Paper Info
Title
Efficient Phase Ii Monitoring Methods For Linear Profiles Under The Random Effect Model
Abstract
A profile is a functional relationship between two or more variables used to monitor the process performance and its quality. Sometimes, the aforementioned relationship is linear or nonlinear depending upon the situation. A monitoring method based on the linear profiles is known as linear profiling which is commonly used due to its simplicity and efficacy. Linear profiling methods have been studied by many researchers with a fixed effect model. However random effect model provides a more suitable interpretation as compared to the fixed effect model under different real-time monitoring methods. Therefore in this article, we are intended to propose a linear profiling EWMA method (EWMA(x[R])-3 chart) and MEWMA(x[R]) chart based on the random effect model using different ranked set sampling techniques such as ranked set sampling (RSS), extreme RSS (ERSS), median RSS (MRSS), double RSS (DRSS), double ERSS (DERSS) and double MRSS (DMRSS). The ranked set sampling (RSS) schemes are not only cost-effective method but also an efficient mechanism as compared to simple random sampling. A designed simulation study used Average Run Length (ARL) as an evaluation measure to witness the detection ability of newly offered EWMA(x[R])-3 chart, MEWMA(x[R]) chart and existing EWMA(x[SRS])-3 chart. The extensive simulation showed that the proposed EWMA(x[R])-3 chart and MEWMA(x[R]) chart have superiority to detect faults in the process compared to a competitive counterpart. The results are further justified with real data application related to a combined cycle power plant.
Year
DOI
Venue
2019
10.1109/ACCESS.2019.2946211
IEEE ACCESS
Keywords
DocType
Volume
Average run length, double RSS, EWMA, intercept, linear profiles
Journal
7
ISSN
Citations 
PageRank 
2169-3536
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Abbas Tahir1164.99
Faisal Rafique200.34
Tahir Mahmood39528.76
Muhammad Mohsin Riaz447586.44