2004•ACM Symposium on Solid Modeling and ApplicationsRequires access

Integrated feature-based and geometric CAD data exchange

Steven Spitz, Ari Rappoport

Open publisher page 46 citations

Abstract

Data exchange between CAD systems is an extremely important solid modeling concept, fundamental both for the theory of the field and for its practical applications. The two main data exchange (DE) paradigms are geometric and parametric DE. Geometric DE is the ordinary method, in which the boundary representation of the object is exchanged. Parametric (or feature-based) DE is a novel method where, given a parametric history (feature) graph in a source system, the goal is to construct a graph in the target system that results in similar geometry while preserving as much parametric information as possible. Each method has its uses and associated problems.In this paper, we introduce Geometry Per Feature (GPF), a method for integration of parametric and geometric data exchange at the single part (object) level. Features can be exchanged either parametrically or geometrically, according to user guidelines and system constraints. At the target system, the resulting model is represented using a history tree, regardless of the amount of original parametric features that have been rewritten as geometric ones. Using this method we maximize the exchange of overall parametric data and overcome one of the main stumbling blocks for feature-based data exchange.

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What this paper is about

Data exchange between CAD systems is an extremely important solid modeling concept, fundamental both for the theory of the field and for its practical applications. The two main data exchange (DE) paradigms are geometric and parametric DE. Geometric DE is the ordinary method, in which the boundary representation of the object is exchanged. Parametric (or feature-based) DE is a novel method where, given a parametric history (feature) graph in a source system, the goal is to construct a graph in the target system that results in similar geometry while preserving as much parametric information as possible. Each method has its uses and associated problems.In this paper, we introduce Geometry Per Feature (GPF), a method for integration of parametric and geometric data exchange at the single part (object) level. Features can be exchanged either parametrically or geometrically, according to user guidelines and system constraints. At the target system, the resulting model is represented using a history tree, regardless of the amount of original parametric features that have been rewritten as geometric ones. Using this method we maximize the exchange of overall parametric data and overcome one of the main stumbling blocks for feature-based data exchange.

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Available abstract

Data exchange between CAD systems is an extremely important solid modeling concept, fundamental both for the theory of the field and for its practical applications. The two main data exchange (DE) paradigms are geometric and parametric DE. Geometric DE is the ordinary method, in which the boundary representation of the object is exchanged. Parametric (or feature-based) DE is a novel method where, given a parametric history (feature) graph in a source system, the goal is to construct a graph in the target system that results in similar geometry while preserving as much parametric information as possible. Each method has its uses and associated problems.In this paper, we introduce Geometry Per Feature (GPF), a method for integration of parametric and geometric data exchange at the single part (object) level. Features can be exchanged either parametrically or geometrically, according to user guidelines and system constraints. At the target system, the resulting model is represented using a history tree, regardless of the amount of original parametric features that have been rewritten as geometric ones. Using this method we maximize the exchange of overall parametric data and overcome one of the main stumbling blocks for feature-based data exchange.

Key concepts: Boundary representation, Geometric primitive, Parametric statistics, Computer science, Solid modeling, Feature (linguistics), Geometric modeling, CAD

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