A Proposed Ultraprecision Machining Process Monitoring Method Using Causal Network Model of Air Spindle System
Hiroshi Sawano, Ryosuke Kobayashi, Hayato Yoshioka,
and Hidenori Shinno
Precision and Intelligence Laboratory, Tokyo Institute of Technology, 4259 Nagatsuta, Midori-ku, Yokohama, Kanagawa 226-8503, Japan
Future ultraprecision machining systems require inprocess monitoring and intelligent machining control functions. This paper presents a newly developed machining process monitoring method. The method proposed aims at monitoring the ultraprecision machining process using a causal network model of an air spindle system. The results of actual machining experiments confirm that the proposed method can estimate the dynamic and thermal behaviors at the cutting point during machining. In consequence, the process monitoring method proposed can systematically predict the tool wear, the contact condition between the tool and the workpiece, the abnormal machining conditions, and so on.
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