Search Results (43)

Background: Stereolithography is a rapid prototyping and 3D printing technique that creates solid three-dimensional models. An accurate and functional 3D model using stereolithography is invaluable in scientific research, particularly in studies involving edentulous patients. Additive manufacture and CAD systems help achieve accurate measurements and procedures and be easily replicated by lowering human error mistakes. The main objective of this study was to develop an in vitro simulation model with a reduced alveolar ridge with the same characteristics as mandibular edentulous patients using stereolithography. Methods: A mandibular model with a resorbed mandibular crest was scanned, and the STL model was aligned to the XYZ reference system. A reduction in the alveolar ridge corresponding to the mandibular mucosa of an edentulous patient was achieved. A negative model also derived from the original model was made to ensure the space for oral simulation material. A dimensional stability test was performed to validate the model. Results: The maximal mean displacement of the model was 0.015 mm, and the minimal mean displacement was 0.004 mm. The oral mucosa had a displacement of approximately 1.6 mm. Conclusions: An in vitro 3D simulation model of a complete edentulous patient mucosa was achieved. Full article

Fluid effects are important in films and advertisements, where their realism and aesthetic quality directly impact the visual experience. With the rapid advancement of digital technology and computer-aided design (CAD), modern visual effects are used to simulate various water-related phenomena, such as flowing water, ocean waves, and raindrops. However, creating these realistic effects is not solely dependent on advanced software and hardware; it also requires an understanding of the technical and artistic aspects of visual effects artists. In the creation process, the artist must possess a keen aesthetic sense and innovative thinking to craft stunning visual effects to overcome technological constraints. Whether depicting the grandeur of turbulent ocean scenes or the romance of gentle rain, the artist needs to transform fluid effects into expressive visual language to enhance emotional impact, aligning with the storyline and the director’s vision. The production process of fluid effects typically involves the following critical steps. First, the visual effects artist utilizes CAD-based tools, particle systems, or fluid simulation software to model the dynamic behavior of water. This process demands a solid foundation in physics and the ability to adjust parameters flexibly according to the specific needs of the scene, ensuring that the fluid motion appears natural and smooth. Next, in the rendering stage, the simulated fluid is transformed into realistic imagery, requiring significant computational power and precise handling of lighting effects. Finally, in the compositing stage, the fluid effects are seamlessly integrated with live-action footage, making the visual effects appear as though they are parts of the actual scene. In this study, the technical details of creating fluid effects using free software such as Blender were explored. How advanced CAD tools are utilized to achieve complex water effects was also elucidated. Additionally, case studies were conducted to illustrate the creative processes involved in visual effects production to understand how to seamlessly blend technology with artistry to create unforgettable visual spectacles. Full article

Facial soft tissue reconstruction is an important tool in forensic investigations, especially when conventional identification methods are unsuccessful. This paper presents a digital workflow for facial reconstruction and identity verification using computer vision techniques applied to two forensic cases. The first case involves a cold case from 1993, in which a manual reconstruction by Prof. Helmer was conducted in 1994. We digitally reconstructed the same individual using CAD software (Blender), enabling a direct comparison between manual and digital techniques. To date, the deceased remains unidentified. The second case, from 2021, involved a digitally reconstructed face that was later matched to a missing person through DNA analysis. Here, comparison material was available, including an official photograph. A police officer involved in the case noted a “striking resemblance” between the reconstruction and the photograph. To evaluate this subjective impression, we performed quantitative analyses using three face recognition models (Dlib-based method, VGG-Face, and GhostFaceNet). The models did not indicate significant similarity, highlighting a gap between human perception and algorithmic assessment. These findings suggest that current face recognition algorithms may not yet be fully suited to evaluating reconstructions, which tend to deviate in subtle but critical facial features. To achieve better facial recognition results, further research is required to generate more anatomically accurate and detailed reconstructions that align more closely with the sensitivity of AI-based identification systems. Full article

Robots and 3D scanning systems are essential in modern industrial production, enhancing quality control, reducing costs, and improving production efficiency. Such systems align with Industry 4.0 trends, incorporating the Internet of Things (IoT), Big Data, Cyber–Physical Systems, and Artificial Intelligence to drive innovation. This paper focuses on the physical adaptation of old or out-of-use articulated robot arms for new tasks such as manipulation with a handheld 3D scanner, with the goal of automated quality control. The adaptation was carried out using a methodology that features the application of several techniques such as 3D digitization (photogrammetry), reverse engineering and 3D modeling (SolidWorks), the CAD search engine (3Dfindit), and 3D printing (fused deposition modeling—FDM). Reconstructed 3D models were used to design connecting elements, such as gripper jaws. The final results show that it is possible to create a connecting element utilizing this approach with very little expenditure of resources and time. Full article

Purpose: This paper investigates the biomechanical effect of thermoformed aligners equipped with complementary biomechanical attachments (CBAs) on periodontal ligaments (PDLs) during the expansion process of the maxillary arch. The analysis was conducted using advanced simulations based on the finite element method (FEM). Methods: High-resolution 3D CAD models were created for four tooth types: canine, first premolar, second premolar, and first molar. Additional 3D models were developed for aligners, CBAs, and PDLs. These were integrated into a comprehensive FEM model to simulate clinical rehabilitation scenarios. Validation was achieved through comparative analysis with empirical medical data. Results: The FEM simulations revealed the following: for canine, the displacement was 0.134 mm with a maximum stress of 4.822 KPa in the amelocemental junction. For the first premolar, the displacement was 0.132 mm at a maximum stress of 3.273 KPa in the amelocemental junction. The second premolar had a displacement of 0.129 mm and a stress of 1.358 KPa at 1 mm from the amelocemental junction; and first molar had a displacement of 0.124 mm and a maximum stress of 2.440 KPa. Conclusions: The inclusion of CBAs significantly reduced tooth tipping during maxillary arch expansion. Among the models tested, the vestibular CBA demonstrated superior performance, delivering optimal tooth movement when combined with thermoformed aligners. Significance: FEM techniques provide a robust and cost-effective alternative to in vivo experimentation, offering precise and reliable insights into the biomechanical efficacy of CBAs in thermoformed aligners. This approach minimizes experimental variability and accelerates the evaluation of innovative orthodontic configurations. Full article

High-precision microfabrication is essential for enhancing or enabling new functionalities in parts and tooling surfaces. V-groove structures are commonly used in surface engineering for diverse applications. Selecting the optimal V-groove shape, array, and fabrication method is crucial for achieving the desired performance. This study integrates the parametric definition of V-groove structures in both design and fabrication modules using three main function blocks (MFBs). MFB1 defines a single V-groove’s parametric model using specific input parameters. MFB2 transforms these parameters into equations to generate a CAD model of the surface. MFB3 combines inputs from MFB1 with parameters related to cutting tool geometry, cutting strategy, and process planning, producing functional NC code for the machine tool. The approach focuses on micromachining radial V-grooves on planar surfaces, requiring precise alignment and multi-axis single-point diamond cutting (SPDC) with rotation tool center point (RTCP) support. Testing on acrylic samples achieved ±0.1° orientation accuracy and ±2 μm positional accuracy, demonstrating potential for applications in drag reduction, fouling resistance, light guiding, and open microfluidics. Full article

To improve the accuracy and completeness of three-dimensional sculpture reconstruction, this study proposes a global–local two-step scanning method for industrial robot-based scanning. First, a global model is generated through stepped rotary scanning based on the object’s dimensions. Subsequently, local viewpoint planning is conducted to refine regions that were incompletely captured in the initial step, with a genetic algorithm optimizing the scanning paths to enhance efficiency. The local models are then aligned and fused with the global model to produce the final 3D reconstruction. Comparative experiments on sculptures made of different materials were conducted to validate the effectiveness of the proposed method. Compared with CAD-slicing and surface-partitioning methods, the proposed approach achieved superior model completeness, a scanning accuracy of 0.26 mm, a standard deviation of 0.31 mm, and a total scanning time of 152 s. The results indicate that the proposed method enhances reconstruction integrity and overall quality while maintaining high efficiency, making it a viable approach for high-precision 3D surface inspection tasks. Full article

The increasing demand for efficiency, brand consistency, and sustainability in automotive design has led to the exploration of innovative methods. This study investigated the impact of the V-shaped Dynamic Morphology Curve (VDMC) on design efficiency, brand consistency, and sustainability outcomes in automobile wheel design. A total of 24 designers took part, divided into an experimental group using VDMC and a control group using traditional CAD methods. VDMC uses parametric modeling to accelerate design iterations while maintaining brand identity. The experimental group completed the design task 31.5% faster, achieved significantly higher brand consistency (9.1/10 vs. 7.8/10), and reduced the number of design iterations by 53.2% compared to the control group. Furthermore, the experimental group made 50.9% fewer design changes, indicating higher design stability. These results show that VDMC significantly improves design efficiency and sustainability by reducing both time and resource consumption while ensuring greater alignment with brand guidelines. This study highlights the potential of VDMC to transform traditional design practices and offers notable benefits for both creative processes and environmental impact. The results suggest that integrating VDMC into design workflows could lead to significant improvements in efficiency and sustainability in the automotive industry and beyond. Full article

The transition from conventional soil mapping (CSM) to digital soil mapping (DSM) not only affects the final map products, but it also affects the concepts of scale, resolution, and sampling intensity. This is critical because in the CSM approach, sampling intensity is intricately linked to the desired scale of soil map publication, which provided standardization of sampling. This is not the case for DSM where sample size varies widely by project, and sampling design studies have largely focused on where to sample without due consideration for sample size. Using a regional soil survey dataset with 1791 sampled and described soil profiles, we first extracted an external validation dataset using the conditioned Latin hypercube sampling (cLHS) algorithm and then created repeated (n = 10) sample plans of increasing size from the remaining calibration sites using the cLHS, feature space coverage sampling (FSCS), and simple random sampling (SRS). We then trained random forest (RF) models for four soil properties: pH, CEC, clay content, and SOC at five different depths. We identified the effective sample size based on the model learning curves and compared it to the optimal sample size determined from the Jensen–Shannon divergence (D_JS) applied to the environmental covariates. Maps were then generated from models that used all the calibration points (reference maps) and from models that used the optimal sample size (optimal maps) for comparison. Our findings revealed that the optimal sample sizes based on the D_JS analysis were closely aligned with the effective sample sizes from the model learning curves (815 for cLHS, 832 for FSCS, and 847 for SRS). Furthermore, the comparison of the optimal maps to the reference maps showed little difference in the global statistics (concordance correlation coefficient and root mean square error) and spatial trends of the data, confirming that the optimal sample size was sufficient for creating predictions of similar accuracy to the full calibration dataset. Finally, we conclude that the Ottawa soil survey project could have saved between CAD 330,500 and CAD 374,000 (CAD = Canadian dollars) if the determination of optimal sample size tools presented herein existed during the project planning phase. This clearly illustrates the need for additional research in determining an optimal sample size for DSM and demonstrates that operationalization of DSM in public institutions requires a sound scientific basis for determining sample size. Full article

Precision in diagnosis is essential for achieving optimal outcomes in prosthodontics, orthodontics, and orthognathic treatments. Virtual articulators provide a sophisticated digital alternative to conventional methods, integrating intraoral scans, facial scans, and cone beam computed tomography (CBCT) to enhance treatment predictability. This review examines advancements in virtual articulator technology, including digital workflows, virtual facebow transfer, and occlusal analysis, with a focus on Artificial Intelligence (AI)-driven methodologies such as machine learning and artificial neural networks. The clinical implications, particularly in condylar guidance and sagittal condylar inclination, are investigated. By streamlining the acquisition and articulation of digital dental models, virtual articulators minimize material handling errors and optimize workflow efficiency. Advanced imaging techniques enable precise alignment of digital maxillary models within computer-aided design and computer-aided manufacturing systems (CAD/CAM), facilitating accurate occlusal simulations. However, challenges include potential distortions during digital file integration and the necessity for robust algorithms to enhance data superimposition accuracy. The adoption of virtual articulators represents a transformative advancement in digital dentistry, with promising implications for diagnostic precision and treatment outcomes. Nevertheless, further clinical validation is essential to ensure the reliable transfer of maxillary casts and refine digital algorithms. Future developments should prioritize the integration of AI to enhance predictive modeling, positioning virtual articulators as a standard tool in routine dental practice, thereby revolutionizing treatment planning and interdisciplinary collaboration. This review explores advancements in virtual articulators, focusing on their role in enhancing diagnostic precision, occlusal analysis, and treatment predictability. It examines digital workflows, AI-driven methodologies, and clinical applications while addressing challenges in data integration and algorithm optimization. Full article

Cranioplasty enables the restoration of cranial defects caused by traumatic injuries, brain tumour excisions, or decompressive craniectomies. Conventional methods rely on Computer-Aided Design (CAD) for implant design, which requires significant resources and expertise. Recent advancements in Artificial Intelligence (AI) have improved Computer-Aided Diagnostic systems for accurate and faster cranial reconstruction and implant generation procedures. However, these face inherent limitations, including the limited availability of diverse datasets covering different defect shapes spanning various locations, absence of a comprehensive pipeline integrating the preprocessing of medical images, cranial reconstruction, and implant generation, along with mechanical testing and validation. The proposed framework incorporates a robust preprocessing pipeline for easier processing of Computed Tomography (CT) images through data conversion, denoising, Connected Component Analysis (CCA), and image alignment. At its core is CRIGNet (Cranial Reconstruction and Implant Generation Network), a novel deep learning model rigorously trained on a diverse dataset of 2160 images, which was prepared by simulating cylindrical, cubical, spherical, and triangular prism-shaped defects across five skull regions, ensuring robustness in diagnosing a wide variety of defect patterns. CRIGNet achieved an exceptional reconstruction accuracy with a Dice Similarity Coefficient (DSC) of 0.99, Jaccard Similarity Coefficient (JSC) of 0.98, and Hausdorff distance (HD) of 4.63 mm. The generated implants showed superior geometric accuracy, load-bearing capacity, and gap-free fitment in the defected skull compared to CAD-generated implants. Also, this framework reduced the implant generation processing time from 40–45 min (CAD) to 25–30 s, suggesting its application for a faster turnaround time, enabling decisive clinical support systems. Full article

This research aims to facilitate informed decision-making to enhance building energy simulation, reduce costs, and minimize CO₂ emissions through building insulation enhancements employing BIM-based simulation. Architectural models of an apartment, a prevalent residential structure in Japan, were developed and examined under diverse insulation scenarios utilizing ArchiCAD 28. Five insulation substances were chosen based on existing guidelines to ensure conformity with local standards and were evaluated for their thermal and environmental properties: Cellulose Fiber, Glass Wool, Urethane Foam, Phenolic Board, and Rock Wool for evaluation based on thermal and environmental properties. The simulation parameters were aligned with Japan’s energy efficiency standards and climate conditions. The factors addressed encompass energy performance evaluation, economic viability, and CO₂ emissions. Simulation findings highlight Urethane Foam as the most effective and environmentally friendly building insulation material. This study provides valuable perspectives for property owners, building designers, and contractors, offering a framework for insulation enhancement choices that optimizes sustainable construction, reduces environmental impact, and enhances cost-effectiveness through the implementation of BIM-based simulation. Full article

The prevalence of kidney stones, a significant urological health concern, necessitates advancements in the management and treatment methods, particularly in the domain of ureteral stents. This study explores the feasibility and potential benefits of utilizing three biodegradable polymers—Polylactic Acid (PLA), Tough Polylactic Acid (Tough PLA), and Polylactic Acid/Poly-hydroxybutyrate (PLA/PHB)—for the fabrication of 3D-printed ureteral stents tailored to patient-specific needs. Through the integration of CAD and Fused Deposition Modeling (FDM) 3D printing technology, ureteral stents were successfully produced, demonstrating key advantages in terms of biodegradability and mechanical properties. The study involved a rigorous evaluation of the biodegradability, tensile strength, and hardness of the stents. Biodegradability tests performed in a simulated physiological environment revealed that PLA/PHB and Tough PLA stents exhibited higher degradation rates compared to PLA, aligning with the requirements for temporary urinary tract support. Tensile strength testing indicated that while PLA showed the highest strength, PLA/PHB and Tough PLA stents provided beneficial ductility, reducing the risk of blockage due to material breakage. Hardness assessments classified PLA/PHB stents as medium soft, optimizing patient comfort during the stenting period. These findings demonstrate the potential of using biodegradable polymers to produce ureteral stents that could eliminate the need for removal procedures, thereby enhancing patient recovery and comfort. Full article

This study presents six degrees of freedom (6-DoF) pose estimation of an object from a single RGB image and retrieval of the matching CAD model by measuring the similarity between RGB and CAD rendering images. The 6-DoF pose estimation of an RGB object is one of the important techniques in 3D computer vision. However, in addition to 6-DoF pose estimation, retrieval and alignment of the matching CAD model with the RGB object should be performed for various industrial applications such as eXtended Reality (XR), Augmented Reality (AR), robot’s pick and place, and so on. This paper addresses 6-DoF pose estimation and CAD model retrieval problems simultaneously and quantitatively analyzes how much the 6-DoF pose estimation affects the CAD model retrieval performance. This study consists of two main steps. The first step is 6-DoF pose estimation based on the PoseContrast network. We enhance the structure of PoseConstrast by adding variance uncertainty weight and feature attention modules. The second step is the retrieval of the matching CAD model by an image similarity measurement between the CAD rendering and the RGB object. In our experiments, we used 2000 RGB images collected from Google and Bing search engines and 100 CAD models from ShapeNetCore. The Pascal3D+ dataset is used to train the pose estimation network and DELF features are used for the similarity measurement. Comprehensive ablation studies about the proposed network show the quantitative performance analysis with respect to the baseline model. Experimental results show that the pose estimation performance has a positive correlation with the CAD retrieval performance. Full article

The study evaluates how the environmental impacts of wooden products could be assessed in the early stages of product development using CAD-integrated life cycle assessment (LCA) tools. Focusing on a wooden chair design, the study compares the environmental impact results derived from LCA tools integrated in SolidWorks, NX and Fusion against a traditional LCA analysis performed using SimaPro. Methods involve analysing a chair model to measure the environmental impacts across different life cycle phases, such as material extraction and manufacturing. The results reveal that manufacturing processes, particularly electricity use, significantly contribute to environmental impacts, especially marine and freshwater ecotoxicity. Comparisons between LCA tools integrated into commercial CAD software and SimaPro 9.5.0.1. showed that while the tools deliver comparable results for global warming potential and other categories, they struggle with certain impact categories. The main distinguishing features of the results were methodological. Overall, the results aligned the most with the impact values calculated in Solidworks Sustainability. The study concludes that CAD-integrated tools are useful for early-stage environmental assessments but have limitations, particularly in their material databases and life cycle scope. For a comprehensive assessment, combining these tools with more detailed analysis methods may be necessary. The research suggests improvements for CAD-based tools to enhance their effectiveness in evaluating the environmental impact of wooden products. Full article