Features Of Computer Aided Design Research Articles

A Novel Computational Paradigm for Reconstructing Solid CAD Features from a Segmented Manifold Triangular Mesh

We introduce a novel computational paradigm for reconstructing solid computer-aided design (CAD) features from the surface of a segmented manifold triangular mesh. This paradigm addresses the challenge of capturing high-level design semantics for manifold triangular meshes and facilitates parametric and variational design capabilities. We categorize four prevalent features, namely extrusion, rotation, sweep, and loft, as generalized swept bodies driven by cross-sectional sketches and feature paths, providing a unified mathematical representation for various feature types. The numerical optimization-based approach conducts geometric processing on the segmented manifold triangular mesh patch, extracting cross-sectional sketch curves and feature paths from its surface, and then reconstructing appropriate features using the Open CASCADE kernel. We employ the personalized three-dimensional (3D) printed model as a case study. Parametric and variant designs of the 3D-printed models are achieved through feature reconstruction of the manifold triangular mesh obtained via 3D scanning.

Product Design Cost Estimation for Make-to-Order Industry: A Machine Learning Approach

This research addresses the need for accurate design cost estimation in the Make-To-Order (MTO) industry. The complexity of product customization is key to differentiation. While many studies focus on manufacturing cost estimation, few explore design cost estimation. To improve the accuracy of design cost estimation, this research proposes a new cost driver based on design features available in Computer-Aided Design (CAD) data. The design feature is analyzed to the actual industry cost using machine learning methods, including Artificial Neural Networks (ANNs) and Support Vector Regression (SVR). The cost drivers identified as significant consisted of twenty-six 3D CAD features and four 2D CAD features. The results showed that the ANN models outperformed the SVR models in correctly estimating product design costs, as evidenced by the high R2values in the training and testing phases. The proposed method allows early identification of cost drivers, a significant advantage at the order initiation stage when detailed design features are often ambiguous. The novelty of this research is the use of 3D CAD technology for cost estimation, which quantifies costs based on product design complexity, providing valuable insights into the impact of design adjustments on costs early in the design process. Doi: 10.28991/ESJ-2024-08-03-022 Full Text: PDF

HG-CAD: Hierarchical Graph Learning for Material Prediction and Recommendation in Computer-Aided Design

Abstract To support intelligent computer-aided design (CAD), we introduce a machine learning architecture, namely HG-CAD, that recommends assembly body material through joint learning of body- and assembly-level features using a hierarchical graph representation. Specifically, we formulate the material prediction and recommendation process as a node-level classification task over a novel hierarchical graph representation of CAD models, with a low-level graph capturing the body geometry, a high-level graph representing the assembly topology, and a batch-level mask randomization enabling contextual awareness. This enables our network to aggregate geometric and topological features from both the body and assembly levels, leading to competitive performance. Qualitative and quantitative evaluation of the proposed architecture on the Fusion 360 Gallery Assembly Dataset demonstrates the feasibility of our approach, outperforming selected computer vision and human baselines while showing promise in application scenarios. The proposed HG-CAD architecture that unifies the processing, encoding, and joint learning of multi-modal CAD features indicates the potential to serve as a recommendation system for design automation and a baseline for future work.

Recent advancement in composite material structurally integrated fibre optic damage assessment system

The idea of using fractures as guiding markers for the implantation of optical fibre implants, serving as sensors to detect damage, has been advanced by numerous specialists across numerous industries. This method examines impact damage in depth, including its underlying causes and outcomes. It has been found that crucial matrix cracking caused by stress and shear might act as a warning sign for errors in embedded systems. The discussion includes the most recent developments in sensor technology and their possible uses. The evaluation of any systemic effects that may result from using such a technique is another crucial component. The results of an early-stage assessment system that used fibre optic technology to assess damage in an aircraft wing's leading edge are presented in this study. A thorough literature review is also done to investigate how embedded sensors affect the characteristics of materials. Although it might not have all the features of computer-aided design (CAD) software, its simplicity makes it a good option for making simple prototypes of transparent structures. Before investing money in more complex projects, this economical strategy allows for a preliminary investigation. During conduction of the experiments, our results show that Kevlar/epoxy panels show resistance to damage unless impacts are specifically focused on the implanted optical fibres. The fragility of these optical fibres can be altered strategically to fit particular applications. It demonstrate the capability of modifying the damage sensitivity of optical fibres through our work. This makes it possible for us to identify the root causes and efficiently track the development of damage zones in response to stress loading.

Automated design of additive manufactured flow components with consideration of overhang constraint

When designing parts for additive manufacturing (AM), users must consider manufacturing restrictions specific to the chosen AM production technology. For material extrusion or laser powder bed fusion (L-PBF), users need to follow design rules such as avoiding geometries with critical overhangs. If users create the 3D part geometry manually using computer-aided design (CAD), the consideration of design rules can be challenging and time-consuming. Especially for complex-shaped parts, novice designers may need multiple loops to analyze and modify CAD features for manufacturability. This manual process prevents users to quickly transfer the layout design of a part into the corresponding production-ready 3D part geometry. Therefore, it is highly desirable to automate the manual CAD process, including the consideration of AM restrictions. This work aims to automate the CAD-based design of AM parts with fluid flow channels. For this purpose, the work presents automated procedures that generate and modify design features such that they automatically comply with the AM overhang constraint. The procedures focus on flow components such as hydraulic manifolds and include design features such as support-free flow channels, integrated and sacrificial supports, and other features such as boreholes, interfaces, ribs, and channel branches. To enforce the overhang constraint in the generation of features, users define the part orientation to the build direction, and values for the minimum build angle and maximum allowed diameter of horizontally oriented circular cross-sections. As a benchmark, the work demonstrates the procedures by revisiting an earlier AM hydraulic manifold. Given restrictions of L-PBF of stainless steel, the study uses the procedures to generate manufacturable 3D manifold designs for different part orientations. One of the manifold variants is fabricated to show the manufacturability of the generated 3D part designs. The work finishes by discussing the benefits of the procedures, their transferability, and enhancements to generate manufacturable and functionally optimized designs.

Enhancing CAD-based shape optimisation by automatically updating the CAD model’s parameterisation

This paper presents an approach which increases the flexibility of a computer-aided design (CAD) model by automatically refining its parameterization and adding new CAD features to the model’s feature tree. It aims to overcome the limitations imposed by the choice of parameters used during the initial model creation, which constrains how the model shape can change during design optimisation. Parametric effectiveness compares the maximum performance improvement that can be achieved using a parameterisation strategy to the maximum performance improvement that can be obtained where the model is unconstrained in how it moves. As such, it provides a measure of how good a parameterisation strategy is and allows different strategies to be compared. The change in parametric effectiveness due to inserting multiple different CAD features can be calculated using a single adjoint analysis; therefore, the computational cost is essentially independent of the number of parameterisation strategies being analysed. The described approach can be used to automatically add new features to the model and subsequently allows the use of the newly added parameters, along with the existing parameters to be used for optimization, providing the opportunity for a better performing product. The developed approach is applied on CAD models created in CATIA V5 for 2D and 3D finite element and computational fluid dynamic problems.

Selection of a green manufacturing process based on CAD features

Environmentally conscious manufacturing process (ECMP) has become an obligation to the environment and to the society itself, enforced primarily by governmental regulations and customer perspective on environmental issues. ECMP involves integrating environmental thinking into new product development. This is especially true in the computer-aided design (CAD) phase which is the last phase in the design process. At this stage, more than 80 % of choices are done. Feature technology (FT), the core of the CAD phase, is then used to integrate environmental aspects. Also, integrations realized on CAD systems, such as computer-aided manufacturing (CAM), computer-aided process plan (CAPP), and product life management (PLM), are explored to eco-design products. This paper presents a new methodology for the selection of a green manufacturing process based on CAD features and CAD/CAM/CAPP/PLM integrations. Firstly, we present an overview of works using FT in the CAD phase to reduce the environmental impacts of a manufacturing process. Secondly, we propose an approach based on FT for selecting an ECMP to promote a new simple eco-design tool which helps inexperienced eco-designers. Finally, a case study is considered to validate the proposed approach and results are commented.

Ecodesigning with CAD Features: Analysis and Proposals

The integration of environmental aspects in design frameworks has become a necessity for manufacturers to maintain their market position. This is especially true in the Computer Aided Design (CAD) phase, which is the last phase in the design process. At this stage, more than 80% of choices have been made. However, the environmental impacts generated by the remaining choices are significant. Features Technology (FT), the core of the CAD phase, is used to integrate environmental aspects. This paper presents a literature review of different works based on FT to ecodesign products. First, we present an overview of features in CAD systems. Second, we present a critical review of works done on ecodesigning with features that we divide into two subsections: the first one concerns CAD-Life Cycle Assessment (LCA) integration (methodologies, prototype tools, and commercial tools), and the second one, works using FT in CAD phase to reduce the environmental impact of one life cycle stage such as material selection or manufacturing. Finally, we propose an approach based on FT for ecodesigning products to promote simple new ecodesign tools which will help the inexperienced designer.

Computer aided design of underground excavations in jointed rock

Stability analysis of rock blocks that may be formed by excavating jointed rock masses is traditionally performed using the stereographic projection technique. However, such technique is prone to human errors, and existing alternative analytical methods are rather tedious and time consuming. In this paper, a computer aided approach is proposed with the prime objective that the entire analysis is automated on a microcomputer. Computer aided design features such as determination of discontinuity orientation based on borehole data, stability analysis of rock blocks involving multiple discontinuity sets, and determination of optimum excavation direction, optimum plunge of rock reinforcement and the most critical direction of earthquake force are provided.