Sentence examples for multivariate process and from inspiring English sources

The multivariate control charts [Hotelling ({T}^{2}) control chart, multivariate CUSUM (MCUSUM), multivariate EWMA (MEWMA)] have been used for the control of multivariate process and have proved their adequacy to reduce the complexity of such process monitoring.

To realize a complete monitoring system for multivariate process and simplify the reconfiguration task to the operators that are not specializing in the realm, we developed an expert system that assures the process correction.

Based on T2 and SPE charts in the feature space, KPCA was applied to fault detection in two example systems: a simple multivariate process and the simulation benchmark of the biological wastewater treatment process.

In addition to trial allocation, significant psychosocial predictors of screening in these individuals were identified through an iterative univariate and multivariate process and the final model is shown as Table  9.

In this paper, we propose a new single control chart which integrates the exponentially weighted moving average (EWMA) procedure with the generalized likelihood ratio (GLR) test for jointly monitoring both the multivariate process mean and variability.

In this paper, a new nonlinear multiscale-MSPC method is proposed to address multivariate process performance monitoring and in particular fault diagnostics in nonlinear processes.

These expectations have substantially increased the demands of experimental data collection, process monitoring, and multivariate process understanding.

In order to build the recycling process in a product lifecycle effectively and efficiently, a process integration should be required among manufacturing planning, modularity design and multivariate process validation.

The designing of surface engineered nanocrystals for improved stability and bioavailability is a multivariate process depending on several critical formulation and process variables.

Moreover, the monitoring of a multivariate process is a complex task, and it can be devised into four subtasks which are: the detection of abnormal situation, the diagnosis of the faults, the identification of variables that involved in the faults and finally the reconfiguration of the process (Venkatasubramanian et al. 2003).

The purpose of this research is to explore the relationship among multivariate process capability indices, expected losses and design reliability for the nominal-the-better case so the likelihood and consequence resulting from the failure of a multi-characteristic engineering design can be evaluated simultaneously.