دانلود مقاله ISI انگلیسی شماره 153437
ترجمه فارسی عنوان مقاله

بهینه سازی کیفیت چندگانه در حفاری برق از ورق فولادی خفیف

عنوان انگلیسی
Multiple Quality Optimizations in Electrical Discharge Drilling of Mild Steel Sheet
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
153437 2017 10 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Materials Today: Proceedings, Volume 4, Issue 8, 2017, Pages 7252-7261

ترجمه کلمات کلیدی
حفاری برق تخلیه، سوراخ دایره ای، حفره سوراخ، بهینه سازی چند هدفه، الگوریتم ژنتیک،
کلمات کلیدی انگلیسی
Electrical Discharge Drilling; Hole Circularity; Hole Taper; Multi-objective Optimization; Genetic Algorithm;
پیش نمایش مقاله
پیش نمایش مقاله  بهینه سازی کیفیت چندگانه در حفاری برق از ورق فولادی خفیف

چکیده انگلیسی

The small diameter holes in different materials by using conventional drilling methods are challenging tasks. But such types of holes may be done by using advanced machining processes. Among the different advanced machining processes, the electrical discharge drilling may be applied with certain advantages over other processes. But electrical discharge drilling has certain defects or disadvantage at the drill specimen due to sparking such as hole circularity and hole taper. These may be optimized by selecting the optimum process parameter levels. In this study, the experiments have been conducted by well-planned orthogonal array L27 in the electrical discharge drilling of mild steel sheet. For the experimentation, discharge current, pulse on time, pulse off time and dielectric pressure have been selected as input process parameters and hole circularity & hole taper as output parameters. The multi regression models for hole circularity and hole taper have been developed by using the experimental data. The statistical analysis for the developed models shows that the models are reliable and adequate and may be used for predicting these quality characteristics satisfactorily. These quality characteristics have been optimized by using genetic algorithm MATLAB tool. In the genetic algorithm optimization, the regression models for circularity and taper have been considered as objective function. The multi-objective optimization result obtained by genetic algorithm, show improvements in both of the quality characteristics.