Computer-aided Design Model Research Articles

Discretization of Non-uniform Rational B-Spline (NURBS) Models for Meshless Isogeometric Analysis

We present an algorithm for fast generation of quasi-uniform and variable-spacing nodes on domains whose boundaries are represented as computer-aided design (CAD) models, more specifically non-uniform rational B-splines (NURBS). This new algorithm enables the solution of partial differential equations within the volumes enclosed by these CAD models using (collocation-based) meshless numerical discretizations. Our hierarchical algorithm first generates quasi-uniform node sets directly on the NURBS surfaces representing the domain boundary, then uses the NURBS representation in conjunction with the surface nodes to generate nodes within the volume enclosed by the NURBS surface. We provide evidence for the quality of these node sets by analyzing them in terms of local regularity and separation distances. Finally, we demonstrate that these node sets are well-suited (both in terms of accuracy and numerical stability) for meshless radial basis function generated finite differences discretizations of the Poisson, Navier-Cauchy, and heat equations. Our algorithm constitutes an important step in bridging the field of node generation for meshless discretizations with isogeometric analysis.

An effective parametric sensitivity analysis to improve electrical and thermal energy/exergy efficiency of PVT system using nanofluid

A 3D steady-state model of a photovoltaic/Thermal system with nanofluid is studied to investigate the electrical and thermal performance of PVT by utilizing a combination of statistical modeling and numerical simulation. The 3D CAD (Computer Aided Design) modeling of the photovoltaic thermal (PV/T) is performed using Ansys Space Claim. The current study is based on using a 2-way coupling FSI approach for modeling nanofluid-based PVT systems. Five output responses electrical power, thermal power, electrical exergy, thermal exergy, and entropy generation are chosen against four input parameters, solar radiation (G_sun), ambient temperature (Tamb), mass flow rate (ṁ), and nanoparticles concentration % (φ) to analyze system performance. A statistical prediction model is developed using response surface methodology (RSM) that starts from the design of experiment (DOE). The predicted outcomes obtained from the statistical model and the numerical simulation of the heat transfer model exhibit the existence of good fitness. Furthermore, optimization is performed using RSM for various optimization objectives to suggest the ideal design parameter values for optimal system performance. Sensitivity analysis illustrates that a rise in ambient temperature causes a drop in electrical power production and leads to an increase in thermal power. However, the increase in solar radiation boosts electrical power and causes a drop in thermal exergy, entropy generation increases with an increase in solar irradiation. Similarly, an increase in mass flow rate leads to an increase in thermal power. Multi-objective optimization with the highest composite desirability values depicts the influence of input design parameters and has a favorable effect on the objective of concurrently maximizing electrical and thermal power.

Recent Trends and Technologies in rapid prototyping and its Inclination towards Industry 4.0

Prototyping technology is becoming vital in the business as a means of cutting costs and manufacturing time. At present, reverse engineering and rapid prototyping are important technologies that enhance prototype development. The traditional approaches require various intricate processes, such as selective heat sintering (SHS), digital-light-processing printer (DLP), remote distributed rapid prototyping model (RDRP), Stereo Lithography (STL) models, and reconstructing computer-aided design (CAD) models from scanned point data and these approaches has limitations in terms of time-consuming and expert knowledge required for automation. This study aims to explore the significance of Industry 4.0 and its impact on rapid prototyping. The study also addresses rapid prototyping in computer network architecture; digital-light-processing printers (DLP) in rapid prototyping, and software-defined network (SDN) networks in the context of rapid prototyping. Along with this powder bed fusion (PBF) method and electron beam melting (EBM) are included in the manuscript. Based on our exploration, the study suggested vital recommendations for the advancement in rapid prototyping using Industry 4.0

Evaluation and Improvement of a Prosthetic Hand Product Using Biomechanics and Empathy Map Approach

The Panangan Prosthetic Hand is a transradial prosthesis that can be operated with both amputated and non-amputated arms. Several users have reported some degree of exhaustion and discomfort when using this prosthesis. Users may also be dissatisfied because this product has not met some of their specific needs and desires. To evaluate the product, tests were conducted by measuring muscle activity using an electromyography (EMG) sensor and assessing discomfort levels using the Borg CR10 scale during specific activities performed with the prosthesis. Additionally, interviews were conducted using an empathy map to profile the participants. The test results showed high muscle activities and discomfort levels in certain tasks, such as pouring water from a drink box. Based on these findings and the participants' profiles, their needs were identified, and solutions for improving the product were designed. Subsequently, these solutions were developed into a three-dimensional computer-aided design (3D CAD) model prototype.

SimPLE, a visuotactile method learned in simulation to precisely pick, localize, regrasp, and place objects.

Existing robotic systems have a tension between generality and precision. Deployed solutions for robotic manipulation tend to fall into the paradigm of one robot solving a single task, lacking "precise generalization," or the ability to solve many tasks without compromising on precision. This paper explores solutions for precise and general pick and place. In precise pick and place, or kitting, the robot transforms an unstructured arrangement of objects into an organized arrangement, which can facilitate further manipulation. We propose SimPLE (Simulation to Pick Localize and placE) as a solution to precise pick and place. SimPLE learns to pick, regrasp, and place objects given the object's computer-aided design model and no prior experience. We developed three main components: task-aware grasping, visuotactile perception, and regrasp planning. Task-aware grasping computes affordances of grasps that are stable, observable, and favorable to placing. The visuotactile perception model relies on matching real observations against a set of simulated ones through supervised learning to estimate a distribution of likely object poses. Last, we computed a multistep pick-and-place plan by solving a shortest-path problem on a graph of hand-to-hand regrasps. On a dual-arm robot equipped with visuotactile sensing, SimPLE demonstrated pick and place of 15 diverse objects. The objects spanned a wide range of shapes, and SimPLE achieved successful placements into structured arrangements with 1-mm clearance more than 90% of the time for six objects and more than 80% of the time for 11 objects.

A nonconforming surface mesh generation method by binary tree

Computer-aided engineering (CAE) has emerged as an indispensable tool for facilitating engineering practices and driving industrial innovation. However, the insufficient quality and efficiency of discretizing complex computer-aided design (CAD) models significantly impede the advancement of CAE calculation accuracy and automation. The presence of “dirty” geometry leads to the fact that it is almost impossible to generate a traditional conforming mesh without geometry repair. In most instances, automating geometry repair proves to be even more challenging than meshing. To cope with intricate CAD model with “dirty” geometry, a novel binary tree surface subdivision method (BSSM) is proposed for automatically generated conforming and nonconforming meshes directly on CAD models. In contrast to the conventional conforming mesh, the nonconforming mesh allows for hanging nodes, thereby eliminating the limitations of the mesh conformance. This facilitates rapid transitions in mesh size for automatic mesh generation when dealing with “dirty” geometry. A series of numerical models employing BSSM are presented in this study. Results reveal that BSSM can automatically, efficiently and reliably generate high level quality mesh for arbitrary structures.

Emerging Innovations in Preoperative Planning and Motion Analysis in Orthopedic Surgery.

In recent years, preoperative planning has undergone significant advancements, with a dual focus: improving the accuracy of implant placement and enhancing the prediction of functional outcomes. These breakthroughs have been made possible through the development of advanced processing methods for 3D preoperative images. These methods not only offer novel visualization techniques but can also be seamlessly integrated into computer-aided design models. Additionally, the refinement of motion capture systems has played a pivotal role in this progress. These "markerless" systems are more straightforward to implement and facilitate easier data analysis. Simultaneously, the emergence of machine learning algorithms, utilizing artificial intelligence, has enabled the amalgamation of anatomical and functional data, leading to highly personalized preoperative plans for patients. The shift in preoperative planning from 2D towards 3D, from static to dynamic, is closely linked to technological advances, which will be described in this instructional review. Finally, the concept of 4D planning, encompassing periarticular soft tissues, will be introduced as a forward-looking development in the field of orthopedic surgery.

Analytic Solutions for Volume, Mass, Center of Gravity, and Inertia of Wing Segments and Rotors of Constant Density

In the preliminary design of aircraft lifting surfaces, accurate mass and inertia properties can be difficult to obtain. Typically, such methods as computer-aided design or statistical processes are used to determine these properties. These methods require significant time and effort to implement. The present paper presents an exact analytic method for calculating the volume, mass, center of gravity, and inertia properties of wing segments and rotors of constant density. The influence of taper, spanwise thickness distribution, airfoil geometry, and sweep are included. The utility of the method is presented, and the accuracy is evaluated with various test cases via percent difference with a corresponding computer-aided design model. These case studies demonstrate the present method to be accurate to within about 1% for typical wing geometries and within about 1.3% for typical propeller geometries.

Sensitivity analysis of non-uniform rational B-splines–based finite element/boundary element coupling in structural-acoustic design

For the purpose of modeling the acoustic fluid-structure interaction using direct differentiation method and conducting a structural-acoustic sensitivity analysis, a coupling approach based on the finite element method and the fast multipole boundary element method is suggested. Non-uniform rational B-splines isogeometric analysis bypasses the difficult volume parameterization procedure in the isogeometric finite element method and the time-consuming meshing process in classical finite element/boundary element method, allowing numerical analysis on computer-aided design models to be completed directly. The finite element/fast multipole boundary element method based on non-uniform rational B-splines isogeometric analysis enables the numerical prediction of the effects of arbitrarily formed vibrating structures on the sound field. Several numerical examples are shown to demonstrate the usefulness and efficiency of the proposed method.

Topological and lattice-based AM optimization for improving the structural efficiency of robotic arms

The robotic arm is one of the vital components of robot assembly. The purpose of the robotic arm is to transmit power and conduct the desired motion, i.e., translation or rotation. Robotic limbs are designed and constructed to execute certain tasks with a high degree of speed, accuracy, and efficiency. This research focuses on to enhancing the strength-to-weight ratio of robotic arm using certain techniques of additive manufacturing, i.e., topology optimization and lattice structure. Employing the finite element analysis, the impact of weight reduction optimization on structural parameters such as stress and deformation in the current design is assessed using ANSYS R18.1 for FE analysis and Creo parametric 7.0 design software for computer-aided design modeling. Observations reveal that the 0.5 and .4 scale lattice structure designs have deformation of 0.01453mm and 0.01453 mm respectively though the generic design has 0.01043 mm deformation. Notably, the 0.5 scale lattice of the robotic arm exhibits a 31.08% higher equivalent stress than the generic design with 29.3%. reduction in mass of the robotic arm. These findings highlight the efficacy of lattice structures for optimizing the robotic arm’s performance, contributing to advancements in power-efficient robot assembly processes.

Contextual Knowledge Framework in CAD Education from the Perspectives of Practicing Engineers

The contemporary industry landscape requires engineering graduates to have expertise in utilizing advanced Computer-Aided Design (CAD) tools. However, prevailing practices reveal a lack of contextual knowledge among Mechanical Engineering undergraduates and fresh graduate engineers in effectively employing 3D CAD modelling software for optimal product design development. Consequently, this study was undertaken to address this issue, with a specific focus on the integration of contextual knowledge into 3D CAD modelling. The study aims to elucidate the fundamental elements of contextual knowledge regularly employed by practicing engineers in their daily design endeavours, specifically in 3D CAD modelling. A transcendental phenomenology approach was used, and four engineers from the engineering department of a shipbuilding company in Peninsular Malaysia were purposefully selected as respondents. The analysis yielded three recurring themes central to the application of contextual knowledge in visualizing and presenting models through 3D CAD modelling: Realization, Design Intention, and Normalization. These elements are pivotal in assisting engineers in contextualizing their design work during the modelling and presentation stages of the new product development process.

Structural and dynamic evaluation of a test bench for mechanical vibrations using finite elements

This numerical study was conducted to assess the experimental bench structure’s adequacy for measuring mechanical vibrations. The bench allows for three types of tests: dynamic imbalance of a single flywheel, dynamic imbalance of dual flywheels, and dynamic imbalance due to defective gears. A CAD (Computer-Aided Design) model of the vibration bench was developed in three distinct configurations. We then conducted structural (static) and dynamic (non-linear) analyses to assess the structural integrity of the bench, its components, and the expected vibration amplitudes during testing. Additionally, the structure’s natural frequencies were determined, and their compatibility with the expected excitation frequencies was confirmed. These assessments were executed using finite element models within the Solidworks Simulation™ framework. The findings indicate that, when designing such machinery, it is crucial to ensure that the vibration modes do not coincide with the excitation frequencies, as this can compromise the experimental results. Consequently, we have proposed and accessed two redesigned versions of the bench to ensure structural integrity and prevent resonance during experimental procedures. The redesigns aim to mitigate the risk of resonance by altering the bench’s structural parameters to shift the natural frequencies away from the range of excitation frequencies. This proactive approach is based on the idea that a big difference between the natural and excitation frequencies lowers the chance of resonance, which makes the results of the experiment more reliable. The enhanced designs were subjected to a series of rigorous simulations to validate their performance, ensuring that they meet the stringent requirements for educational and research applications.

ABC model for cost estimation of custom implants by Additive Manufacturing.

Computer-aided design (CAD) models can now be directly converted into products and structures. One technique to realize such approach is through Additive Manufacturing (AM). AM is relatively new manufacturing technology in which products are manufactured by layering various materials like rubber, metal, ceramic, composites, and polymers. However, the use of this technology requires consideration of its associated cost to ensure its competitiveness. In this paper, a simplified mathematical cost model is suggested. The model considers the main components of costs. The model formula utilizes expenses related to the pre-processing, main processing, and the post-processing operations. To validate the model, it is tested to estimate the cost of medical implants manufacturing using AM technique. In many cases, medical implants require unique or dedicated design for each patient. Hence cost estimation will help to assess and estimate the required financial resources for such operations. A case study is provided in this paper to estimate the manufacturing cost of a finger's phalanges bone, with metal implant using AM technique. The developed model may be described as Activity Based Costing (ABC). The model is introduced to estimate the cost of parts produced using AM technique. Although the model is developed to suit custom implant manufacturing using AM technique, its use may also be adapted to suit the manufacturing of many other parts and products. The developed model is aiming to achieve several tasks namely assigning cost drivers to each activity, estimating the cost of individual actions, allocating overhead expenses, calculating the overall production cost, and establishing an acceptable selling price. It assists companies in computing the cost of custom implants for customers, enhancing the accuracy of production cost estimates, and ultimately boosting profitability.

Automated Assessment Tool for 3D Computer-Aided Design Models

Computer-aided design (CAD) has become an integral part of engineering education, particularly for those studying mechanical engineering. By providing practical skills that are highly valued in the engineering industry, proficiency in CAD systems enhances students’ employability. Generally, CAD systems provide students with the tools and knowledge necessary to excel in their engineering education and future careers. In order to help teachers to give the best training to their students and to make the right evaluations, an automatized tool is needed to support the evaluation of CAD models during training sessions. After an extensive bibliographical search, this paper proposes a CAD Model Automatized Assessment (MAA) Tool for mechanical courses called the CAD MAA Tool. This tool is mainly based on a developed model that takes into account different aspects of modeling, such as geometric, feature-based, and parametric modeling. To correctly evaluate a given part compared to a reference one, the proposed model uses different coefficients fixed by the teacher according to their teaching strategies or course objectives.

Interactive reverse engineering of CAD models

Reverse engineering Computer-Aided Design (CAD) models based on the original geometry is a valuable and challenging research problem that has numerous applications across various tasks. However, previous approaches have often relied on excessive manual interaction, leading to limitations in reconstruction speed. To mitigate this issue, in this study, we approach the reconstruction of a CAD model by sequentially constructing geometric primitives (such as vertices, edges, loops, and faces) and performing Boolean operations on the generated CAD modules. We address the complex reconstruction problem in four main steps. Firstly, we use a plane to cut the input mesh model and attain a loop cutting line, ensuring accurate normals. Secondly, the cutting line is automatically fitted to edges using primitive information and connected to form a primitive loop. This eliminates the need for time-consuming manual selection of each endpoint and significantly accelerates the reconstruction process. Subsequently, we construct the loop of primitives as a chunked CAD model through a series of CAD procedural operations, including extruding, lofting, revolving, and sweeping. Our approach incorporates an automatic height detection mechanism to minimize errors that may arise from manual designation of the extrusion height. Finally, by merging Boolean operations, these CAD models are assembled together to closely approximate the target geometry. We conduct a comprehensive evaluation of our algorithm using a diverse range of CAD models from both the Thingi10K dataset and real-world scans. The results validate that our method consistently delivers accurate, efficient, and robust reconstruction outcomes while minimizing the need for manual interactions. Furthermore, our approach demonstrates superior performance compared to competing methods, especially when applied to intricate geometries.

Enhancing Furniture Manufacturing with 3D Scanning

Product design and manufacturing leverage 3D scanning for various applications. This study aims to investigate the effectiveness of 3D scanning in furniture production by surveying the literature and showcasing four real-world case studies. The literature review reveals that 3D data acquired from real-world objects have applications in research, rapid prototyping, restoration, and preservation of antique furniture, optimizing CNC machining processes, and measuring furniture components for quality control. The case study descriptions demonstrated the circumstances, rationale, and methodology for 3D scanning. All the case studies analyzed stem from the collaboration between the Laboratory for Product Development and Design at the Faculty of Mechanical Engineering at the University of Sarajevo and various furniture production enterprises from Bosnia and Herzegovina. The conclusions highlight that 3D scanning in the furniture sector is advantageous for developing computer-aided design models from early-stage design prototypes, validating the dimensional accuracy of manufactured components by comparing with CAD models, safeguarding and reconstructing vintage furniture, and remanufacturing formerly produced goods that lack complete technical records (reverse engineering).

Method for estimating management points for dimensional quality management in shipbuilding and offshore plant construction using terrestrial laser scanning and a computer-aided design model

This study proposes a method for estimating management points for dimensional quality management in shipbuilding and offshore plant construction using terrestrial laser scanning. The dimensional quality is managed by calculating errors between quality management points in a 3-dimensional (3D) computer-aided design (CAD) model and their corresponding measurement points in a fabricated block. The proposed method utilizes a point cloud of the fabricated block together with a 3D CAD model of the block to estimate the measurement points. To achieve this, global registration, extraction of the region of interest, point segmentation in the region of interest, plane estimation of the segmented points, and estimation of measurement points are performed in an automated manner. To verify the proposed method, it is implemented and experimented with actual ship blocks. The experimental results reveal that the estimated measurement points are within the allowable tolerance of 7 mm.

Novel patient-specific gingival soft-tissue expander development for large bone defects using silicone 3D-printing technology

The current hydrogel self-inflating expander is limited by its volume and linear expansion rate, making it unsuitable for correcting patient-specific large mandibular bone defects in soft-tissue surgeries. This study devised a novel approach for crafting patient-specific gingival tissue expanders for large mandibular bone defects by employing silicone 3D-printing technology. The biocompatible and swellable polymer tablet was compressed and placed into a 3D-printed silicone membrane to evaluate its expansion capability. Two patient-specific large left and right mandibular bone defects with complex geometries were selected to generate defect expander models in a computer-aided design (CAD) software. The swellable tablets were enveloped in the 3D-printed silicone membranes to form soft-tissue expanders, which were then immersed in phosphate-buffered saline (PBS) for 6 weeks to observe their expansion. Results demonstrated that a slot-shaped silicone soft-tissue tablet attained an expansion volume of 1960 mm³. A fourth-degree polynomial fitting curve illustrated slower expansion rates in the initial 2 weeks and achieved complete expansion in about 6 weeks. Patient-specific silicone expander testing indicated less than 2% error in the average expanded volumes of compared to CAD models. The cross-sectional profile of the soft-tissue expanders closely resembled the CAD model. This study demonstrated that biocompatible polymer could be utilized as swellable tablet material and enveloped within a 3D-printed silicone membrane to generate a novel soft-tissue expander that adhered to clinical standards. Additionally, the study validated the feasibility of expanding patient-specific silicone expanders within 6 weeks for repairing large left and right mandibular bone defects.

Adaptive recognition of machining features in sheet metal parts based on a graph class-incremental learning strategy

The integration of computer-aided design (CAD), computer-aided process planning (CAPP), and computer-aided manufacturing (CAM) systems is significantly enhanced by employing deep learning-based automatic feature recognition (AFR) methods. These methods outperform traditional, rule-based approaches, particularly in handling the complexities of intersecting features. However, existing deep learning-based AFR methods face two major challenges. The initial challenge stems from the frequent utilization of voxelized or point-cloud representations of CAD models, resulting in the unfortunate loss of valuable geometric and topological information inherent in original Boundary representation (B-Rep) models. The second challenge involves the limitation of supervised deep learning methods in identifying machining features that are not present in the predefined dataset. This constraint renders them suboptimal for the continually evolving datasets of real industrial scenarios. To address the first challenge, this study introduces a graph-structured language, Multidimensional Attributed Face-Edge Graph (maFEG), crafted to encapsulate the intricate geometric and topological details of CAD models. Furthermore, a graph neural network, Sheet-metalNet, is proposed for the efficient learning and interpretation of maFEGs. To tackle the second challenge, a three-component incremental learning strategy is proposed: an initial phase of pre-training and fine-tuning, a prototype sampling-based replay, and a stage employing knowledge distillation for parameter regularization. The effectiveness of Sheet-metalNet and its complementary incremental learning strategy is evaluated using the open-source MFCAD++ dataset and the newly created SMCAD dataset. Experimental results show that Sheet-metalNet surpasses state-of-the-art AFR methods in machining feature recognition accuracy. Moreover, Sheet-metalNet demonstrates adaptability to dynamic dataset changes, maintaining high performance when encountering newly introduced features, thanks to its innovative incremental learning strategy.

A 3D printing assisted microfluidic absorbance-based measurement system for biological assay

Development of rapid analytical systems utilizing 3D printing is an emerging area of interest with the potential to provide efficient solutions by integrating multidisciplinary technology without compromising the quality of the system. In this study we report the fabrication of a 3D printing assisted microfluidic based absorbance measurement system, leveraging 3D printing along with integrating miniature optical components for the accurate measurement of biological assays. The developed system is rapid, affordable, and compact, through set of computer-aided design models and fusion deposition modeling 3D printing along with relevant electronic circuitry involving optical components like surface mounting devices. The handheld device features a capacitive touchscreen display, programmed to seamlessly perform MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay. The device was employed for assessing the cell viability using Michigan cancer foundation-7 (MCF-7) cell lines over varying concentrations of tamoxifen, reciprocating the MTT assay analysis conducted by using spectrophotometer. The device achieved excellent results which upon comparison with the conventional spectrophotometer-based results have shown a correlation coefficient of 0.98. This compact and rapid absorbance measurement system holds significant potential for evaluating the cytotoxicity of drugs, and further development of innovative analytical devices.