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|Document Type: ||Thesis or dissertation|
|Title: ||A knowledge based manufacturing advisor for CAD|
|Authors: ||Lockett, Helen L.|
|Supervisors: ||Guenov, Marin D.|
|Issue Date: ||Jul-2005|
|Abstract: ||This thesis presents a knowledge based manufacturing advisor for Computer Aided
Design. The aim of the project has been to develop techniques that can help designers to
evaluate the manufacturability of moulded parts during the design process.
One of the major achievements in the research has been the development of a novel
feature recognition approach to allow moulding features to be recognised from a CAD
model. Existing feature recognition techniques are not appropriate for moulded parts
and a new feature recognition approach has been developed that uses a mid-surface
abstraction from the CAD solid model as the basis for feature recognition. The feature
recognition methodology presented in this research is a graph based technique that uses
an attributed mid-surface adjacency graph as the basis for feature recognition. Feature
recognition algorithms have been developed for a range of common moulding features.
Two evaluation techniques are presented that measure the quality of the feature
recognition results and provide a confidence measure for the manufacturing advice that
is generated. The first evaluation technique uses the Hausdorff distance to measure the
similarity of the mid-surface model to the CAD solid model that was used to generate it,
and the second uses a face mapping technique to evaluate the completeness of the
feature recognition results.
A demonstrator for the knowledge based manufacturing advisor has been developed
which incorporates the feature recognition software and an expert system for moulding
advice. The expert system provides an interactive software environment in which the
user can input details about their part design, and receive tailored manufacturing advice
for a range of moulding processes. The demonstrator has been tested on a range of
realistic moulded parts.|
|Appears in Collections:||PhD and Masters by research theses (School of Engineering)|
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