한국정밀공학회지 제12권 제8호 (1995월 8월)
선삭가공시 절삭조건에 의한 chip형태의 분류와 예측에 관한 연구
ABSTRACT In recent years, the rapid development of the machine tool and tough insert has made metaI removal rates increase, and automatic system without human supervision requires a higher degree reliability of machining process. Therefore the control of chips is one of the important topics which deserves much attention. The chip classification was made based upon standard deviation of the mean cutting force measured by a tool dynamometer. STS304 was chosen as the workpiece which is known as the difficult-to-cut material and mainly saw-toothed chip produced, and the chip type according to the standard deviation of mean cutting force was classified into five categories in this experiment. Long continuous type chip which interrupts the normal cutting process, and damages the operator, tool and workpiece has low standard deviation value, while short broken type chip. which is favourable chip for disposal, has relatively large standard deviation value. In addition. we investigated the possibility that the chip type can be predicted analyzing the relationship between chip type and cutting condition by the trained neural network, and obtained favourable results by which the chip type can be predicted with cutting condition before cutting process. Key words : difficult-to-cut material(난삭재), standard deviation(표준편차), chip type (칩형태), neural network (신경회로망)
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