نتایج جستجو برای: multivariate process hotelling t2 control chart multi
تعداد نتایج: 2974117 فیلتر نتایج به سال:
The method of change (or anomaly) detection in high-dimensional discrete-time processes using a multivariate Hotelling chart is presented. We use normal random projections as a method of dimensionality reduction. We indicate diagnostic properties of the Hotelling control chart applied to data projected onto a random subspace of R. We examine the random projection method using artificial noisy i...
This paper deals with the application of Principal Component Analysis (PCA) and the Hotelling’s T2 Chart, using data collected from a drinking water treatment process. PCA is applied primarily for the dimensional reduction of the collected data. The Hotelling’s T2 control chart was used for the fault detection of the process. The data was taken from a United Utilities Multistage Water Treatment...
Adaptive sample size and sampling intervals schemes have been widely used to improve the statistical efficiency of Hotelling T control chart in detecting small changes when the quality of a product or a process can be characterised by the multivariate distribution of quality characteristics. In this paper, we design a Hotelling T scheme varying sample sizes and sampling intervals (VSSI-T) for a...
The monitoring of a multivariate process with the use of multivariate statistical process control MSPC charts has received considerable attention. However, in practice, the use of MSPC chart typically encounters a difficulty. This difficult involves which quality variable or which set of the quality variables is responsible for the generation of the signal. This study proposes a hybrid schemewh...
The usual procedure when employing a T2 control chart for multivariate process monitoring is to take samples of fixed size n0 every h0 hours from the process. Recent studies have shown that using variable parameters (VP) schemes results in charts with more statistical power when detecting small to moderate shifts in the process mean vector. In this paper, the VPT2 control chart for monitoring t...
The objective of the current paper is to present an intelligent system for complex process monitoring, based on artificial intelligence technologies. This system aims to realize with success all the complex process monitoring tasks that are: detection, diagnosis, identification and reconfiguration. For this purpose, the development of a multi-agent system that combines multiple intelligences su...
Multivariate control charts such as Hotelling`s T^ 2 and X^ 2 are commonly used for monitoring several related quality characteristics. These control charts use correlation structure that exists between quality characteristics in an attempt to improve monitoring. The purpose of this article is to discuss some issues related to the G chart proposed by Levinson et al. [9] for detecting shifts in ...
Control charts are graphical tools widely used to monitor manufacturing processes to quickly detect any change in a process that may result in a change in product quality. The statistic plotted on a control chart is based on samples of n ≥ 1 observations (rational subgroups) that may be taken at regular sampling intervals. However, there are numerous practical applications using individual obse...
In the development of industrial processes there are situations where it is necessary to control or simultaneously monitor two or more quality variables of the production process. The problems of process monitoring where several related variables are studied can be controlled by means of multivariate control charts. The objective of this work is to describe the implementation of the control cha...
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