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신경망을 이용한 유연디스크 디버링가공 아크형상구간 인자예측에 관한 연구
유송민,Yoo, Song-Min 한국생산제조학회 2009 한국생산제조학회지 Vol.25 No.2
Disk grinding was often applied to deburring process in order to enhance the final product quality. Inherent chamfering capability of the flexible disk grinding process in the early stage was analyzed with respect to various process parameters including workpiece length, wheel speed, depth of cut and feed. Initial chamfered edge defined as arc zone was characterized with local radius of curvature. Averaged radius and arc zone ratio was well evaluated using neural network system. Additional neural network analysis adding workpiece length showed enhance performance in predicting arc zone ratio and curvature radius with reduced error rate. A process condition design parameter was estimated using remaining input and output parameters with the prediction error rate lower than 2.0% depending on the relevant input parameter combination and neural network structure composition.
신경망을 이용한 유연디스크 가공 종단부 품질예측에 관한 연구
유송민,Yoo, Song-Min 한국생산제조학회 2010 한국생산제조학회지 Vol.26 No.1
Even though a flexible disk grinding process was often applied to enhance the product quality, it produced non-flat zone in the beginning and the exit (end) area. Since latter area is susceptible to poor product quality with burn mark, careful analysis is required to cope with such degradation. The flexible disk grinding exit stage was analyzed for workpiece length, wheel speed, depth of cut and feed. The exit stage qualities defined as exit stage ratio and exit stage angle or slope was characterized. A neural network application results reveled that exit stage characteristics was predicted more accurately without workpiece dimension with minimum error of 1.3%.