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A study on the exit stage quality prediction of flexible disk process using neural network  

Yoo, Song-Min (경희대학교 공과대학 기계공학과)
Publication Information
Journal of the Korean Society of Manufacturing Technology Engineers / v.19, no.6, 2010 , pp. 760-767 More about this Journal
Abstract
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%.
Keywords
Flexible disk grinding; Exit stage; Neural network; Stage characteristics;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
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