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Reliability Evaluation of STD-11 Cutting Surface on the Machined Condition using the Back-Propagation Neural Network  

Kim Sun-Jin (서강정보대학 소방안전관리과)
Sung Back-Sub (국립목포대학교 선계해양시스템공학부)
Cho Gyu-Jae (조선대학교 기계공학과)
Kim Ha-Sik (조선이공대학 컴퓨터응용기계과)
Ban Jae-Sam (광주테크노파크 LED／LD패키징시험생산기술지원센터)
Publication Information
Transactions of the Korean Society of Machine Tool Engineers / v.13, no.5, 2004 , pp. 7-15 More about this Journal
Abstract
The purpose of this study was to present the method to choose the optimum machining condition for the wire EDM. This was completed by examining the ever-changing quality of the material and by improving the function of the wire electric discharge machine. Precision metal mold products and the unmanned wire electric discharge machining system were used and then applied in industrial fields. This experiment uses the wire electric discharge machine with brass wire electrode of 0.25mm. To measure the precision of the machining surface, average values are obtained from 3 samples of measures of center-line average roughness by using a third dimension gauge and a stylus surface roughness gauge.
Keywords
Variation of hand drum form; Back-propagation; Variance technique; Standard error of estimaie; Coefficient of multiple correlation; Coefficient of determination;
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  • Reference
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