Feature conversion for concurrent engineering
PhD student - Klaas Jan de Kraker |
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Today's development of industrial products faces high demands. Products must be developed fast, and must be of good quality. For product developers, this implies integration of traditionally separated product development phases, i.e. concurrent engineering.
For concurrent engineering, functional product information is required. Design by features enables to model a product with both geometric and functional properties. Using feature validation, the intended functional product properties are maintained under model modifications.
Hence, the ideal product development environment integrates concurrent engineering and feature modelling. Each engineering discipline is represented by a so-called view. Each view contains features relevant to the specific discipline. Communication between different views requires feature conversion, which translates modifications to a feature model in one view to another.
For concurrent engineering using feature modelling, a product model has been developed. It consists of a shared central geometry and constraint representation, and a feature model for each view. The product geometry representation is a cellular data structure to which feature instances refer.
Two types of feature conversion have been developed that propagate feature model geometry and topology changes between views. Geometry changes are propagated using automatically derived geometric constraints. Topology changes are propagated using generic view specifications, the cellular model, and a newly developed feature recognition technique.
This new feature recognition technique is a generic and hierarchical technique which is called top-down feature recognition. At the top level, it prescribes feature classes in a specified order, ensuring meaningful feature interpretations. At the lower level, instances of a feature class are recognized based on geometric reasoning; it has the advantage that it can handle intersecting features.
This project has been supported by the Netherlands Computing Science Reserach Foundation (SION), with financial support from the Netherlands Organization for Scientific Research (NWO).