Indexing 5-Axis Machining Process Design Support System Shortening Die Fabrication Lead Time

Yoshihiko Yamada; Toshiyuki Okita; Yoshimasa Kuwano

doi:10.4028/www.scientific.net/KEM.523-524.392

Paper Titles

Surface Generation for Magic-Mirror by End-Milling and Magnetic Polishing with Digitally Functioned CNC Machining Center
p.368

Biofabrication of Biopolymer and Biocomposite Scaffolds for Bone Tissue Engineering
p.374

Method to Decide Paths and Postures of Flat End Mill for 5-Axis Control Machining Based on Minimum Cusp Height
p.380

Proposal of Ball End-Milling Condition Decision Methodology Using Data-Mining from Tool Catalog Data
p.386

Indexing 5-Axis Machining Process Design Support System Shortening Die Fabrication Lead Time
p.392

Generation of NC Program for Realizing High Speed Feed Rate of Cutting Tool
p.398

Development of Orthros, an Evaluation System for Free Curved Plate Thickness with a Robot - Generation of the Path Considering Collision
p.404

Reuse of Digital Mock-Up Data by Using Shape Matching
p.410

Automatic Reverse Engineering Based on Reconstructing Measurement Data in 3D-Lattice
p.414

HomeKey Engineering MaterialsKey Engineering Materials Vols. 523-524Indexing 5-Axis Machining Process Design Support...

Indexing 5-Axis Machining Process Design Support System Shortening Die Fabrication Lead Time

Abstract:

In recent years, due to intensified global competitiveness in die machining, further reduction of lead time, lower costs and higher accuracy are in demand. 5-axis machining is receiving attention as a means to solving these issues. However, differing to the conventional 3-axis machining, complex thinking tasks such as determining tool orientation while considering interference are required in the process design phase prior to machining, which not only places pressure on even those experienced workers, but also consumes a significantly longer amount of time than that required for the actual machining itself. Accordingly, with the aim of shortening the overall lead time from machining process design through to machining itself, we have developed a support system which makes highly efficient indexing 5-axis machining process design possible in a short time even for inexperienced workers. This report presents the algorithms contrived and calculation test results.