Augmented Convex Decomposition Using Incremental Update for Recognition of Form Features

1996 ◽  
Author(s):  
Frédéric Parienté ◽  
Yong Se Kim
Keyword(s):  
Feature Recognition ◽  
Feature Representation ◽  
Boundary Representation ◽  
Central Feature ◽  
Decomposition Tree ◽  
Active Components ◽  
Convex Decomposition ◽  
Volumetric Representation ◽  
Incremental Update ◽  
Form Features

Abstract Alternating Sum of Volumes with Partitioning (ASVP) decomposition is a volumetric representation of a part obtained from its boundary representation that organizes faces of the part in an outside-in hierarchy. ASVP decomposition combines Alternating Sum of Volumes (ASV) decomposition, using convex hulls and set difference operations, and remedial partitioning, using cutting operations and concave edges. A Form Feature Decomposition (FFD) which can serve as a central feature representation for various applications is obtained from ASVP decomposition. The incremental update of convex decomposition is achieved by exploiting its hierarchical structure. For a connected incremental design change, the active components that only need to be updated are localized in a subtree of the decomposition tree called active subtree. Then, the new decomposition is obtained by only updating the active subtree in the old decomposition. In this paper, we present a new decomposition, called Augmented Alternating Sum of Volumes with Partitioning (AASVP) decomposition, that is incrementally constructed using ASV incremental update as a local operation on a decomposition tree. AASVP provides an improved feature recognition capability as it localizes the effect of the change in the decomposition tree, avoids excessive remedial partitioning and catches the designer’s intent in feature editing. AASVP differs from ASVP at the remedial-partitioning nodes by partitioning less. The current remedial partitioning method could be improved such that AASVP decomposition can be constructed directly from the solid model.

Incremental and Localized Update of Convex Decomposition for Form Feature Decomposition

1995 ◽  
Author(s):  
Frédéric Parienté ◽  
Yong Se Kim
Keyword(s):  
Design Procedure ◽  
Feature Representation ◽  
Boundary Representation ◽  
Central Feature ◽  
Decomposition Tree ◽  
Active Components ◽  
Support Design ◽  
Convex Decomposition ◽  
Incremental Update ◽  
Form Feature

Abstract Alternating Sum of Volumes with Partitioning (ASVP) decomposition is a volumetric representation of a part obtained from its boundary representation, organizing the faces of the part in an outside-in hierarchy. A Form Feature Decomposition (FFD) which can serve as a central feature representation for various applications is obtained from ASVP decomposition. In a typical design procedure, part designs are analyzed for a given application context and redesign suggestions are made; design changes are then propagated from one context to another through the FFD. Thus, incremental update capability is crucial to support design refinement. FFD incremental update can be achieved by incrementally updating the corresponding ASVP decomposition. This paper describes how ASVP incremental update is achieved by exploiting the hierarchical structure of the decomposition. ASVP incremental update seeks to determine the new decomposition tree of a part, after its boundary representation is changed, without computing it from scratch. Based on local face alteration and extremality considerations, we look for active components that need to be updated. For a connected delta volume, defined as the volumetric difference between the old and new parts, active components are localized in a subtree of the decomposition tree, called active subtree. Then, the new decomposition is obtained by only updating the active subtree using localized ASVP decomposition operations.

1997 Status of the Form Feature Recognition Method Using Convex Decomposition

1997 ◽  
Author(s):  
Eric Wang ◽  
Yong Se Kim
Keyword(s):  
Feature Recognition ◽  
Feature Representation ◽  
Boundary Representation ◽  
Current Status ◽  
Recognition Method ◽  
Convex Decomposition ◽  
Feature Representations ◽  
Negative Feature ◽  
Form Features ◽  
Form Feature

Abstract This paper describes the current status of our feature recognition method using a convex decomposition method called Alternating Sum of Volumes with Partitioning (ASVP). Volumetric form features are recognized from a part’s boundary representation by applying combination operations to the ASVP decomposition of the part to obtain a Form Feature Decomposition (FFD). The FFD can be post-processed to obtain application-specific feature representations; in particular, the conversion to the Negative Feature Decomposition (NFD), a machining feature representation, is described. Our domain of recognizable parts includes those having planar and cylindrical surfaces such that all cylindrical surfaces are bounded by straight edges and circular arcs, or are blending surfaces resulting from applying constant-radius blending to the part. We report the results of applying our method to the test parts for the 1997 Computers in Engineering Feature Panel Session.

Handling Blending Features in Form Feature Recognition Using Convex Decomposition

1994 ◽  
Author(s):  
Sreekumar Menon ◽  
Yong Se Kim
Keyword(s):  
Feature Recognition ◽  
Boundary Representation ◽  
Recognition Method ◽  
Geometric Information ◽  
Polyhedral Model ◽  
Curved Boundary ◽  
Convex Decomposition ◽  
Geometric Objects ◽  
Form Features ◽  
Form Feature

Abstract Form features intrinsic to the product shape can be recognized using a convex decomposition called Alternating Sum of Volumes with Partitioning (ASVP). However, the domain of geometric objects to which ASVP decomposition can be applied had been limited to polyhedral solids due to the difficulty of convex hull construction for solids with curved boundary faces. We develop an approach to extend the geometric domain to solids having cylindrical and blending features. Blending surfaces are identified and removed from the boundary representation of the solid, and a polyhedral model of the unblended solid is generated while storing the cylindrical geometric information. From the ASVP decomposition of the polyhedral model, polyhedral form features are recognized. Form feature decomposition of the original solid is then obtained by reattaching the stored blending and cylindrical information to the form feature components of its polyhedral model. In this way, a larger domain of solids can be covered by the feature recognition method using ASVP decomposition. In this paper, handling of blending features in this approach is described.

Form Feature Recognition by Convex Decomposition

1991 ◽  
Author(s):  
Yong Se Kim
Keyword(s):  
Decomposition Method ◽  
Feature Recognition ◽  
Convex Hulls ◽  
Convex Decomposition ◽  
Geometric Objects ◽  
Volumetric Representation ◽  
Feature Information ◽  
Form Features ◽  
Form Feature

Abstract A convex decomposition method, called Alternating Sum of Volumes (ASV), uses convex hulls and set difference operations. ASV decomposition may not converge, which severely limits the domain of geometric objects that can be handled. By combining ASV decomposition and remedial partitioning for the non-convergence, we have proposed a convergent convex decomposition called Alternating Sum of Volumes with Partitioning (ASVP). In this article, we describe how ASVP decomposition is used for recognition of form features. ASVP decomposition can be viewed as a hierarchical volumetric representation of form features. Adjacency and interaction between form features are inherently represented in the decomposition in a hierarchical way. Several methods to enhance the feature information obtained by ASVP decomposition are also discussed.

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.

Conversions in Form Feature Recognition Using Convex Decomposition

1992 ◽  
Author(s):  
Yong Se Kim ◽  
Kenneth D. Roe
Keyword(s):  
Decomposition Method ◽  
Feature Recognition ◽  
Inductive Learning ◽  
The Other ◽  
New Combination ◽  
Convex Decomposition ◽  
Feature Information ◽  
Form Features ◽  
Primal And Dual ◽  
Form Feature

Abstract A convergent convex decomposition method called Alternating Sum of Volumes with Partitioning (ASVP) has been used to recognize volumetric form features intrinsic to the product shape. The recognition process is done by converting the ASVP decomposition into a form feature decomposition by successively applying combination operations on ASVP components. In this paper, we describe a method to generate new combination operations through inductive learning from conversion processes of primal and dual ASVP decompositions when one decomposition produces more desirable form feature information than the other.

A Convergent Convex Decomposition of Polyhedral Objects

1992 ◽  
Vol 114 (3) ◽  
pp. 468-476 ◽  
Author(s):  
Yong Se Kim ◽  
D. J. Wilde
Keyword(s):  
Decomposition Method ◽  
Feature Recognition ◽  
Current Method ◽  
Convex Decomposition ◽  
Object Based ◽  
Geometric Objects ◽  
Polyhedral Objects ◽  
Volumetric Representation ◽  
Boundary Information ◽  
The Given

A convex decomposition method, called Alternating Sum of Volumes (ASV), uses convex hulls and set difference operations. ASV decomposition, however, may not converge, which severely limits the domain of geometric objects that the current method can handle. We investigate the cause of non-convergence and present a remedy; we propose a new convex decomposition called Alternating Sum of Volumes with Partitioning (ASVP) and prove its convergence. ASVP decomposition is a hierarchical volumetric representation which is obtained from the boundary information of the given object based on convexity. As an application, from feature recognition by ASVP decomposition if briefly discussed.

Feature Recognition by Volume Decomposition Using Half-Space Partitioning

1994 ◽  
Author(s):  
Yan Shen ◽  
Jami J. Shah
Keyword(s):  
Half Space ◽  
Decomposition Method ◽  
Feature Recognition ◽  
Boundary Representation ◽  
Solid Model ◽  
Space Partitioning ◽  
Machining Features ◽  
Convex Decomposition ◽  
Volume Decomposition ◽  
Convex Cell

Abstract A volume decomposition method called minimum convex decomposition by half space partitioning has been developed to recognize machining features from the boundary representation of the solid model. First, the total volume to be removed by machining is obtained by subtracting the part from the stock. This volume is decomposed into minimum convex cells by half space partitioning at every concave edge. A method called maximum convex cell composition is developed to generate all alternative volume decompositions. The composing sub volumes are classified based on degree of freedom analysis. This paper focuses on the first part of our system, i.e., the volume decomposition. The other part of the work will be submitted for publication at a leter date.

Feature-Based Machining Precedence Reasoning and Sequence Planning

1998 ◽  
Author(s):  
Yong Se Kim ◽  
Eric Wang ◽  
Choong Soo Lee ◽  
Hyung Min Rho
Keyword(s):  
Feature Recognition ◽  
Search Space ◽  
Machining Process ◽  
Planning System ◽  
Process Information ◽  
Computer Aided Process Planning ◽  
Sequence Planning ◽  
Precedence Relations ◽  
Feature Based ◽  
Form Features

Abstract This paper presents a feature-based method to support machining sequence planning. Precedence relations among machining operations are systematically generated based on geometric information, tolerance specifications, and machining expertise. The feature recognition method using Alternating Sum of Volumes With Partitioning (ASVP) Decomposition is applied to obtain a Form Feature Decomposition (FFD) of a part model. Form features are classified into a taxonomy of atomic machining features, to which machining process information has been associated. Geometry-based precedence relations between features are systematically generated using the face dependency information obtained by ASVP Decomposition and the features’ associated machining process information. Multiple sets of precedence relations are generated as alternative precedence trees, based on the feature types and machining process considerations. These precedence trees are further enhanced with precedence relations from tolerance specifications and machining expertise. Machining sequence planning is performed for each of these precedence trees, applying a matrix-based method to reduce the search space while minimizing the number of tool changes. The precedence trees may then be evaluated based on machining cost and other criteria. The precedence reasoning module and operation sequence planning module are currently being implemented within a comprehensive Computer-Aided Process Planning system.

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