Machining, Measurement, and Control Laboratory

2 0 0 0    C o n f e r e n c e    P a p e r

High Speed and High Productive Drilling by Intelligent Machine Tools
--Integration of the Cutting Conditions Planning and Adaptive Control 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.)

This study aims to achieve the total machining process optimization in drilling processes by integrating the cutting conditions planning and adaptive control. The first question we have to ask here is how to determine adequate cutting conditions when drilling several workpieces, especially when the hardness of each workpiece is different and unknown. The proposed method determines the initial cutting condition based on the standard material characteristics that are stored in the database. The cutting process characteristics are identified during drilling processes, and the database is updated based on the on-line identification.

Furthermore, a method to select an optimal adaptive control method among many candidates is proposed. This method estimates the performance index, such as the total cutting time, based on the cutting process model before actual cutting, and selects the optimal adaptive control method.

Simulation case-studies are also shown to validate the effectiveness of the proposed approaches. The first case study considers the successive drilling of shallow holes on cast iron workpieces. The cutting time is reduced by about 40%. The second case study considers a deep hole drilling process on steel workpieces. The cutting time is reduced by about 5-20%.

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