الفهرس 
High level topology
RESEARCH METHODOLOGYOnly 14 pages are availabe for public view
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Abstract
Mohamed Ahmed Awad. Extraction of Machining Features from Data File. Unpublished Doctor of
Philosophy thesis. Design and Production Engineering Department, Faculty of Engineering, Ain Shams
university,
1997
The process of producing a mechanical part can be divided into three major steps; design, process
planning and manufacturing. Today, many of the design and manufacturing activities have been
successfully automated with isolated CAD and CAM systems respectively. However, computer aided
process planning (CAPP), the link between these two systems, did not reach the same level of
success.
Process planning involves many activities to translate design requirements into a manufacturing
plan which are subjective, labor intensive and time consuming process. It is heavily dependent on
the knowledge and expertise of process planners. Automation of these activities will result in
accurate, consistent and cost effective process plans and bridge the gap between CAD and CAM
systems.
The main obstacle to CAPP is the different ways by which CAD and CAPP systems view and store the
part information. CAD systems define and store part information in terms of geometry and topology,
while CAPP systems require the information in the form of manufacturing features. Consequently,
automatic interpretation of part geometry and topology into their corresponding manufacturing
features is the only way to achieve CAPP. Automatic interpretation is a non trivial solution due to
the existence of many CAD representation schemes and many manufacturing feature sets, which are
process dependent. For each manufacturing process, a set of manufacturing features must be created
to represent its capabilities. Algorithms required to interpret a CAD part information into their
corresponding manufacturing features will be dependent on the CAD representation scheme used.
Since there are many different types of manufacturing processes, the scope of this thesis will be
limited to machining processes which are commonly used in manufacturing.
Some researchers have addressed the problem by restricting the designer to use only machining
features during the design process. This approach is unrealistic since it requires a high level
of manufacturing knowledge on the part of the designer. Other researchers developed feature
recognition algorithms to extract high level semantic knowledge from different CAD
representation schemes. However, all these attempts limited their work scope to the
extraction of form features which are not directly related to machining features.
The objective of this research is to develop an algorithm by which the machining features can be
extracted from the major CAD representation schemes, geometrical and technical CAD systems.
The algorithm consists of three major modules; form feature extraction, machining feature mapping
and tool accessibility validation. In the first module, form features are extracted from
low level primitive CAD information with an entity growing procedure. The second module
maps either form features determined in the first module or design features from a
feature based CAD data file into their corresponding machining features. Some of the features
are converted by an entity growing procedure while others by a decomposition
algorithm. In the third module, tool accessibility is used to guarantee that all the
machining features are globally accessible. Otherwise, an alternative set of features is
created. The algorithm has been implemented on an IBM PC computer using the C++ language. Three
case studies were utilized to demonstrate the capabilities of the developed algorithm.
Computer Aided Design
KEYWORDS
Feature Recognition
Computer Aided Manufacturing
Computer Aided Process Planning
Feature Extraction
Feature Mapping