Alexander Balduhn
Sponsored by CODEF
Abstract- For the face milling process, many algorithms have been developed
to optimize the tool path with respect to the burr formation process,
and to predict the occurrence of burrs. However, collecting data to
create the factual knowledge base for face milling burr expert systems
has long been seen as too costly and time consuming due to the many
parameters that influence the burr formation process in the face milling
operation. A suitably designed part that captures in essence the distinguishing
mechanisms of burr formation can be very beneficial in reducing the
number of experiments performed. This paper describes the geometry of
a workpiece and the machining strategy employed to generate the distinct
face milling burr formation mechanisms. Measurement is limited to burr
size parameters that directly influence the functionality of the workpiece
edge and the ease of burr removal in further processing. The burr data
collected after machining the specially designed workpiece is stored
in the database. The database is designed using an Entity-Relationship
model. This high level conceptual model helps structure the data in
a fashion that renders this database highly suitable for planning applications.
The database is designed to handle the most important queries raised
by a process planner. For example, identifying insert materials that
generate the smallest burrs for a given workpiece material, and so forth.
The database also directly interfaces with the optimization programs
like burr prediction and tool path planning that were developed for
burr minimization in face milling. In addition, this database can be
used as a standalone system, i.e. a "burr expert", to recommend
cutting parameters or tools for a specific material.
Keywords: burr expert system, face milling, edge quality, database.
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