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Lycourgos Kyprianou
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Lycourgos Kyprianou : ウィキペディア英語版
Lycourgos Kyprianou
Dr.Lycourgos Kyprianou was the former chairman of GlobalSoft and AremisSoft Corp.
Also known for his pioneering work on the development of computational feature recognition. The first ever published work on features was for the original boundary representation modelling system, BUILD, and was performed by Dr. Kyprianou.
==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 (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.

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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