کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8942583 | 1645105 | 2018 | 53 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Nonparametric control schemes for profiles with attribute data
ترجمه فارسی عنوان
طرح های کنترل غیرمعمول برای پروفایل با داده های ویژگی
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
داده های مشخصه، میانگین متحرک متوسط وزن، آزمون نسبت امید، هموار سازی کرنل خطی نظارت بر مشخصات، کنترل فرآیند آماری،
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی صنعتی و تولید
چکیده انگلیسی
Attribute data are very common in the real production and service processes. Therefore, many kinds of control charts for attribute data have been studied in the literature. On the other hand, profile monitoring has been a popular statistical process control (SPC) problem recently. Moreover, in some cases, the response variables of profiles are attribute data, such as binary or Poisson data. Thus, the research on SPC for profiles with attribute data is very important, which motivates us to undertake this current research and try to develop a unified framework for monitoring such kind of profiles. In this paper, the unified framework of control schemes based on the nonparametric regression is proposed, including the generalized likelihood ratio chart, the T2 chart and the exponential weighted moving average chart. These schemes could tackle linear or nonlinear profiles with a wide class of response variables belonging to the exponential family of distributions. The performance of the proposed control charts is studied under the binomial and Poisson profiles by numerical simulations. Furthermore, two examples are used for illustrating the implementation of the proposed control charts.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Industrial Engineering - Volume 125, November 2018, Pages 87-97
Journal: Computers & Industrial Engineering - Volume 125, November 2018, Pages 87-97
نویسندگان
Yanfen Shang, Zhiqiong Wang, Yang Zhang,