Volume 32, Issue 1 (IJIEPR 2021)                   IJIEPR 2021, 32(1): 1-11 | Back to browse issues page


XML Print


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

Noorossana R, Khalili S. Phase II monitoring of auto-correlated linear profiles using multivariate linear mixed model. IJIEPR. 2021; 32 (1) :1-11
URL: http://ijiepr.iust.ac.ir/article-1-845-en.html
1- IUST , rassoul@iust.ac.ir
2- 1. Industrial Engineering Department, Azad University, South-Tehran Branch, Tehran, Iran.
Abstract:   (651 Views)
In the last few decades, profile monitoring in univariate and multivariate environment has drawn a considerable attention in the area of statistical process control. In multivariate profile monitoring, it is required to relate more than one response variable to one or more explanatory variables. In this paper, the multivariate multiple linear profile monitoring problem is addressed under the assumption of existing autocorrelation among observations. Multivariate linear mixed model (MLMM) is proposed to account for the autocorrelation between profiles. Then two control charts in addition to a combined method are applied to monitor the profiles in phase II. Finally, the performance of the presented method is assessed in terms of average run length (ARL). The simulation results demonstrate that the proposed control charts have appropriate performance in signaling out-of-control conditions.
 
Full-Text [PDF 724 kb]   (259 Downloads)    
Type of Study: Research | Subject: Quality Control
Received: 2018/08/9 | Accepted: 2020/08/23 | Published: 2020/12/11

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

Send email to the article author


© 2021 All Rights Reserved | International Journal of Industrial Engineering & Production Research

Designed & Developed by : Yektaweb