کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10407584 | 893052 | 2013 | 14 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A multivariate surface roughness modeling and optimization under conditions of uncertainty
ترجمه فارسی عنوان
مدل سازی و بهینه سازی سطحی چند متغیره در شرایط عدم اطمینان
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
کنترل و سیستم های مهندسی
چکیده انگلیسی
Correlated responses can be written in terms of principal component scores, but the uncertainty in the original responses will be transferred and will influence the behavior of the regression function. This paper presents a model building strategy that consider the multivariate uncertainty as weighting matrix for the principal components. The main objective is to increase the value of R2 predicted to improve model's explanation and optimization results. A case study of AISI 52100 hardened steel turning with Wiper tools was performed in a Central Composite Design with three-factors (cutting speed, feed rate and depth of cut) for a set of five correlated metrics (Ra, Ry, Rz, Rq and Rt). Results indicate that different modeling methods conduct approximately to the same predicted responses, nevertheless the response surface to Weighted Principal Component - case b - (WPC1b) presented the highest predictability.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Measurement - Volume 46, Issue 8, October 2013, Pages 2555-2568
Journal: Measurement - Volume 46, Issue 8, October 2013, Pages 2555-2568
نویسندگان
Luiz Gustavo D. Lopes, José Henrique de Freitas Gomes, Anderson Paulo de Paiva, Luiz Fernando Barca, João Roberto Ferreira, Pedro Paulo Balestrassi,