Machining, Measurement, and Control Laboratory
 

2 0 0 0    J o u r n a l    P a p e r

 
 
 
 
A study on advanced drilling by intelligent machine tools
(1st Report)
--Monitoring of tool failure and improvement of productivity--
 
Makoto Fujishima (Mori Seiki Co., Ltd.)
Yoshiaki Kakino (Kyoto University)
Atsushi Matsubara (Kyoto University)
Tomonori Sato (Mitsubishi Electric Corp.)
Isao Nishiura (Mori Seiki Co., Ltd.)
 
 
 
Abstract

Two adaptive control schemes are proposed for high-productivity drilling processes. First, an adaptive control scheme of the drill's feed rate is considered. The cutting force in a drilling process is estimated by monitoring the motor current of the spindle motor and feed drive servo motors, and thus no additional sensor is required. The feed rate is controlled such that the cutting force is kept constant during drilling processes to avoid tool chippings. Furthermore, an automated pecking control is also proposed. A pecking is known to be crucial to avoid tool breakage due to the chip jamming particularly in a drilling process of deep holes. The proposed algorithm determines the timing of peckings based on the estimated cutting force. An intelligent drilling process control system is developed integrating those two functions. The improvement in the productivity of drilling processes is verified in experimentation using the developed system.

 
 
 
 
 
 
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