Additive Manufacturing. Journal of Manufacturing and Materials Processing. 2021; 5 (2):38.
Chicago/Turabian StyleXing Peng; Lingbao Kong; Jerry Fuh; Hao Wang. 2021. "A Review of Post-Processing Technologies in Additive Manufacturing." Journal of Manufacturing and Materials Processing 5, no. 2: 38.
In the selective laser melting process, metal powder melted by the laser heat source generates large instantaneous energy, resulting in transient high temperature and complex stress distribution. Different temperature gradients and anisotropy finally determine the microstructure after melting and affect the build quality and mechanical properties as a result. It is important to monitor and investigate the temperature and stress distribution evolution. Due to the difficulties in online monitoring, finite element methods (FEM) are used to simulate and predict the building process in real time. In this paper, a thermo-mechanical coupled FEM model is developed to predict the thermal behaviors of the melt pool by using Gaussian moving heat source. The model could simulate the shapes of the melt pool, distributions of temperature and stress under different process parameters through FEM. The influences of scanning speed, laser power, and spot diameter on the distribution of the melt pool temperature and stress are investigated in the SLM process of Al6063, which is widely applied in aerospace, transportation, construction and other fields due to its good corrosion resistance, sufficient strength and excellent process performance. Based on transient analysis, the relationships are identified among these process parameters and the melt pool morphology, distribution of temperature and thermal stress. It is shown that the maximum temperature at the center point of the scanning tracks will gradually increase with the increment of laser power under the effect of thermal accumulation and heat conduction, as the preceded scanning will preheat the subsequent scanning tracks. It is recommended that the parameters with optimized laser power (P = 175–200 W), scanning speed (v = 200–300 mm/s) and spot diameter (D = 0.1–0.15 mm) of aluminum alloy powder can produce a high building quality of the SLM parts under the pre-set conditions.
Xianyin Duan; Xinyue Chen; Kunpeng Zhu; Tao Long; Shiyang Huang; Fuh Jerry. The Thermo-Mechanical Coupling Effect in Selective Laser Melting of Aluminum Alloy Powder. Materials 2021, 14, 1673 .
AMA StyleXianyin Duan, Xinyue Chen, Kunpeng Zhu, Tao Long, Shiyang Huang, Fuh Jerry. The Thermo-Mechanical Coupling Effect in Selective Laser Melting of Aluminum Alloy Powder. Materials. 2021; 14 (7):1673.
Chicago/Turabian StyleXianyin Duan; Xinyue Chen; Kunpeng Zhu; Tao Long; Shiyang Huang; Fuh Jerry. 2021. "The Thermo-Mechanical Coupling Effect in Selective Laser Melting of Aluminum Alloy Powder." Materials 14, no. 7: 1673.
In the selective laser melting process, the molten pool flow, particularly the keyhole phenomenon, plays an important role in the pore formation and then influences the mechanical properties. In this study, we develop a 3D numerical model to simulate the keyhole mode in SLM. The transient evolutions of the temperature field, fluid flow, molten pool geometry and energy absorption have all been reproduced. The simulated molten pool dimensions agree well with the experimental data, including the fluctuation. More thorough insights into the underlying physical mechanisms are achieved, including the correlation between the keyhole geometry and laser absorption, the influence of manufacturing parameters on the melting mode, and the fluid flow pattern under different melting modes. These understandings can provide guidance for the optimization of manufacturing process parameters to improve the product quality.
Wenjun Ge; Jerry Y.H. Fuh; Suck Joo Na. Numerical modelling of keyhole formation in selective laser melting of Ti6Al4V. Journal of Manufacturing Processes 2021, 62, 646 -654.
AMA StyleWenjun Ge, Jerry Y.H. Fuh, Suck Joo Na. Numerical modelling of keyhole formation in selective laser melting of Ti6Al4V. Journal of Manufacturing Processes. 2021; 62 ():646-654.
Chicago/Turabian StyleWenjun Ge; Jerry Y.H. Fuh; Suck Joo Na. 2021. "Numerical modelling of keyhole formation in selective laser melting of Ti6Al4V." Journal of Manufacturing Processes 62, no. : 646-654.
Selective laser melting (SLM) is a promising additive manufacturing technology, which involves complex physics such as heat and mass transfer, phase transformation and molten pool flow. In this study, a three dimensional numerical model is developed to model the thermal-fluid flow and to predict the surface morphology for the SLM process. Particularly the laser ray tracing method is coupled with the VOF method to reproduce the multiple reflections of laser between the randomly packed powder particles and highly dynamic molten pool. Two sets of experiments are used to validate the model: 1) single tracks on a bare plate with different scan strategies, and 2) single tracks on a powder layer with different scan speeds. For the bare-plate single tracks, the width and surface elevation, including their variation along the track distance, are well reproduced in the simulations. For the powder-layer single tracks, the experimentally-observed balling, distributed and smooth tracks with varied scan speeds are all reproduced in the simulations. The results illustrate the complex flow pattern of the molten pool, particularly the effect of partially melted particles: 1) the semi-melted particles, drive the molten fluid flow from the molten pool center towards the unmelted particle, leading to the single track non-uniformity; 2) the near-fully melted particles, drive the molten fluid flow down into the melt pool, increasing the single track uniformity.
Wenjun Ge; SangWoo Han; Suck Joo Na; Jerry Ying Hsi Fuh. Numerical modelling of surface morphology in selective laser melting. Computational Materials Science 2020, 186, 110062 .
AMA StyleWenjun Ge, SangWoo Han, Suck Joo Na, Jerry Ying Hsi Fuh. Numerical modelling of surface morphology in selective laser melting. Computational Materials Science. 2020; 186 ():110062.
Chicago/Turabian StyleWenjun Ge; SangWoo Han; Suck Joo Na; Jerry Ying Hsi Fuh. 2020. "Numerical modelling of surface morphology in selective laser melting." Computational Materials Science 186, no. : 110062.
We describe the development and validation of a novel 3D-printed nasopharyngeal swab for the identification of SARS-CoV-2. We subjected the novel swab to mechanical and fluid absorption testing ex-vivo, and confirmed its ability to retain and release murine coronavirus and SARS-CoV-2. Compared to the Copan FLOQSwab, the novel swab displayed excellent correlation of RT-PCR cycle threshold values on paired clinical testing in COVID-19 patients, at r = 0.918 and 0.943 for the SARS-CoV-2 ORF1/a and sarbecovirus E-gene respectively. Overall positive and negative percent agreement was 90.6% and 100% respectively on a dual-assay RT-PCR platform, with discordant samples observed only at high cycle thresholds. When carefully designed and tested, 3D-printed swabs are a viable alternative to traditional swabs and will help mitigate strained resources in the escalating COVID-19 pandemic.
Joshua K Tay; Gail B Cross; Chun Kiat Lee; Benedict Yan; Jerold Loh; Zhen Yu Lim; Nicholas Ngiam; Jeremy Chee; Soo Wah Gan; Anmol Saraf; Wai Tung Eason Chow; Han Lee Goh; Chor Hiang Siow; Derrick Wq Lian; Woei Shyang Loh; Kwok Seng Loh; Vincent Tk Chow; De Yun Wang; Jerry Yh Fuh; Ching-Chiuan Yen; John El Wong; David M Allen. Design and clinical validation of a 3D-printed nasopharyngeal swab for COVID-19 testing. 2020, 1 .
AMA StyleJoshua K Tay, Gail B Cross, Chun Kiat Lee, Benedict Yan, Jerold Loh, Zhen Yu Lim, Nicholas Ngiam, Jeremy Chee, Soo Wah Gan, Anmol Saraf, Wai Tung Eason Chow, Han Lee Goh, Chor Hiang Siow, Derrick Wq Lian, Woei Shyang Loh, Kwok Seng Loh, Vincent Tk Chow, De Yun Wang, Jerry Yh Fuh, Ching-Chiuan Yen, John El Wong, David M Allen. Design and clinical validation of a 3D-printed nasopharyngeal swab for COVID-19 testing. . 2020; ():1.
Chicago/Turabian StyleJoshua K Tay; Gail B Cross; Chun Kiat Lee; Benedict Yan; Jerold Loh; Zhen Yu Lim; Nicholas Ngiam; Jeremy Chee; Soo Wah Gan; Anmol Saraf; Wai Tung Eason Chow; Han Lee Goh; Chor Hiang Siow; Derrick Wq Lian; Woei Shyang Loh; Kwok Seng Loh; Vincent Tk Chow; De Yun Wang; Jerry Yh Fuh; Ching-Chiuan Yen; John El Wong; David M Allen. 2020. "Design and clinical validation of a 3D-printed nasopharyngeal swab for COVID-19 testing." , no. : 1.
This paper aims to improve the surface quality of 316L stainless steel parts manufactured by selective laser melting (SLM) using dry mechanical-electrochemical polishing (DMECP). DMECP is an advanced surface finishing method combining the advantages of both mechanical and electrochemical polishing techniques in a more environmentally friendly manner. In this paper, the SLM process-related defects causing poor surface quality are analysed first. The material removal mechanism of DMECP is investigated to continuously remove the oxide layers formed during polishing. Surface morphology and roughness evolution under different polishing conditions are characterised. The top surface roughness can be reduced by over 91% from 8.72 μm to 0.75 μm compared to side surface by over 93% from 12.10 to 0.80 μm. The material removal on the top surface is more efficient than that on the side surface under the same polishing condition. The secondary defects formed during polishing can be removed using mechanical polishing mode. The chemical element composition of the polished surface exhibits almost identical content to the initial 316L powders. Compared with the initial dark and rough surfaces, the results validate the capability of DMECP as an effective tool to improve the SLM surface quality and achieve a mirror finish.
Yuchao Bai; Cuiling Zhao; Jin Yang; Jerry Ying Hsi Fuh; Wen Feng Lu; Can Weng; Hao Wang. Dry mechanical-electrochemical polishing of selective laser melted 316L stainless steel. Materials & Design 2020, 193, 108840 .
AMA StyleYuchao Bai, Cuiling Zhao, Jin Yang, Jerry Ying Hsi Fuh, Wen Feng Lu, Can Weng, Hao Wang. Dry mechanical-electrochemical polishing of selective laser melted 316L stainless steel. Materials & Design. 2020; 193 ():108840.
Chicago/Turabian StyleYuchao Bai; Cuiling Zhao; Jin Yang; Jerry Ying Hsi Fuh; Wen Feng Lu; Can Weng; Hao Wang. 2020. "Dry mechanical-electrochemical polishing of selective laser melted 316L stainless steel." Materials & Design 193, no. : 108840.
In recent years, metal cellular structures have drawn attentions in various industrial sectors due to their design freedoms and abilities to achieve multi-functional mechanical properties. However, metal cellular structures are difficult to fabricate due to their complex geometries, even with modern additive manufacturing technologies such as the direct metal laser sintering (DMLS) process. Assessing the manufacturability of metal cellular structures via a DMLS process is a challenging task as the geometric features of the structures are complex. Besides, via a DMLS process, the manufacturability also depends on the cumulative deformation of the layers during the manufacturing process. Existing methods on Design for Additive Manufacturing (DFAM) provide design guidelines that are based on past successful printed designs. However, they are not effective in predicting the manufacturability of metal cellular structures. In this paper, we propose a semi-supervised deep learning based manufacturability assessment (SSDLMA) framework to assess whether a metal cellular structure can be successfully manufactured from a given DMLS process. To enable efficient learning, we represent the complex cellular structures as 3D binary arrays with a simple yet efficient voxelisation method. We then train a deep learning based classifier using only a small amount of experimental data by adopting a semi-supervised learning approach. By running real experiments and comparing with existing DFAM methods and machine learning models, we demonstrate the advantages of the proposed SSDLMA framework. The proposed framework can be extended to predict the manufacturability of various other complex geometries beyond cellular structure in a reliable way even with a small number of training data.
Yilin Guo; Wen Feng Lu; Jerry Ying Hsi Fuh. Semi-supervised deep learning based framework for assessing manufacturability of cellular structures in direct metal laser sintering process. Journal of Intelligent Manufacturing 2020, 32, 347 -359.
AMA StyleYilin Guo, Wen Feng Lu, Jerry Ying Hsi Fuh. Semi-supervised deep learning based framework for assessing manufacturability of cellular structures in direct metal laser sintering process. Journal of Intelligent Manufacturing. 2020; 32 (2):347-359.
Chicago/Turabian StyleYilin Guo; Wen Feng Lu; Jerry Ying Hsi Fuh. 2020. "Semi-supervised deep learning based framework for assessing manufacturability of cellular structures in direct metal laser sintering process." Journal of Intelligent Manufacturing 32, no. 2: 347-359.
Support structures are needed due to the complexities of induced structural, thermal and process factors in Selective Laser Melting (SLM). To date, little systematic study is found to unveil the support removability by a post-machining process. This paper presents an experimental study of removing 316L stainless steel cone and block supports by milling. The effect of different supports is identified by the variation in the microhardness distribution and microstructure of the workpieces. The milling performance of cone and block supports at different cutting depths is studied on the surface finish, surface roughness, milling force, and tool wear and chip formation. The cone supports are subjected to severe collapse, whilst the block supports are mainly removed by localized shearing. The milling force and specific cutting energy of cutting block supports are lower than that of cone supports, and so is the tool wear. A finite element method (FEM) model is developed to explain the removal mechanisms. The results of this study provide an essential reference and unique insight into removal of metal support structures. Moreover, the removability of supports, which is derived from the post-processing stage, should be considered as a new factor in the support design for additive manufacturing.
Qiqiang Cao; Yuchao Bai; Jiong Zhang; Zhuoqi Shi; Jerry Ying Hsi Fuh; Hao Wang. Removability of 316L stainless steel cone and block support structures fabricated by Selective Laser Melting (SLM). Materials & Design 2020, 191, 108691 .
AMA StyleQiqiang Cao, Yuchao Bai, Jiong Zhang, Zhuoqi Shi, Jerry Ying Hsi Fuh, Hao Wang. Removability of 316L stainless steel cone and block support structures fabricated by Selective Laser Melting (SLM). Materials & Design. 2020; 191 ():108691.
Chicago/Turabian StyleQiqiang Cao; Yuchao Bai; Jiong Zhang; Zhuoqi Shi; Jerry Ying Hsi Fuh; Hao Wang. 2020. "Removability of 316L stainless steel cone and block support structures fabricated by Selective Laser Melting (SLM)." Materials & Design 191, no. : 108691.
Laser aided additive manufacturing (LAAM) is a key metal 3D printing and remanufacturing technology for fabrication of near-net shape parts. Studying thermal field induced by different scanning strategies is important to evaluate and optimize the resultant residual stress and distortion distribution. However, it is very computationally expensive to simulate multi-bead deposition process using existing numerical model to analyze and select appropriate laser scanning strategies. In this paper, we make use of a recently developed and experimentally validated efficient thermal field prediction numerical model for LAAM to generate training data for a physics-based machine learning algorithm. A combined Recurrent Neural Networks and Deep Neural Networks (RNN–DNN) model was developed to identify the correlation between laser scanning patterns and their corresponding thermal history distributions. Subsequently, the developed RNN–DNN model is able to make thermal field prediction for an arbitrary geometry with different scanning strategies. Comparison between the numerical simulation results and the RNN–DNN predictions showed good agreement of more than 95%.
K. Ren; Y. Chew; Y.F. Zhang; J.Y.H. Fuh; G.J. Bi. Thermal field prediction for laser scanning paths in laser aided additive manufacturing by physics-based machine learning. Computer Methods in Applied Mechanics and Engineering 2020, 362, 112734 .
AMA StyleK. Ren, Y. Chew, Y.F. Zhang, J.Y.H. Fuh, G.J. Bi. Thermal field prediction for laser scanning paths in laser aided additive manufacturing by physics-based machine learning. Computer Methods in Applied Mechanics and Engineering. 2020; 362 ():112734.
Chicago/Turabian StyleK. Ren; Y. Chew; Y.F. Zhang; J.Y.H. Fuh; G.J. Bi. 2020. "Thermal field prediction for laser scanning paths in laser aided additive manufacturing by physics-based machine learning." Computer Methods in Applied Mechanics and Engineering 362, no. : 112734.
Ultrasonic vibrations were applied to weld Ni-based metallic glass ribbons with Al and Cu ribbons to manufacture high-performance metallic glass and crystalline metal composites with accumulating formation characteristics. The effects of ultrasonic vibration energy on the interfaces of the composite samples were studied. The ultrasonic vibrations enabled solid-state bonding of metallic glass and crystalline metals. No intermetallic compound formed at the interfaces, and the metallic glass did not crystallize. The hardness and modulus of the composites were between the respective values of the metallic glass and the crystalline metals. The ultrasonic bonding additive manufacturing can combine the properties of metallic glass and crystalline metals and broaden the application fields of metallic materials.
Guiwei Li; Ji Zhao; Jerry Ying Hsi Fuh; Wenzheng Wu; Jili Jiang; Tianqi Wang; Shuai Chang. Experiments on the Ultrasonic Bonding Additive Manufacturing of Metallic Glass and Crystalline Metal Composite. Materials 2019, 12, 2975 .
AMA StyleGuiwei Li, Ji Zhao, Jerry Ying Hsi Fuh, Wenzheng Wu, Jili Jiang, Tianqi Wang, Shuai Chang. Experiments on the Ultrasonic Bonding Additive Manufacturing of Metallic Glass and Crystalline Metal Composite. Materials. 2019; 12 (18):2975.
Chicago/Turabian StyleGuiwei Li; Ji Zhao; Jerry Ying Hsi Fuh; Wenzheng Wu; Jili Jiang; Tianqi Wang; Shuai Chang. 2019. "Experiments on the Ultrasonic Bonding Additive Manufacturing of Metallic Glass and Crystalline Metal Composite." Materials 12, no. 18: 2975.
Additive manufacturing (commonly known as 3D printing) is defined as a family of technologies that deposit and consolidate materials to create a 3D object as opposed to subtractive manufacturing methodologies. Fused deposition modeling (FDM), one of the most popular additive manufacturing techniques, has demonstrated extensive applications in various industries such as medical prosthetics, automotive, and aeronautics. As a thermal process, FDM may introduce internal voids and pores into the fabricated thermoplastics, giving rise to potential reduction on the mechanical properties. This paper aims to investigate the effects of the microscopic pores on the mechanical properties of material fabricated by the FDM process via experiments and micromechanical modeling. More specifically, the three-dimensional microscopic details of the internal pores, such as size, shape, density, and spatial location were quantitatively characterized by X-ray computed tomography (XCT) and, subsequently, experiments were conducted to characterize the mechanical properties of the material. Based on the microscopic details of the pores characterized by XCT, a micromechanical model was proposed to predict the mechanical properties of the material as a function of the porosity (ratio of total volume of the pores over total volume of the material). The prediction results of the mechanical properties were found to be in agreement with the experimental data as well as the existing works. The proposed micromechanical model allows the future designers to predict the elastic properties of the 3D printed material based on the porosity from XCT results. This provides a possibility of saving the experimental cost on destructive testing.
Xue Wang; Liping Zhao; Jerry Ying Hsi Fuh; Heow Pueh Lee. Effect of Porosity on Mechanical Properties of 3D Printed Polymers: Experiments and Micromechanical Modeling Based on X-Ray Computed Tomography Analysis. Polymers 2019, 11, 1154 .
AMA StyleXue Wang, Liping Zhao, Jerry Ying Hsi Fuh, Heow Pueh Lee. Effect of Porosity on Mechanical Properties of 3D Printed Polymers: Experiments and Micromechanical Modeling Based on X-Ray Computed Tomography Analysis. Polymers. 2019; 11 (7):1154.
Chicago/Turabian StyleXue Wang; Liping Zhao; Jerry Ying Hsi Fuh; Heow Pueh Lee. 2019. "Effect of Porosity on Mechanical Properties of 3D Printed Polymers: Experiments and Micromechanical Modeling Based on X-Ray Computed Tomography Analysis." Polymers 11, no. 7: 1154.
Laser aided additive manufacturing (LAAM) is one of the key metal 3D printing technologies for surface cladding or fabrication of near-net shape parts. The study of LAAM scanning pattern is important to understand their relationship with residual stress and part distortion. This paper proposed a framework to both simulate and evaluate laser scanning paths. Firstly, an efficient 3D thermal history analysis finite element (FE) model was developed to predict temperature field evolution for arbitrary scanning patterns. Subsequently, a thermal field based evaluation method was established to determine the optimal scanning pattern with minimal distortion. The effectiveness of the framework was validated experimentally by depositing a rectangular clad on a cuboid substrate with five different scanning patterns. Experiments showed width-wise Zigzag scanning pattern yielded largest distortion. This method with 5 criteria and two evaluation levels were effective to identify an improved width-wise Zigzag scanning pattern by adjusting the deposition paths sequence, while determining the length-wise scanning as the optimal pattern. This work also demonstrated that the temperature field can be used to make qualitative evaluation of LAAM induced distortion which further reduces computational costs.
K. Ren; Y. Chew; Y.F. Zhang; G.J. Bi; J.Y.H. Fuh. Thermal analyses for optimal scanning pattern evaluation in laser aided additive manufacturing. Journal of Materials Processing Technology 2019, 271, 178 -188.
AMA StyleK. Ren, Y. Chew, Y.F. Zhang, G.J. Bi, J.Y.H. Fuh. Thermal analyses for optimal scanning pattern evaluation in laser aided additive manufacturing. Journal of Materials Processing Technology. 2019; 271 ():178-188.
Chicago/Turabian StyleK. Ren; Y. Chew; Y.F. Zhang; G.J. Bi; J.Y.H. Fuh. 2019. "Thermal analyses for optimal scanning pattern evaluation in laser aided additive manufacturing." Journal of Materials Processing Technology 271, no. : 178-188.
Specific structures of esophagus play an important role in specific functions. However, current esophageal tissue engineering scaffolds replicate them poorly. To address this issue, the objective of this study is to fabricate a hierarchical PCL/F127 scaffold inspired by the natural esophageal structure. The hierarchical scaffold consists of aligned fibers in micro-size and thin film with nano-sized pores through combining E-jetting and E-spraying. The aligned fibers of scaffold guide the orientation and induce the elongation of fibroblasts, mimicking the uniformly oriented esophageal muscles. Furthermore, the film functioned as a protective barrier to replicate the esophageal mucosa. Meanwhile, the film also increases cell adhesion area, hence, improving cell proliferation. These two features of the fabricated hierarchical scaffold mimic the structure of natural esophagus. Moreover, fabricated hierarchical scaffold possesses comparable mechanical properties to natural esophagus. These results prove the potential of fabricated scaffold for esophagus tissue repair.
Bin Wu; Yuhe Yang; Jia Shi; Shuai Chang; Shihao Li; Wen Feng Lu; Dieter Trau; Jerry Ying Hsi Fuh. A biologically inspired hierarchical PCL/F127 scaffold for esophagus tissue repair. Materials Letters 2019, 243, 132 -135.
AMA StyleBin Wu, Yuhe Yang, Jia Shi, Shuai Chang, Shihao Li, Wen Feng Lu, Dieter Trau, Jerry Ying Hsi Fuh. A biologically inspired hierarchical PCL/F127 scaffold for esophagus tissue repair. Materials Letters. 2019; 243 ():132-135.
Chicago/Turabian StyleBin Wu; Yuhe Yang; Jia Shi; Shuai Chang; Shihao Li; Wen Feng Lu; Dieter Trau; Jerry Ying Hsi Fuh. 2019. "A biologically inspired hierarchical PCL/F127 scaffold for esophagus tissue repair." Materials Letters 243, no. : 132-135.
Laser deposition strategies can have significant effect on the temperature distribution for multi-bead multi-layered additive manufacturing. Its influence on thermal field will affect the induced residual stress and distortion. In this paper, a computationally efficient numerical model for Laser Aided Additive Manufacturing (LAAM) process was developed for evaluating deposition strategies and understanding how their dynamic temperature evolution can cause significant differences in the residual stress and distortion. The numerical model was calibrated with experimental clad bead dimensions and process parameters for depositing multi-bead SS316L onto the substrate of the same material. The numerical model was validated with experimental results for depositing a rectangular clad layer on a 3 mm thick substrate using Zigzag strategies along the width (x-axis) and length (y-axis) directions. Temperature field measurements using infrared camera and X-ray diffraction residual stress field measurements agreed well with numerical results. The predicted residual stress field showed that the approximately 2.3 times larger distortion along the y-axis direction in width-wise Zigzag scanning is caused by non-uniform stress distribution in the y-axis direction. However, width-wise Zigzag scanning leads to more homogeneous stress distribution in the x-axis and therefore lower distortion in the x-axis direction compared to length-wise Zigzag scanning.
K. Ren; Y. Chew; J.Y.H. Fuh; Y.F. Zhang; Guijun Bi. Thermo-mechanical analyses for optimized path planning in laser aided additive manufacturing processes. Materials & Design 2018, 162, 80 -93.
AMA StyleK. Ren, Y. Chew, J.Y.H. Fuh, Y.F. Zhang, Guijun Bi. Thermo-mechanical analyses for optimized path planning in laser aided additive manufacturing processes. Materials & Design. 2018; 162 ():80-93.
Chicago/Turabian StyleK. Ren; Y. Chew; J.Y.H. Fuh; Y.F. Zhang; Guijun Bi. 2018. "Thermo-mechanical analyses for optimized path planning in laser aided additive manufacturing processes." Materials & Design 162, no. : 80-93.
The rapid development of additive manufacturing technology provides a more flexible and efficient manufacturing solution for the high value-added parts with a complex topology. However, the poor surface finish poses a major obstacle for the wide application of the additively manufactured components when their functionality and tolerance are benchmarked with those produced by the conventional process. In selective laser melting, visible pattern and texture of the printed layers and unmolten particles cannot be avoided although research works have been conducted to improve the surface finish by optimising the selective laser melting strategy and process parameters. Therefore, a dedicated post-processing technique is generally required to improve the surface finish of the additively manufactured products in terms of various levels of geometric complexity. In this study, a vibration-assisted conformal polishing tool is developed to finish a representative v-groove structure fabricated by selective laser melting. Experiments are conducted to investigate the effects of abrasive size and polishing time on the improvement in surface roughness. The developed technique in this paper can be applied to finish the additively manufactured internal structures such as honeycomb structure and irregular holes that have linear projection along a single axis.
Jiong Zhang; Alvin You Xiang Toh; Hao Wang; Wen Feng Lu; Jerry Ying Hsi Fuh. Vibration-assisted conformal polishing of additively manufactured structured surface. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 2018, 233, 4154 -4164.
AMA StyleJiong Zhang, Alvin You Xiang Toh, Hao Wang, Wen Feng Lu, Jerry Ying Hsi Fuh. Vibration-assisted conformal polishing of additively manufactured structured surface. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science. 2018; 233 (12):4154-4164.
Chicago/Turabian StyleJiong Zhang; Alvin You Xiang Toh; Hao Wang; Wen Feng Lu; Jerry Ying Hsi Fuh. 2018. "Vibration-assisted conformal polishing of additively manufactured structured surface." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 233, no. 12: 4154-4164.
The incidence of peripheral nerve injuries is on the rise and the current gold standard for treatment of such injuries is nerve autografting. Given the severe limitations of nerve autografts which include donor site morbidity and limited supply, Neural Guide Conduits (NGCs) are considered as an effective alternative treatment. Conductivity is a desired property of an ideal NGC. Reduced graphene oxide (rGO) possesses several advantages in addition to its conductive nature such as the high surface area to volume ratio due to its nanostructure and has been explored for use in tissue engineering. However, most of the works reported are on traditional 2D culture with a layer of rGO coating, while the native tissue microenvironment is three‐dimensional. In this study, PCL/rGO scaffolds are fabricated using Electrohydrodynamic jet (EHD‐jet) 3D printing method as a proof of concept study. Mechanical and material characterization of the printed PCL/rGO scaffolds and PCL scaffolds are done. The addition of rGO results in softer scaffolds which is favorable for neural differentiation. In vitro neural differentiation studies using PC12 cells are also performed. Cell proliferation was higher in PCL/rGO scaffolds than PCL scaffolds. Reverse Transcription Polymerase Chain Reaction (RT‐PCR) and immunocytochemistry results reveal that PCL/rGO scaffolds support neural differentiation of PC12 cells. This article is protected by copyright. All rights reserved.
Sanjairaj VijayaVenkataRaman; Siti Thaharah; Shuo Zhang; Wen Feng Lu; Jerry Ying Hsi Fuh. 3D‐Printed PCL/rGO Conductive Scaffolds for Peripheral Nerve Injury Repair. Artificial Organs 2018, 43, 515 -523.
AMA StyleSanjairaj VijayaVenkataRaman, Siti Thaharah, Shuo Zhang, Wen Feng Lu, Jerry Ying Hsi Fuh. 3D‐Printed PCL/rGO Conductive Scaffolds for Peripheral Nerve Injury Repair. Artificial Organs. 2018; 43 (5):515-523.
Chicago/Turabian StyleSanjairaj VijayaVenkataRaman; Siti Thaharah; Shuo Zhang; Wen Feng Lu; Jerry Ying Hsi Fuh. 2018. "3D‐Printed PCL/rGO Conductive Scaffolds for Peripheral Nerve Injury Repair." Artificial Organs 43, no. 5: 515-523.
In tissue engineering, cell-laden scaffold has gradually replaced cell-less scaffold due to better biological performance. However, manual pipetting, the traditional cell seeding for cell-laden scaffold, leads to an imprecise and inhomogeneous cell distribution. As an alternative, micro-extrusion of cell-laden hydrogel achieves homogenous cell distribution, but causes high shear stress which is harmful to cells. To address this challenge, the objective of this study is to print cells on porous scaffold precisely without causing high shear stress to produce homogeneous cell-laden hybrid scaffold. Porous polycaprolactone scaffold fabricated through electro-hydrodynamic jetting was used as a representation. To improve scaffold hydrophilicity for better cell adhesion, 6% (w/w) Pluronic F127 was blended with polycaprolactone. HeLa cells, as a demonstration, were ejected on the scaffold fibers through piezoelectric inkjet printing. As a result, inkjet printing showed a more precise and homogeneous cell distribution and enhanced cell proliferation compared to manual pipetting (1.34- fold increase after 7 days). Furthermore, due to the low viscosity of cell solution, the average shear stress caused during inkjet printing was 1.79 kPa as opposed to 18 kPa of micro-extrusion, which is friendly to cells. In summary, through inkjet printing, homogeneous cell-laden hybrid scaffold could be fabricated with lower shear stress.
Bin Wu; Shihao Li; Jia Shi; Sanjairaj Vijayavenkataraman; Wen Feng Lu; Dieter Trau; Jerry Ying Hsi Fuh. Homogeneous cell printing on porous PCL/F127 tissue engineering scaffolds. Bioprinting 2018, 12, e00030 .
AMA StyleBin Wu, Shihao Li, Jia Shi, Sanjairaj Vijayavenkataraman, Wen Feng Lu, Dieter Trau, Jerry Ying Hsi Fuh. Homogeneous cell printing on porous PCL/F127 tissue engineering scaffolds. Bioprinting. 2018; 12 ():e00030.
Chicago/Turabian StyleBin Wu; Shihao Li; Jia Shi; Sanjairaj Vijayavenkataraman; Wen Feng Lu; Dieter Trau; Jerry Ying Hsi Fuh. 2018. "Homogeneous cell printing on porous PCL/F127 tissue engineering scaffolds." Bioprinting 12, no. : e00030.