3,947 research outputs found
One-sided Downward Control Chart for Monitoring the Multivariate Coefficient of Variation with VSSI Strategy
In recent years, control charts monitoring the coefficient of variation (CV), denoted as the ratio of the variance to the mean, is attracting significant attention due to its ability to monitor processes in which the process mean and process variance are not independent of each other. However, very few studies have been done on charts to monitor downward process shifts, which is important since downward process shifts show process improvement. In view of the importance of today's competitive manufacturing environment, this paper proposes a one-sided chart to monitor the downward multivariate CV (MCV) with variable sample size and sampling interval (VSSI), i.e. the VSSID MCV chart. This paper monitors the MCV as most industrial processes simultaneously monitor at least two or more quality characteristics, while the VSSI feature is incorporated, as it is shown that this feature brings about a significant improvement of the chart. A Markov chain approach was adopted for designing a performance measure of the proposed chart. The numerical comparison revealed that the proposed chart outperformed existing MCV charts. The implementation of the VSSID MCV chart is illustrated with an example
Optimal statistical designs of multivariate EWMA and multivariate CUSUM charts based on average run length and median run leng
Carta kawalan multivariat ialah alat yang berkuasa dalam kawalan proses yang
melibatkan kawalan serentak beberapa cirian kualiti yang berkorelasi. Carta-carta
multivariat hasil tambah longgokan {MCUSUM) dan multivariat purata bergerak
berpemberat eksponen (MEWMA) sentiasa dicadangkan dalam kawalan proses
apabila pengesanan cepat anjakan tetap yang keciJ atau sederhana dalam vektor min
adalah diingini.
A multivariate control chart is a powerful tool in process control involving a
simultaneous monitoring of several correlated quality characteristics. The multivariate
cumulative sum (MCUSUM) and multivariate exponentially weighted moving average
(MEWMA) charts are often recommended in process monitoring when a quick
detection of small or moderate sustained shifts in the mean vector is desired
Quantitative infrared thermography resolved leakage current problem in cathodic protection system
Leakage current problem can happen in Cathodic Protection
(CP) system installation. It could affect the performance of
underground facilities such as piping, building structure, and
earthing system. Worse can happen is rapid corrosion where
disturbance to plant operation plus expensive maintenance
cost. Occasionally, if it seems, tracing its root cause could be
tedious. The traditional method called line current
measurement is still valid effective. It involves isolating one
by one of the affected underground structures. The recent
methods are Close Interval Potential Survey and Pipeline
Current Mapper were better and faster. On top of the
mentioned method, there is a need to enhance further by
synthesizing with the latest visual methods. Therefore, this
paper describes research works on Infrared Thermography
Quantitative (IRTQ) method as resolution of leakage current
problem in CP system. The scope of study merely focuses on
tracing the root cause of leakage current occurring at the CP
system lube base oil plant. The results of experiment
adherence to the hypothesis drawn. Consequently, res
A LASSO Chart for Monitoring the Covariance Matrix
Multivariate control charts are essential tools in multivariate statistical process control. In real applications, when a multivariate process shifts, it occurs in either location or scale. Several methods have been proposed recently to monitor the covariance matrix. Most of these methods use rational subgroups and are used to detect large shifts. In this paper, we propose a new accumulative method, based on penalized likelihood estimators, that uses individual observations and is useful to detect small and persistent shifts in a process when sparsity is present
Optimal Designs Of Univariate And Multivariate Synthetic Control Charts Based On Median Run Length
Univariate and multivariate control charts are usually optimally designed using average run length (ARL) as a sole measure of the charts’ performances. It is well known that the shape of the run length distribution for the univariate and multivariate charts changes from highly skewed when the process is in-control to approximately symmetric for large process shifts. Therefore, the median run length (MRL) is a more meaningful interpretation of the in-control and out-of-control performances of the charts and provides additional information not given by the average run length (ARL)
- …