Laboratory for Manufacturing and Sustainability

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.