Session: DFMLC-08-01-Special Session-Design Tool Showcase

Paper Number: 97865

97865 - Improved Method for Extracting Difficult-to Machine Shapes Using Multiple Milling Simulation Results 

Most existing design for manufacturability (DFM) systems detect difficult-to-machine shapes in a part by comparing the registered shape patterns with the CAD model of the part. To use these systems, it is necessary to examine and register the shape pattern in which machining is difficult. The time and cost for the registration are a large hindrance to the popularization of the DFM system.

To address such difficulties, we previously developed a software technology to assist in the design of machine parts with high machinability. Our DFM system is milling-simulation-based, and it detects shapes that cannot be machined using available cutters by repeatedly executing milling simulations with cutters. The milling simulations were executed from six cutting directions: ± X, ± Y, and ± Z directions (the spindle direction of the cutter was fixed in the + Z axis direction, and the milling operations from different directions were realized by changing the posture of the workpiece). Our system visualizes the remaining shapes unmachined after all simulations as difficult-to-machine shapes. The only preparation required for using this system is the shape information of the available cutters. No pre-registration of the difficult-to-machine shape patterns is necessary when using the system.

This paper describes an enhanced software technology that improves the extraction and visualization capability of difficult-to-machine shapes. Contrary to our previously reported software, the current software is equipped with a recognition function for the shape features. By controlling the milling simulation process according to the recognized features, more accurate simulation results can be obtained. The current software can visualize the extracted difficult-to-machine shape by superposing and displaying the shape left unmachined after milling simulations on the CAD model of the part. By examining this shape, the reason for the difficulty in machining can be visually understood, and it can be referred to in the design improvement. We implemented the software and applied it to CAD models of parts to evaluate its practicality.

Presenting Author: Masatomo Inui Ibaraki University

Presenting Author Biography: Masatomo Inui is a professor in the Department of Mechanical Systems Engineering at Ibaraki University, Japan. His current research interests include geometric modeling and its application to the automation of mechanical manufacturing. Inui received his doctorate in precision machinery engineering from the University of Tokyo. He is a member of IEEE and ASME. Contact him at masatomo.inui.az@vc.ibaraki.ac.jp.

Authors:

Masatomo Inui Ibaraki University
Qi Chen Ibaraki University
Nobuyuki Umezu Ibaraki University