TitleWhite layer thickness prediction in WEDM-ANFIS modeling
SourceMITC2015-pp 240-241
AuthorIbrahem Maher, Ahmed A.D. Sarhan, Houriyeh Marashi, Mohsen Marani Barzani, M. Hamdi


Wire Electric Discharge Machining (WEDM) is a nontraditional technique by which the required profile is acquired using spark energy. Regarding wire cutting, precision machining is necessary to achieve high product quality. White Layer Thickness (WLT) is one of the most important factors for assessing superior surface finish. In this research, Adaptive Neuro-fuzzy Inference System (ANFIS) was used to predict the WLT in WEDM using coated wire electrode. The predicted data were compared with measured values, and the average prediction error for WLT was 2.61 %. 


MITC2015-pp 240-241