scholarly journals Improving Geometric Accuracy of 3D Printed Parts Using 3D Metrology Feedback and Mesh Morphing

2020 ◽  
Vol 4 (4) ◽  
pp. 112
Author(s):  
Moustapha Jadayel ◽  
Farbod Khameneifar
Keyword(s):  
Vector Field ◽  
Three Dimensional ◽  
Measurement Data ◽  
Geometric Accuracy ◽  
Average Deviation ◽  
Mesh Model ◽  
3D Printed ◽  
3D Metrology ◽  
Deviation Vector ◽  
A Current

Additive manufacturing (AM), also known as 3D printing, has gained significant interest due to the freedom it offers in creating complex-shaped and highly customized parts with little lead time. However, a current challenge of AM is the lack of geometric accuracy of fabricated parts. To improve the geometric accuracy of 3D printed parts, this paper presents a three-dimensional geometric compensation method that allows for eliminating systematic deviations by morphing the original surface mesh model of the part by the inverse of the systematic deviations. These systematic deviations are measured by 3D scanning multiple sacrificial printed parts and computing an average deviation vector field throughout the model. We demonstrate the necessity to filter out the random deviations from the measurement data used for compensation. Case studies demonstrate that printing the compensated mesh model based on the average deviation of five sacrificial parts produces a part with deviations about three times smaller than measured on the uncompensated parts. The deviation values of this compensated part based on the average deviation vector field are less than half of the deviation values of the compensated part based on only one sacrificial part.

Geometric Accuracy Prediction for Additive Manufacturing Through Machine Learning of Triangular Mesh Data

2019 ◽  
Author(s):  
Nathan Decker ◽  
Qiang Huang
Keyword(s):  
Machine Learning ◽  
Additive Manufacturing ◽  
Three Dimensional ◽  
Triangular Mesh ◽  
Geometric Accuracy ◽  
New Approach ◽  
Machine Learning Model ◽  
3D Printed ◽  
3D Shapes ◽  
Complex Parts

Abstract While additive manufacturing has seen tremendous growth in recent years, a number of challenges remain, including the presence of substantial geometric differences between a three dimensional (3D) printed part, and the shape that was intended. There are a number of approaches for addressing this issue, including statistical models that seek to account for errors caused by the geometry of the object being printed. Currently, these models are largely unable to account for errors generated in freeform 3D shapes. This paper proposes a new approach using machine learning with a set of predictors based on the geometric properties of the triangular mesh file used for printing. A direct advantage of this method is the simplicity with which it can describe important properties of a 3D shape and allow for predictive modeling of dimensional inaccuracies for complex parts. To evaluate the efficacy of this approach, a sample dataset of 3D printed objects and their corresponding deviations was generated. This dataset was used to train a random forest machine learning model and generate predictions of deviation for a new object. These predicted deviations were found to compare favorably to the actual deviations, demonstrating the potential of this approach for applications in error prediction and compensation.

scholarly journals Geometric Evaluation of Mobile-Phone Camera Images for 3D Information

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Ferruh Yilmazturk ◽  
Ali Ersin Gurbak
Keyword(s):  
Three Dimensional ◽  
Bundle Adjustment ◽  
Reference Object ◽  
Geometric Accuracy ◽  
Mesh Model ◽  
The Galaxy ◽  
3D Mesh Model ◽  
Structure Height ◽  
3D Information ◽  
Two Stages

This study aimed to investigate the usability of smartphone camera images in 3D positioning applications with photogrammetric techniques. These investigations were performed in two stages. In the first stage, the cameras of five smartphones and a digital compact camera were calibrated using a calibration reference object, with signalized points having known three-dimensional (3D) coordinates. In the calibration process, the self-calibration bundle adjustment method was used. To evaluate the metric performances, the geometric accuracy tests in the image and object spaces were performed and the test results were compared. In the second stage, a 3D mesh model of a historical cylindrical structure (height = 8 m and diameter = 5 m) was generated using Structure-from-Motion and Multi-View-Stereo (SfM-MVS) approach. The images were captured using the Galaxy S4 smartphone camera, which produced the best result in the geometric accuracy tests for smartphone cameras. The accuracy tests on the generated 3D model were also applied in order to examine 3D object reconstruction capabilities of imaging with this device. The results demonstrated that smartphone cameras can be easily used as image acquisition tools for multiple photogrammetric applications.

2D versus 3D Endoscopy: Head-to-Head Comparison in a Simulated Model of Endoscopic Endonasal Dural Suturing

2021 ◽  
Author(s):  
Ivanna Nebor ◽  
Zoe Anderson ◽  
Juan C. Mejia-Munne ◽  
Ahmed Hussein ◽  
Kora Montemagno ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Cerebrospinal Fluid Fistula ◽  
Average Deviation ◽  
Endoscopic Endonasal ◽  
Simulated Model ◽  
Novice Group ◽  
Significant Difference ◽  
Procedural Time ◽  
3D Printed ◽  
Dural Suturing

Abstract Objective Endonasal dural suturing (EDS) has been reported to decrease the incidence of cerebrospinal fluid fistula. This technique requires handling of single-shaft instrumentation in the narrow endonasal corridor. It has been proposed that three-dimensional (3D) endoscopes were associated with improved depth perception. In this study, we sought to perform a comparison of two-dimensional (2D) versus 3D endoscopy by assessing surgical proficiency in a simulated model of EDS. Materials and Methods Twenty-six participants subdivided into groups based on previous endoscopic experience were asked to pass barbed sutures through preset targets with either 2D (Storz Hopkins II) or 3D (Storz TIPCAM) endoscopes on 3D-printed simulation model. Surgical precision and procedural time were measured. All participants completed a Likert scale questionnaire. Results Novice, intermediate, and expert groups took 11.0, 8.7, and 5.7 minutes with 2D endoscopy and 10.9, 9.0, and 7.6 minutes with 3D endoscopy, respectively. The average deviation for novice, intermediate, and expert groups (mm) was 5.5, 4.4, and 4.3 with 2D and 6.6, 4.6, and 3.0 with 3D, respectively. No significant difference in procedural time or accuracy was found in 2D versus 3D endoscopy. 2D endoscopic visualization was preferred by the majority of expert/intermediate participants, while 3D endoscopic visualization by the novice group. Conclusion In this pilot study, there was no statistical difference in procedural time or accuracy when utilizing 2D versus 3D endoscopes. While it is possible that widespread familiarity with 2D endoscopic equipment has biased this study, preliminary analysis suggests that 3D endoscopy offers no definitive advantage over 2D endoscopy in this simulated model of EDS.

Use of Three-dimensional Printing in the Development of Optimal Cardiac CT Scanning Protocols

2020 ◽  
Vol 16 (8) ◽  
pp. 967-977
Author(s):  
Zhonghua Sun
Keyword(s):  
Cardiovascular Disease ◽  
Cardiac Computed Tomography ◽  
Three Dimensional ◽  
Ct Scanning ◽  
Aortic Diseases ◽  
Clinical Value ◽  
Three Dimensional Printing ◽  
Doctor Patient Communication ◽  
Medical Education And Training ◽  
3D Printed

Three-dimensional (3D) printing is increasingly used in medical applications with most of the studies focusing on its applications in medical education and training, pre-surgical planning and simulation, and doctor-patient communication. An emerging area of utilising 3D printed models lies in the development of cardiac computed tomography (CT) protocols for visualisation and detection of cardiovascular disease. Specifically, 3D printed heart and cardiovascular models have shown potential value in the evaluation of coronary plaques and coronary stents, aortic diseases and detection of pulmonary embolism. This review article provides an overview of the clinical value of 3D printed models in these areas with regard to the development of optimal CT scanning protocols for both diagnostic evaluation of cardiovascular disease and reduction of radiation dose. The expected outcomes are to encourage further research towards this direction.

Investigation of the Static Behavior and Failure Mechanisms of a 3D Printed Bio-Based Sandwich with Auxetic Core

2020 ◽  
Vol 12 (05) ◽  
pp. 2050051
Author(s):  
Khawla Essassi ◽  
Jean-Luc Rebiere ◽  
Abderrahim El Mahi ◽  
Mohamed Amine Ben Souf ◽  
Anas Bouguecha ◽  
...  
Keyword(s):  
Failure Mechanisms ◽  
Three Dimensional ◽  
Acoustic Emissions ◽  
Shear Stiffness ◽  
Tensile Tests ◽  
Sandwich Composite ◽  
Static Behavior ◽  
Flax Fibers ◽  
Data Points ◽  
3D Printed

In this research contribution, the static behavior and failure mechanisms are developed for a three-dimensional (3D) printed dogbone, auxetic structure and sandwich composite using acoustic emissions (AEs). The skins, core and whole sandwich are manufactured using the same bio-based material which is polylactic acid reinforced with micro-flax fibers. Tensile tests are conducted on the skins and the core while bending tests are conducted on the sandwich composite. Those tests are carried out on four different auxetic densities in order to investigate their effect on the mechanical and damage properties of the materials. To monitor the invisible damage and damage propagation, a highly sensitive AE testing method is used. It is found that the sandwich with high core density displays advanced mechanical properties in terms of bending stiffness, shear stiffness, facing bending stress and core shear stress. In addition, the AE data points during testing present an amplitude range of 40–85[Formula: see text]dB that characterizes visible and invisible damage up to failure.

Dynamic simulation of wind field in three-dimensional display space considering particle swarm algorithm fuzzy logic

2021 ◽  
pp. 1-6
Author(s):  
Honglei Xu ◽  
Linhuan Wang
Keyword(s):  
Fuzzy Logic ◽  
Dynamic Simulation ◽  
Wind Field ◽  
Three Dimensional ◽  
Measurement Data ◽  
Particle Swarm ◽  
Particle Swarm Algorithm ◽  
Three Dimensional Display ◽  
Swarm Algorithm ◽  
Synchronous Measurement

In order to improve the accuracy of dynamic detection of wind field in the three-dimensional display space, system software is carried out on the actual scene and corresponding airborne radar observation information data, and the particle swarm algorithm fuzzy logic algorithm is introduced into the wind field dynamic simulation process in three-dimensional display space, to analyze the error of the filtering result in detail, to process the hurricane Lily Doppler radar measurement data with the optimal adaptive filtering according to the error data. The three-dimensional wind field synchronous measurement data obtained by filtering was compared with three-dimensional wind field synchronous measurement data of the GPS dropsonde in this experiment, the sea surface wind field measurement data of the multi-band microwave radiometer, and the wind field data at aircraft altitude.

scholarly journals Data-Driven Intelligent 3D Surface Measurement in Smart Manufacturing: Review and Outlook

Machines ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 13
Author(s):  
Yuhang Yang ◽  
Zhiqiao Dong ◽  
Yuquan Meng ◽  
Chenhui Shao
Keyword(s):  
High Resolution ◽  
High Performance ◽  
Sampling Design ◽  
Three Dimensional ◽  
Measurement Data ◽  
Data Driven ◽  
Surface Measurement ◽  
Smart Manufacturing ◽  
Future Research ◽  
3D Surface

High-fidelity characterization and effective monitoring of spatial and spatiotemporal processes are crucial for high-performance quality control of many manufacturing processes and systems in the era of smart manufacturing. Although the recent development in measurement technologies has made it possible to acquire high-resolution three-dimensional (3D) surface measurement data, it is generally expensive and time-consuming to use such technologies in real-world production settings. Data-driven approaches that stem from statistics and machine learning can potentially enable intelligent, cost-effective surface measurement and thus allow manufacturers to use high-resolution surface data for better decision-making without introducing substantial production cost induced by data acquisition. Among these methods, spatial and spatiotemporal interpolation techniques can draw inferences about unmeasured locations on a surface using the measurement of other locations, thus decreasing the measurement cost and time. However, interpolation methods are very sensitive to the availability of measurement data, and their performances largely depend on the measurement scheme or the sampling design, i.e., how to allocate measurement efforts. As such, sampling design is considered to be another important field that enables intelligent surface measurement. This paper reviews and summarizes the state-of-the-art research in interpolation and sampling design for surface measurement in varied manufacturing applications. Research gaps and future research directions are also identified and can serve as a fundamental guideline to industrial practitioners and researchers for future studies in these areas.

scholarly journals Midface Reconstruction: Planning and Outcome

2020 ◽  
Vol 53 (03) ◽  
pp. 324-334
Author(s):  
Gautam Biswas
Keyword(s):  
Digital Imaging ◽  
3D Structure ◽  
Three Dimensional ◽  
The Past ◽  
Complex Anatomy ◽  
Osseointegrated Implants ◽  
Low Profile ◽  
3D Printed ◽  
Midface Reconstruction ◽  
Reconstruction Planning

Abstract Reconstruction of the complex anatomy and aesthetics of the midface is often a challenge. A careful understanding of this three-dimensional (3D) structure is necessary. Anticipating the extent of excision and its planning following oncological resections is critical.In the past over two decades, with the advances in microsurgical procedures, contributions toward the reconstruction of this area have generated interest. Planning using digital imaging, 3D printed models, osseointegrated implants, and low-profile plates, has favorably impacted the outcome. However, there are still controversies in the management: to use single composite tissues versus multiple tissues; implants versus autografts; vascularized versus nonvascularized bone; prosthesis versus reconstruction.This article explores the present available options in maxillary reconstruction and outlines the approach in the management garnered from past publications and experiences.

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