Open AccessEvaluation of Variable Parameter MCV Control Chart in Downward Process Shifts
Author(s) -
XinYing Chew
Publication year - 2021
Publication title -
wseas transactions on systems and control/wseas transactions on systems and control
Language(s) - English
Resource type - Journals
eISSN - 2224-2856
pISSN - 1991-8763
DOI - 10.37394/23203.2021.16.43
Subject(s) - control chart , ewma chart , multivariate statistics , chart , process (computing) , shewhart individuals control chart , variance (accounting) , statistics , statistical process control , computer science , markov chain , x bar chart , variable (mathematics) , process variable , \bar x and r chart , mathematics , mathematical analysis , accounting , business , operating system
Previous studies revealed that the coefficient of variation (CV) is important in ensuring process quality, especially for monitoring a process where its process mean and variance are highly correlated. The fact that almost all industrial process monitoring involves a minimum of two or more related quality characteristics being monitored simultaneously. The existing adaptive charts for monitoring the multivariate CV are focused on detecting upward process shifts. The downward process monitoring is crucial since it shows process improvement. Very little research works are available on the downward adaptive multivariate CV chart. This makes it difficult for the quality engineer who wishes to implement the adaptive multivariate CV chart on the downward process monitoring. Therefore, this paper filled the research gap by proposing a downward variable parameter chart for the multivariate coefficient of variation. The performance measures of the proposed charts are derived based on the Markov-chain approach. Numerical comparisons between the proposed and existing charts have been made, in terms of the average time to signal criterion. The findings reveal that the proposed charts outperform the existing charts for detecting small and moderate downward process shifts