Feature recognition
Encyclopedia
The term "feature" does not imply the same meaning in different engineering disciplines. This has resulted in several ambiguous definitions for feature. A feature, in computer-aided design
(CAD) software, can be called a region of a part with some interesting geometric or topological patterns. This meaning can refer to all sorts of information, such as for example, shape, functional or manufacturing information. Although many types of features have been investigated, the most common type of feature is the form feature, which contains both shape information and parametric information. Examples of form features common in many shape models are round holes, slots, bosses, and pockets.
Features can also be used to represent manufacturing information of the part. Different manufacturing domains require different feature representations. Some of the properties that need to be encoded by features are assembly method, manufacturing process and tolerances. A manufacturing feature can be defined as a form feature, but not necessarily vice versa . Among manufacturing features, the ones received extensive attention are the machining features. A machining feature can be regarded as the volume swept by a cutting tool. In this sense, it is always a negative (subtracted) volume, in contrast with form features that are sometimes positive (added) volumes.
Feature data in a CAD model can be represented either as a collection of surfaces or volumetrically. Surface features are naturally used for example to describe manufacturing tolerances or locating surfaces in fixture design. volumetric features on the other hand, are used in process planning since manufacturing information (particularly in machining) is better portrayed volumetrically .
The first published work on features was for the original boundary representation modelling system, BUILD, and was performed by Lyc Kyprianou . Soon other work followed based on different solid representations. Overviews on the work on features can be found in Shah et al.; Subrahmanyam and Wozny; Salomons et al.
/CAM
system can be fully automated, however, the idea of using manufacturing features to design a part has its own shortcomings : The features used to design the part do not necessarily represent the best way to manufacture it. It is, therefore, the designer's responsibility to evaluate all methods that can produce the part. Furthermore, manufacturing features are not the most natural way of designing a part.
Automatic Feature Recognition (AFR) is regarded as an ideal solution to automate design and manufacturing processes. Successful automation of CAD and CAM systems is a vital connection in building Computer Integrated Manufacturing
(CIM) systems.. This is the part of the FR research that has attracted much of the attention. Another important application of AFR is for manufacturability evaluation The AFR system should be able to interpret the design differently based on alternative features and feed back the manufacturability and cost of those interpretations to the designer.
There is a big stockpile of different AFR techniques that has been proposed for CAD/CAM integration and process planning. Han et al. provides a critical and detailed analysis of some of the existing approaches. The most common methods according to Han et al. range from graph-based algorithms to hint-based and volumetric decomposition techniques. In the graph-based feature recognition, a graph showing the topology of the part (connection of faces) is created. The graph is often attributed, for example the edges are marked as concave or convex . This graph is then analyzed to extract subsets of nodes and arcs that match with any predefined template. This is done by a variety of techniques, including graph iso-morphism algorithms.
Graph based approaches have been criticized for several shortcomings. They fail to account for manufacturability of the recognized features due to their strong reliance on topological patterns rather than geometry. The intersection of features causes an explosion in the number of possible feature patterns that spoils any attempt to formulate feature patterns. To address these difficulties, Vandenbrande and Requicha. proposed to search for "minimal indispensable portion of a feature's boundary", called hints, rather than complete feature patterns. For example, presence of two opposing planar faces is a hint for potential existence of a slot feature. Hints are not necessarily restricted to the part geometry. They can be extracted form tolerances and design attributes as well. For example, "a thread attribute may be taken as a hole hint" . This approach has been more successful in recognizing intersecting features. However, the efficiency of the approach has been argued, as there could be a huge number of traces that won't lead to valid features. Some authors have been in favor of using a hybrid of graph based and hint based FR. Other existing FR approaches are volumetric decomposition , Artificial Neural Networks, and expert systems Babic et al. briefly introduces many of them.
However, building feature recognition systems that function effectively on real industrial products has been elusive. A real product with hundreds of faces and end edges brings almost all the above approaches to a halt due to computational complexity. Furthermore, the features studied in these approaches are usually over simplified. The bulk of the feature recognition literature normally deals with 2.5D features (those made by sweeping a 2D profile along a linear axis). Graph representations, hint definitions or volume decompositions are much more difficult to define for 3D and free form features. The work done by Sundararajan is focused on free form surfaces, but again it is limited in application. Oversimplification is also evident even in the course of 2.5D features. For example, feature recognition algorithms usually assume sharp concave edges in the feature geometry. However, such edges are barely used in real design of mechanical components due to manufacturing constrains. Some of these issues such as the presence of filleted edges and free form surfaces in the model have been studied by Rahmani and Arezoo .
Computer-aided design
Computer-aided design , also known as computer-aided design and drafting , is the use of computer technology for the process of design and design-documentation. Computer Aided Drafting describes the process of drafting with a computer...
(CAD) software, can be called a region of a part with some interesting geometric or topological patterns. This meaning can refer to all sorts of information, such as for example, shape, functional or manufacturing information. Although many types of features have been investigated, the most common type of feature is the form feature, which contains both shape information and parametric information. Examples of form features common in many shape models are round holes, slots, bosses, and pockets.
Features can also be used to represent manufacturing information of the part. Different manufacturing domains require different feature representations. Some of the properties that need to be encoded by features are assembly method, manufacturing process and tolerances. A manufacturing feature can be defined as a form feature, but not necessarily vice versa . Among manufacturing features, the ones received extensive attention are the machining features. A machining feature can be regarded as the volume swept by a cutting tool. In this sense, it is always a negative (subtracted) volume, in contrast with form features that are sometimes positive (added) volumes.
Feature data in a CAD model can be represented either as a collection of surfaces or volumetrically. Surface features are naturally used for example to describe manufacturing tolerances or locating surfaces in fixture design. volumetric features on the other hand, are used in process planning since manufacturing information (particularly in machining) is better portrayed volumetrically .
The first published work on features was for the original boundary representation modelling system, BUILD, and was performed by Lyc Kyprianou . Soon other work followed based on different solid representations. Overviews on the work on features can be found in Shah et al.; Subrahmanyam and Wozny; Salomons et al.
Feature Technology
Work on features (generally called feature technology)can be divided into two rough categories: Design-by-features and Feature recognition. In design-by-features, also known as feature-based design (FBD), feature structures are introduced directly into a model using particular operations or by sewing in shapes. On the other hand, the goal of feature recognition (FR) is to algorithmically extract higher level entities (e.g. manufacturing features) from lower level elements (e.g. surfaces, edges, etc.) of a CAD model.Design by Features
By using features to build up shape models, the design process is made more efficient, because the shape of features can be pre-defined. Features in FBD can be directly associated to manufacturing information so that these information can be retrieved in downstream applications. In this way, an overall CADComputer-aided design
Computer-aided design , also known as computer-aided design and drafting , is the use of computer technology for the process of design and design-documentation. Computer Aided Drafting describes the process of drafting with a computer...
/CAM
Computer-aided manufacturing
Computer-aided manufacturing is the use of computer software to control machine tools and related machinery in the manufacturing of workpieces. This is not the only definition for CAM, but it is the most common; CAM may also refer to the use of a computer to assist in all operations of a...
system can be fully automated, however, the idea of using manufacturing features to design a part has its own shortcomings : The features used to design the part do not necessarily represent the best way to manufacture it. It is, therefore, the designer's responsibility to evaluate all methods that can produce the part. Furthermore, manufacturing features are not the most natural way of designing a part.
Feature Recognition
The classical Kyprianou's method was aimed to encode parts for group technology (GT). The purpose of GT is to systematically classify objects based on their manufacturing method. Kyprianou's work involved classifying faces into primary and secondary groups and then identifying features according to patterns of these primary or secondary faces. A primary face is one with multiple boundaries (also called "hole-loops") or mixed concave and convex boundaries. A concave boundary is a set of concave edges, where the solid angle over the edge is more than 180. Secondary faces are all other faces. Kyprianou's work was continued and extended by Jared et al. to cover a number of important special cases where features interacted.Automatic Feature Recognition (AFR) is regarded as an ideal solution to automate design and manufacturing processes. Successful automation of CAD and CAM systems is a vital connection in building Computer Integrated Manufacturing
Computer Integrated Manufacturing
Computer-integrated manufacturing is the manufacturing approach of using computers to control the entire production process. This integration allows individual processes to exchange information with each other and initiate actions...
(CIM) systems.. This is the part of the FR research that has attracted much of the attention. Another important application of AFR is for manufacturability evaluation The AFR system should be able to interpret the design differently based on alternative features and feed back the manufacturability and cost of those interpretations to the designer.
There is a big stockpile of different AFR techniques that has been proposed for CAD/CAM integration and process planning. Han et al. provides a critical and detailed analysis of some of the existing approaches. The most common methods according to Han et al. range from graph-based algorithms to hint-based and volumetric decomposition techniques. In the graph-based feature recognition, a graph showing the topology of the part (connection of faces) is created. The graph is often attributed, for example the edges are marked as concave or convex . This graph is then analyzed to extract subsets of nodes and arcs that match with any predefined template. This is done by a variety of techniques, including graph iso-morphism algorithms.
Graph based approaches have been criticized for several shortcomings. They fail to account for manufacturability of the recognized features due to their strong reliance on topological patterns rather than geometry. The intersection of features causes an explosion in the number of possible feature patterns that spoils any attempt to formulate feature patterns. To address these difficulties, Vandenbrande and Requicha. proposed to search for "minimal indispensable portion of a feature's boundary", called hints, rather than complete feature patterns. For example, presence of two opposing planar faces is a hint for potential existence of a slot feature. Hints are not necessarily restricted to the part geometry. They can be extracted form tolerances and design attributes as well. For example, "a thread attribute may be taken as a hole hint" . This approach has been more successful in recognizing intersecting features. However, the efficiency of the approach has been argued, as there could be a huge number of traces that won't lead to valid features. Some authors have been in favor of using a hybrid of graph based and hint based FR. Other existing FR approaches are volumetric decomposition , Artificial Neural Networks, and expert systems Babic et al. briefly introduces many of them.
However, building feature recognition systems that function effectively on real industrial products has been elusive. A real product with hundreds of faces and end edges brings almost all the above approaches to a halt due to computational complexity. Furthermore, the features studied in these approaches are usually over simplified. The bulk of the feature recognition literature normally deals with 2.5D features (those made by sweeping a 2D profile along a linear axis). Graph representations, hint definitions or volume decompositions are much more difficult to define for 3D and free form features. The work done by Sundararajan is focused on free form surfaces, but again it is limited in application. Oversimplification is also evident even in the course of 2.5D features. For example, feature recognition algorithms usually assume sharp concave edges in the feature geometry. However, such edges are barely used in real design of mechanical components due to manufacturing constrains. Some of these issues such as the presence of filleted edges and free form surfaces in the model have been studied by Rahmani and Arezoo .
Commercial Feature Recognition Systems
Few commercial feature recognition systems are also available. Though feature recognition technology can be applied for various applications, commercial software have effectively adopted feature recognition technology for recreating the feature tree from imported models so that even the imported models can be edited as if it were a native solid model. Major 3D CAD modelers have Feature Recognition to convert imported 3-D models into native feature based models. CAM software and design for manufacturing software are also built using this feature recognition technology. Few CAD/CAM software have used commercially available third-party feature recognition library, which recognizes various features from 3-D B-Rep models. Separate libraries are available for Design, Manufacturing and Sheet metal applications. Design feature recognition library can identify features such as holes of various types, split holes, hole-chains, fillets, chamfers, cut extrudes, boss extrudes, drafted extrudes, revolved cuts, revolved bosses, ribs, drafts, lofts and sweeps are identified. Manufacturing feature recognition library provides recognition of manufacturing features such as simple holes, tapered holes, counter-bore holes, counter-sunk holes, counter-drilled holes, hole-chains, hole patterns such as linear, rectangular and circular patterns, fillets, chamfers, blind pockets, through pockets, drafted pockets, filleted and chamfered pockets, simple slots, drafted slots, filleted and chamfered slots, islands in pockets and slots, machinable volumes, machinable slabs, multiple intersecting features, axi-symmetric features such as external turned profiles, internal turned profiles, turned grooves such as vee and dovetail grooves, and mill-turn features such as slots and pocket in turned profiles. Sheet metal feature recognition library extracts features from a sheet metal perspective. Various features identified through this library include walls, bends, holes, cutouts, flanged holes, flanged cutouts, notches, open hems, closed hems, teardrop hems, rolled hems (curls), jog flanges, edge flanges, contour flanges, stamps such as louver, lance, bridge, dimple, beads, embosses and ribs. Though such commercial systems can identify a variety of features listed above, further research can be driven to identify feature types that are not identified by such commercial systems. Manufacturing features such as 3-axis and 5-axis feature recognition are generally not available in such commercial systems.External links
- Feature Recognition—The Missing Link To Automated CAM
- Manufacturing feature recognition towards integration with process planning
- Manufacturing feature recognition: a status report
- http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6TYR-4KBVWWS-2&_user=458507&_coverDate=08%2F31%2F2006&_rdoc=3&_fmt=full&_orig=browse&_srch=doc-info(%23toc%235625%232006%23999619991%23629202%23FLA%23display%23Volume)&_cdi=5625&_sort=d&_docanchor=&_ct=10&_acct=C000022002&_version=1&_urlVersion=0&_userid=458507&md5=4f14aa9bb522b395efbb6d3ce22e5528hybrid hint-based and graph-based feature recognition]