Volume 28, Issue 4 (IJIEPR 2017)                   IJIEPR 2017, 28(4): 367-376 | Back to browse issues page

XML Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Noorossana R, Najafi M. Change Point Estimation in High Yield Processes in the Presence of Serial Correlation. IJIEPR. 2017; 28 (4) :367-376
URL: http://ijiepr.iust.ac.ir/article-1-687-en.html
1- Iran Universirt of Science and Technology , rassoul@iust.ac.ir
2- Kar University
Abstract:   (1822 Views)

Change point estimation is as an effective method for identifying the time of a change in production and service processes. In most of the statistical quality control literature, it is usually assumed that the quality characteristic of interest is independently and identically distributed over time. It is obvious that this assumption could be easily violated in practice. In this paper, we use maximum likelihood estimation method to estimate when a step change has occurred in a high yield process by allowing a serial correlation between observations. Monte Carlo simulation is used as a vehicle to evaluate performance of the proposed method. Results indicate satisfactory performance for the proposed method.

Full-Text [PDF 303 kb]   (535 Downloads)    
Type of Study: Research | Subject: Quality Control
Received: 2016/08/3 | Accepted: 2017/12/4 | Published: 2018/01/20

Add your comments about this article : Your username or Email:

Send email to the article author

© 2020 All Rights Reserved | International Journal of Industrial Engineering & Production Research

Designed & Developed by : Yektaweb