کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5452629 1513782 2017 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Optimization of machining parameters to improve the surface quality
ترجمه فارسی عنوان
بهینه سازی پارامترهای ماشینکاری برای بهبود کیفیت سطح
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی مواد شیمی مواد
چکیده انگلیسی
The preparation of quality surfaces is very important process in the surface engineering. The surface roughness will influence the quality and effectiveness of the subsequent coatings for protection against corrosion, wear resistance and finishes quality of decorative layers. For these reasons, the authors of the present work have focused in manufacturing parameters that influence the surface quality of hardness metallic materials. In this work, the effects of varying four parameters in the milling process, namely cutting speed, feed rate, radial depth and axial depth. The influence of these parameters on the surface roughness are analyzed individually and also the interaction between some of them for the milling machining of hardened Steel (steel 1.2738), being used the Taguchi optimization method. For this purposed was built a L16 orthogonal array and for each parameter were defined two different levels, corresponding to sixteen experimental tests. From these tests were retrieved sixteen surface roughness measurements The influence of each parameter in surface roughness were then obtained by applying the analysis of variance (ANOVA) to experimental data. It is noted that the minimum roughness measured was 1.05µm. This study also serve to determined the contribution of each machining parameters and their interaction for surface roughness. The results show that the radial cutting depth and the interaction between the radial and axial depth of cut are the most revelevant parameters, being their contributions for the minimization surface roughness about 30% and 24%, respectively.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Procedia Structural Integrity - Volume 5, 2017, Pages 355-362
نویسندگان
, , ,