scholarly journals Manufacturing Task Description for Robotic Welding and Automatic Feature Recognition on Product CAD Models

Procedia CIRP ◽  
2017 ◽  
Vol 60 ◽  
pp. 122-127 ◽  
Author(s):  
Alexander Kuss ◽  
Thomas Dietz ◽  
Konstantin Ksensow ◽  
Alexander Verl
Keyword(s):  
Feature Recognition ◽  
Robotic Welding ◽  
Task Description ◽  
Cad Models ◽  
Automatic Feature Recognition

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.

Graph Representation of 3D CAD Models for Machining Feature Recognition With Deep Learning

2021 ◽  
Author(s):  
Weijuan Cao ◽  
Trevor Robinson ◽  
Hua Yang ◽  
Flavien Boussuge ◽  
Andrew Colligan ◽  
...  
Keyword(s):  
Deep Learning ◽  
Feature Recognition ◽  
Graph Representation ◽  
3D Cad ◽  
Machining Feature ◽  
Cad Models

Using Automatic Feature Recognition to Interface CAD to CAPP

1992 ◽  
Author(s):  
Eric Wang
Keyword(s):  
Pattern Matching ◽  
Feature Recognition ◽  
Scale Up ◽  
Fundamental Difference ◽  
Computer Integrated Manufacturing ◽  
Semantic Gap ◽  
Recognition Method ◽  
Computer Aided Process Planning ◽  
Computer Aided ◽  
Automatic Feature Recognition

Abstract Interfacing CAD to CAPP (computer-aided process planning) is crucial to the eventual success of a fully-automated computer-integrated manufacturing (CIM) environment. Current CAD and CAPP systems are separated by a “semantic gap” that represents a fundamental difference in the ways in which they represent information. This semantic gap makes the interfacing of CAD to CAPP a non-trivial task. This paper argues that automatic feature recognition is an indispensable technique in interfacing CAD to CAPP. It then surveys the current literature on automatic feature recognition methods and systems, and analyzes their suitability as CAD/CAPP interfaces. It also describes a relatively recent automatic feature recognition method based on volumetric decomposition, using Kim’s alternating sum of volumes with partitioning (ASVP) algorithm. The paper’s main theses are: (1) that most previous automatic feature recognition approaches are ultimately based on pattern-matching; (2) that pattern-matching approaches are unlikely to scale up to the real world; and (3) that volumetric decomposition is an alternative to pattern-matching that avoids its shortcomings. The paper concludes that automatic feature recognition by volumetric decomposition is a promising approach to the interfacing of CAD to CAPP.

Knowledge acquisition techniques for feature recognition in CAD models

2007 ◽  
Vol 19 (1) ◽  
pp. 21-32 ◽  
Author(s):  
Emmanuel Brousseau ◽  
Stefan Dimov ◽  
Rossitza Setchi
Keyword(s):  
Knowledge Acquisition ◽  
Feature Recognition ◽  
Cad Models

A Generalized Method for the Classification and Extraction of Form Features

1996 ◽  
Author(s):  
A. Z. Qamhiyah ◽  
R. D. Venter ◽  
B. Benhabib
Keyword(s):  
Feature Extraction ◽  
Sequential Extraction ◽  
Feature Recognition ◽  
Boundary Elements ◽  
Geometric Reasoning ◽  
Extraction Techniques ◽  
Planar Surfaces ◽  
Cad Models ◽  
Extraction Stage ◽  
Form Features

Abstract Feature-extraction techniques address the primary limitation of feature-recognition approaches, namely their lack of generalization. This paper presents a boundary-based procedure for the classification and sequential extraction of form features from the CAD models of objects with planar surfaces. Form features are first classified based on their effect on the boundary elements of a basic shape. Geometric reasoning is then used to obtain generalized properties of the form-features’ classes. Finally, form-features’ classes are sequentially extracted based on the recognized properties. At the onset of each extraction stage, the object is viewed as an initial basic shape that has been iteratively altered through the introduction of form features.

Geometric Reasoning for the Coding of CAD Models

1995 ◽  
Author(s):  
A. Z. Qamhiyah ◽  
B. Benhabib ◽  
R. D. Venter
Keyword(s):  
Computer Aided Design ◽  
Feature Recognition ◽  
Effective Means ◽  
Boundary Representation ◽  
Cad Model ◽  
Cad System ◽  
Cad Models ◽  
Form Features ◽  
Feature Based Design ◽  
Design Retrieval

Abstract Many of today’s concurrent product-development cycles depend on the utilization of intelligent Computer-Aided Design (CAD) systems. Thus, it would be essential to provide CAD users with effective means for interacting with the CAD system and its database. This paper addresses the development of a boundary-based coding procedure for CAD models. Coding the geometric and processing characteristics of objects, based on their CAD model representation, has been long recognized as an effective approach that allows convenient design retrieval on the one hand and process-planning automation on the other. Our work is based on the assumption that form features are recognizable and extractable from the CAD model by current feature-recognition, feature extraction and feature-based-design approaches. The coding procedure is applicable to the boundary representation of the object and its extracted form features.

Partial Matching Algorithm of 3D CAD Models Based on the Constraints of Transition Features

2010 ◽  
Vol 97-101 ◽  
pp. 3371-3375
Author(s):  
Kai Xing Zhang ◽  
Shu Sheng Zhang ◽  
Xiao Liang Bai
Keyword(s):  
Feature Recognition ◽  
Graph Isomorphism ◽  
Topological Information ◽  
Machining Features ◽  
New Approach ◽  
Partial Matching ◽  
Mechanical Parts ◽  
3D Cad ◽  
Matching Efficiency ◽  
Cad Models

The CAD models of mechanical parts usually have many blends and chamfers, and the existence of these machining features can greatly change the geometric and topological patterns of the CAD models, but the existing partial matching algorithms cannot match the CAD models which contain machining features such as blends and chamfers. In this paper, a new approach to partial matching based on the constraints of transition features is proposed. Firstly, the transition features are identified by feature recognition, and then these machining features are removed to eliminate the impacts to the geometric and topological information of the CAD models, and the attribute adjacent graph is reconstructed, finally, the sub-graph isomorphism approach is used to achieve the partial matching. Experimental results show that this method can achieve partial matching of CAD models which contain machining features such as blends and chamfers, and the matching efficiency can satisfy the requirement of the engineering retrieval.

On the Development of Virtual Inner Loops for Feature Recognition

2015 ◽  
Vol 656-657 ◽  
pp. 761-767 ◽  
Author(s):  
Ming Hsuan Wang ◽  
Jiing Yih Lai ◽  
Yu Kai Chiu ◽  
Chia Hsiang Hsu ◽  
Yao Chen Tsai ◽  
...  
Keyword(s):  
Feature Recognition ◽  
Typical Feature ◽  
Industrial Applications ◽  
Extensive Study ◽  
Cad Model ◽  
Recognition Algorithms ◽  
Single Face ◽  
Cad Models

Typical feature recognition algorithms in industrial applications are primarily used for solving cases where a feature locates on a single face only. A feature locating on multiple surfaces is quite common in real CAD models, but it has not been received extensive study yet. The reason is because the loop data in current B-rep model is limited to a face only. The aim of this study is to develop a method to search for all kinds of inner loops on a CAD model, including the ones within a face and those across multiple faces. These inner loops are called virtual inner loops because they do not exist in current B-rep model. Several realistic examples are also presented to illustrate the meaning and feasibility of the proposed method.

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