Computer-aided microfluidics (CAMF): from digital 3D-CAD models to physical structures within a day

2013 ◽  
Vol 15 (5) ◽  
pp. 625-635 ◽  
Author(s):  
Ansgar Waldbaur ◽  
Bernardo Carneiro ◽  
Paul Hettich ◽  
Elisabeth Wilhelm ◽  
Bastian E. Rapp
Keyword(s):  
3D Cad ◽  
Computer Aided ◽  
Cad Models

scholarly journals Automatized Evaluation of Students’ CAD Models

2021 ◽  
Vol 11 (4) ◽  
pp. 145
Author(s):  
Nenad Bojcetic ◽  
Filip Valjak ◽  
Dragan Zezelj ◽  
Tomislav Martinec
Keyword(s):  
Computer Aided Design ◽  
Three Dimensional ◽  
Computer Application ◽  
Test Cases ◽  
Cad Model ◽  
Computer Solution ◽  
3D Cad ◽  
Computer Aided ◽  
Cad Models ◽  
Aided Design

The article describes an attempt to address the automatized evaluation of student three-dimensional (3D) computer-aided design (CAD) models. The driving idea was conceptualized under the restraints of the COVID pandemic, driven by the problem of evaluating a large number of student 3D CAD models. The described computer solution can be implemented using any CAD computer application that supports customization. Test cases showed that the proposed solution was valid and could be used to evaluate many students’ 3D CAD models. The computer solution can also be used to help students to better understand how to create a 3D CAD model, thereby complying with the requirements of particular teachers.

Creating by Imagining: Use of Natural and Intuitive BCI in 3D CAD Modeling

2013 ◽  
Author(s):  
Sree Shankar S. ◽  
Anoop Verma ◽  
Rahul Rai
Keyword(s):  
3D Modeling ◽  
Signal Acquisition ◽  
Natural Interaction ◽  
Brain Wave ◽  
3D Cad ◽  
Facial Movements ◽  
Brain Signals ◽  
Computer Aided ◽  
Cad Models ◽  
Google Sketchup

Since its inception, computer aided 3D modeling has primarily relied on the Windows, Icons, Menus, Pointer (WIMP) user interface. WIMP has rarely been able to tap into the natural intuitiveness and imagination of the user which accompanies any design process. Brain-computer interface (BCI) is a novel modality that uses the brain signals of a user to enable natural and intuitive interaction with an external device. The BCI’s potential to become an important modality of natural interaction for 3D modeling is almost limitless and unexplored. In theory, using BCI one can create any 3D model by simply thinking about it. This paper presents a basic framework for using BCI as an interface for computer aided 3D modeling. This framework involves the task of recording and recognizing electroencephalogram (EEG) brain wave patterns and electromyogram (EMG) signals corresponding to facial movements. The recognized EEG/EMG brain signals and associated keystrokes are used to activate/control different commands of a CAD package. Eight sample CAD models are created using the Emotiv EEG head set based BCI interface and Google SketchUp and presented to demonstrate the efficacy of the developed system based on the framework. To further exhibit BCI’s usability, human factor studies have been carried out on subjects from different backgrounds. Based on preliminary results, it is concluded that EEG/EMG based BCI is suitable for computer aided 3D modeling purposes. Issues in signal acquisition, system flexibility, integration with other modalities, and data collection are also discussed.

A Methodology for Building Up an Infrastructure of Haptically Enhanced Computer-Aided Design Systems

2008 ◽  
Vol 8 (4) ◽  
Author(s):  
Weihang Zhu
Keyword(s):  
Computer Aided Design ◽  
Force Feedback ◽  
Haptic Rendering ◽  
Haptic Interface ◽  
Cad Systems ◽  
3D Cad ◽  
Cad System ◽  
Computer Aided ◽  
Cad Models ◽  
Aided Design

This paper presents an infrastructure that integrates a haptic interface into a mainstream computer-aided design (CAD) system. A haptic interface, by providing force feedback in human-computer interaction, can improve the working efficiency of CAD/computer-aided manufacturing (CAM) systems in a unique way. The full potential of the haptic technology is best realized when it is integrated effectively into the product development environment and process. For large manufacturing companies this means integration into a commercial CAD system (Stewart, et al., 1997, “Direct Integration of Haptic User Interface in CAD Systems,” ASME Dyn. Syst. Control Div., 61, pp. 93–99). Mainstream CAD systems typically use constructive solid geometry (CSG) and boundary representation (B-Rep) format as their native format, while internally they automatically maintain triangulated meshes for graphics display and for numerical evaluation tasks such as surface-surface intersection. In this paper, we propose to render a point-based haptic force feedback by leveraging built-in functions of the CAD systems. The burden of collision detection and haptic rendering computation is alleviated by using bounding spheres and an OpenGL feedback buffer. The major contribution of this paper is that we developed a sound structure and methodology for haptic interaction with native CAD models inside mainstream CAD systems. We did so by analyzing CAD application models and by examining haptic rendering algorithms. The technique enables the user to directly touch and manipulate native 3D CAD models in mainstream CAD systems with force/touch feedback. It lays the foundation for future tasks such as direct CAD model modification, dynamic simulation, and virtual assembly with the aid of a haptic interface. Hence, by integrating a haptic interface directly with mainstream CAD systems, the powerful built-in functions of CAD systems can be leveraged and enhanced to realize more agile 3D CAD design and evaluation.

Graph-Based Simplification of Feature-Based Three-Dimensional Computer-Aided Design Models for Preserving Connectivity

2015 ◽  
Vol 15 (3) ◽  
Author(s):  
Soonjo Kwon ◽  
Byung Chul Kim ◽  
Duhwan Mun ◽  
Soonhung Han
Keyword(s):  
Computer Aided Design ◽  
Three Dimensional ◽  
Evaluation Metrics ◽  
Prototype System ◽  
Cad Model ◽  
3D Cad ◽  
Computer Aided ◽  
Cad Models ◽  
Feature Based ◽  
Aided Design

The required level of detail (LOD) of a three-dimensional computer-aided design (3D CAD) model differs according to its purpose. It is therefore important that users are able to simplify a highly complex 3D CAD model and create a low-complexity one. The simplification of a 3D CAD model requires the application of a simplification operation and evaluation metrics for the geometric elements of the 3D CAD model. The evaluation metrics are used to select those elements that should be removed. The simplification operation removes selected elements in order to simplify the 3D CAD model. In this paper, we propose the graph-based simplification of feature-based 3D CAD models using a method that preserves connectivity. First, new evaluation metrics that consider the discrimination priority among several simplification criteria are proposed. Second, a graph-based refined simplification operation that prevents the separation of a feature-based 3D CAD model into multiple volumes is proposed. Finally, we verify the proposed method by implementing a prototype system and performing simplification experiments using feature-based 3D CAD models.

MVCNN++: Computer-Aided Design Model Shape Classification and Retrieval Using Multi-View Convolutional Neural Networks

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Atin Angrish ◽  
Akshay Bharadwaj ◽  
Binil Starly
Keyword(s):  
Neural Networks ◽  
Computer Aided Design ◽  
Training Data ◽  
Shape Classification ◽  
Training Time ◽  
3D Cad ◽  
Computer Aided ◽  
Cad Models ◽  
Engineering Models ◽  
Aided Design

Abstract Deep neural networks (DNNs) have been successful in classification and retrieval tasks of images and text, as well as in the graphics domain. However, these DNNs algorithms do not translate to 3D engineering models used in the product design and manufacturing. This paper studies the use of multi-view convolutional neural network (MVCNN) algorithm enhanced by the addition of engineering metadata, for classification and retrieval of 3D computer-aided design (CAD) models. The proposed algorithm (MVCNN++) builds on the MVCNN algorithm with the addition of part dimension data, improving its efficacy for manufacturing part classification and yielding an improvement in classification accuracy of 5.8% over the original version. Unlike datasets used for 3D shape classification and retrieval in the computer graphics domain, engineering level description of 3D CAD models do not yield themselves to neat, distinct classes. Techniques such as relaxed-classification and prime angled cameras for capturing feature detail were used to address training data capture issues specific to 3D CAD models, along with the use of transfer learning to reduce training time. Our study has shown that DNNs can be used to search and discover relevant 3D engineering models in large public repositories, making 3D models accessible to the community.

scholarly journals FROM CAD TO PHYSICS-BASED DIGITAL TWIN: FRAMEWORK FOR REAL-TIME SIMULATION OF VIRTUAL PROTOTYPES

2020 ◽  
Vol 1 ◽  
pp. 335-344
Author(s):  
J. G. Pereira ◽  
A. Ellman
Keyword(s):  
Product Development ◽  
Conceptual Design ◽  
Engineering Process ◽  
Digital Twin ◽  
3D Cad ◽  
Time Simulation ◽  
Computer Aided ◽  
Engineering Work ◽  
Cad Models ◽  
Virtual Prototypes

AbstractEngineering work is mostly done in 3D CAD software throughout the engineering process from conceptual design and layout of products. Physics-Based Virtual Prototypes are very valuable addition on Computer Aided Engineering enabling product development simulators, training simulators and digital twin concept in product lift-cycle process. In this work, we present a framework, how such virtual prototypes can be developed from 3D CAD models with meaningful effort.

Direct Touch and Manipulation of Native 3D Models With Haptic Interface in the Mainstream CAD Systems

2006 ◽  
Author(s):  
Weihang Zhu ◽  
Yuan-Shin Lee
Keyword(s):  
Manufacturing Systems ◽  
Manufacturing Industry ◽  
Haptic Interface ◽  
New Techniques ◽  
Cad Systems ◽  
3D Cad ◽  
Computer Aided ◽  
Design And Manufacturing ◽  
Cad Cam ◽  
Cad Models

This paper presents new techniques for integrating haptic interface with mainstream CAD systems. Haptic interface, by providing force feedback in human-computer interaction, can improve the working efficiency of CAD/CAM (Computer-aided Design and Manufacturing) systems in a unique way. Compared to the test beds and prototypes in the past research, the new techniques would allow the user to directly touch and manipulate native 3D CAD models in mainstream CAD/CAM systems with force/touch feedback. Contrary to the common thoughts among the research community, the presented techniques eliminate time- and resource-consuming pre-processing or duplication of the CAD models data, such as conversion to volumetric models or triangulated mesh models. It would allow the CAD/CAM user to evaluate or assembly the CAD models with force/touch feedback, and meanwhile modify the design without having to resort to other geometry representation method or systems. By integrating haptic interface directly with mainstream CAD systems, the powerful built-in functions of CAD systems can be leveraged and enhanced to realize more agile 3D CAD design and evaluation, which will eventually lead to a more competitive design and manufacturing industry. This research would open up a new direction of haptic application research in CAD/CAM area. The presented techniques can be used in tasks such as digital mockup, virtual assembly, virtual prototyping, computer-aided product design and manufacturing.

scholarly journals Practical method for the fast generation of a CAM model for jet engine parts

2021 ◽  
Vol 13 (3) ◽  
pp. 168781402110027
Author(s):  
Byung Chul Kim ◽  
Ilhwan Song ◽  
Duhwan Mun
Keyword(s):  
Computer Aided Design ◽  
Feature Recognition ◽  
Practical Method ◽  
Numerical Control ◽  
Cnc Machine Tools ◽  
Cnc Machine ◽  
Jet Engine ◽  
Computer Aided ◽  
Cad Models ◽  
Cam Model

Manufacturers of machine parts operate computerized numerical control (CNC) machine tools to produce parts precisely and accurately. They build computer-aided manufacturing (CAM) models using CAM software to generate code to control these machines from computer-aided design (CAD) models. However, creating a CAM model from CAD models is time-consuming, and is prone to errors because machining operations and their sequences are defined manually. To generate CAM models automatically, feature recognition methods have been studied for a long time. However, since the recognition range is limited, it is challenging to apply the feature recognition methods to parts having a complicated shape such as jet engine parts. Alternatively, this study proposes a practical method for the fast generation of a CAM model from CAD models using shape search. In the proposed method, when an operator selects one machining operation as a source machining operation, shapes having the same machining features are searched in the part, and the source machining operation is copied to the locations of the searched shapes. This is a semi-automatic method, but it can generate CAM models quickly and accurately when there are many identical shapes to be machined. In this study, we demonstrate the usefulness of the proposed method through experiments on an engine block and a jet engine compressor case.

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