Machining, Measurement, and Control Laboratory
 

2 0 0 0    J o u r n a l    P a p e r

 
 
 
 
A study on drilling process control by intelligent machine tools (1st Report)
--Determination of cutting condition for drilling--
 
Tomonori Sato (Mitsubishi Electric Corp.)
Yoshiaki Kakino (Kyoto University)
Atsushi Matsubara (Kyoto University)
Makoto Fujishima (Mori Seiki Co., Ltd.)
Isao Nishiura (Mori Seiki Co., Ltd.)
Kouji Kamatani (West Japan Railway Co.)
 
 
 
Abstract

This project considers a method to determine cutting conditions in drilling processes of several workpieces. The design of cutting conditions in a drilling process is particularly important and difficult when there are considerable uncertainties in the hardness of each workpiece. The proposed method determines initial cutting conditions based on the nominal characteristics of the workpiece material, which are stored in the database. The material characteristics are identified during drilling processes, and the database is updated based on on-line identification. This "learning cycle" optimizes the cutting conditions even when the hardness of the workpiece material is not known. By optimizing the cutting conditions, one can expect more efficient machining without reducing the tool life. Simulation and experimental results show that the total cutting time is reduced by about 40%.

 
 
 
 
 
 
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